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Environmental determinants of vascular plant species richness in the Austrian Alps
Abstract
Aim To test predictions of different large-scale biodiversity hypotheses by analysing species richness patterns of vascular plants in the Austrian Alps.Location The Austrian part of the Alps (c. 53,500 km2).Methods Within the floristic inventory of Central Europe the Austrian part of the Alps were systematically mapped for vascular plants. Data collection was based on a rectangular grid of 5 × 3 arc minutes (34–35 km2). Emerging species richness patterns were correlated with several environmental factors using generalized linear models. Primary environmental variables like temperature, precipitation and evapotranspiration were used to test climate-related hypotheses of species richness. Additionally, spatial and temporal variations in climatic conditions were considered. Bedrock geology, particularly the amount of calcareous substrates, the proximity to rivers and lakes and secondary variables like topographic, edaphic and land-use heterogeneity were used as additional predictors. Model results were evaluated by correlating modelled and observed species numbers.Results Our final multiple regression model explains c. 50% of the variance in species richness patterns. Model evaluation results in a correlation coefficient of 0.64 between modelled and observed species numbers in an independent test data set. Climatic variables like temperature and potential evapotranspiration (PET) proved to be by far the most important predictors. In general, variables indicating climatic favourableness like the maxima of temperature and PET performed better than those indicating stress, like the respective minima. Bedrock mineralogy, especially the amount of calcareous substrate, had some additional explanatory power but was less influential than suggested by comparable studies. The amount of precipitation does not have any effect on species richness regionally. Among the descriptors of heterogeneity, edaphic and land-use heterogeneity are more closely correlated with species numbers than topographic heterogeneity.Main conclusions The results support energy-driven processes as primary determinants of vascular plant species richness in temperate mountains. Stressful conditions obviously decrease species numbers, but presence of favourable habitats has higher predictive power in the context of species richness modelling. The importance of precipitation for driving global species diversity patterns is not necessarily reflected regionally. Annual range of temperature, an indicator of short-term climatic stability, proved to be of minor importance for the determination of regional species richness patterns. In general, our study suggests environmental heterogeneity to be of rather low predictive value for species richness patterns regionally. However, it may gain importance at more local scales.
... Although it has been reported widely that the biogeographical history of mountains has shaped diversity patterns of cold-adapted plant species in alpine regions Harris, 2007;McGlone et al., 2001;Sklenář et al., 2014), a major unresolved question is the extent to which the interplay of ecological drivers and historical contingencies dictates the patterns of alpine plant diversity at the global level (Nagy & Grabherr, 2009). The significance of these drivers might shift from global to local spatial scales and can reveal new patterns and relationships that are not evident at regional scales at which alpine plant diversity patterns have been studied so far (Jiménez-Alfaro et al., 2014;Lenoir et al., 2010;Moser et al., 2005;Vonlanthen et al., 2006). ...
... Although this might have resulted in a sharper delimitation of season lengths, it probably had little effect on our global analyses. We included the mean temperature, precipitation, growing degree days and mean potential evapotranspiration of the growing season, all of which have been reported to have positive effects on photosynthetic activity and species richness in alpine areas (Körner, 2003;Moser et al., 2005;Nagy & Grabherr, 2009). Growing degree days (i.e., the sum of monthly temperatures > .9°C ...
... This finding confirms the effect of habitat heterogeneity on species richness inherent to larger areas (Lomolino, 2000a) through the occurrence of more diverse bedrock types (Moser et al., 2005). ...
... Although it has been reported widely that the biogeographical history of mountains has shaped diversity patterns of cold-adapted plant species in alpine regions Harris, 2007;McGlone et al., 2001;Sklenář et al., 2014), a major unresolved question is the extent to which the interplay of ecological drivers and historical contingencies dictates the patterns of alpine plant diversity at the global level (Nagy & Grabherr, 2009). The significance of these drivers might shift from global to local spatial scales and can reveal new patterns and relationships that are not evident at regional scales at which alpine plant diversity patterns have been studied so far (Jiménez-Alfaro et al., 2014;Lenoir et al., 2010;Moser et al., 2005;Vonlanthen et al., 2006). ...
... Although this might have resulted in a sharper delimitation of season lengths, it probably had little effect on our global analyses. We included the mean temperature, precipitation, growing degree days and mean potential evapotranspiration of the growing season, all of which have been reported to have positive effects on photosynthetic activity and species richness in alpine areas (Körner, 2003;Moser et al., 2005;Nagy & Grabherr, 2009). Growing degree days (i.e., the sum of monthly temperatures > .9°C ...
... This finding confirms the effect of habitat heterogeneity on species richness inherent to larger areas (Lomolino, 2000a) through the occurrence of more diverse bedrock types (Moser et al., 2005). ...
Aim
Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales.
Location
Global.
Time period
Data collected between 1923 and 2019.
Major taxa studied
Vascular plants.
Methods
We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample‐based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed‐effect modelling framework.
Results
The latitudinal pattern of regional richness peaked around the equator and at mid‐latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid‐latitudes of the Northern Hemisphere, despite a considerable within‐region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors.
Main conclusions
In contrast to the well‐known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid‐latitudes, indicating that the diversity of alpine plants is linked to regional idiosyncrasies and to the historical prevalence of alpine ecosystems, rather than current macroclimatic gradients.
... So far, most of the published studies (e.g. Moser et al., 2005;Essl et al., 2009;Loidi et al., 2015) explored endemic species richness in relation to geographical and ecological factors, whereas little attention has been paid to endemic beta diversity patterns and their relative spatial configuration. Thus, a thorough understanding of the patterns of endemism and ecological factors underlying their distribution may have relevant implications for conservation purposes (Lamoreux et al., 2006;Essl et al., 2009). ...
... In particular, since the Last Glacial Maximum (LGM) and during the Pleistocene, large species fluctuations occurred in the Alps leading plant taxa to survive in disjunct refugia (Taberlet et al., 1998;Tribsch and Schönswetter, 2003;Essl et al., 2009), from where they may have recolonized surrounding areas. Other studies proved that current environmental features such as climate, elevation, topography, geology along with fine-scale effects (i.e. the size and spatial arrangement of habitats) affect present species distribution (Wohlgemuth, 1998;Lobo et al., 2001;Vetaas and Grytnes, 2002;Moser et al., 2005;Essl et al., 2009;Cañadas et al., 2014;Loidi et al., 2015;Brambach et al., 2017). However, as pointed out in Whittaker et al. (2001), probably it is the interplay between historical factors and current climatic conditions which influences species richness patterns and especially those of endemism. ...
... This suggests that greater topographical complexity might provide a higher variability of resources and, in turns, ecological niches for vascular plants (Kallimanis et al., 2011). On the other hand, the reduction J o u r n a l P r e -p r o o f in their spatial turnover maybe due to the high specialization required to grow in these extreme environments (Tribsch and Schönswetter, 2003;Moser et al., 2005;Noroozi et al., 2018). ...
Identification of center of endemism is a crucial issue to improve the understanding on overall biodiversity distribution and related conservation actions. Despite the well-known distribution of global endemic areas, less effort has been devoted in defining local hotspots and their ecological determinants. In this study, we analyzed the distribution and the spatial pattern of endemic diversity of vascular plant in the southeastern Italian Alps, aiming at identifying the occurrence of local hotspots and focusing on the relationships occurring between alpha (i.e. species richness) and beta diversity (i.e. Local Contributors of Beta Diversity) along with their ecological and spatial drivers. We observed that both alpha and beta diversity metrics have a strong negative relationship, showing a clear spatial pattern. Among the environmental drivers, geomorphological and climatic variables were the most influent, pointing out the importance of landscape heterogeneity and local oceanic climate conditions to favor endemic richness. We also found that historical factors (i.e. Last Glacial Maximum) significantly affected the pattern of endemic diversity. Interestingly, most of the variables showed contrasting effects on alpha and beta diversity. Our study proposes an approach for the identification of local hotspots of endemic species, which take into account both the spatially structured nature of ecological data and their associated environmental drivers. Our findings might provide new insight in the ecological process driving current endemic plant patterns and become pivotal for nature conservationist both to identify areas of high conservation value and to suggest appropriate management schemes also beyond existing protected areas.
... Processes and abiotic variability related to geofeatures include, but are not limited to, microclimatic and sheltering effects around landforms (e.g. hollows and ridges); erosion, water storage capacity, physical and chemical weathering, pH variability, and mineral and textural variety via geology and soil; and water storage, transfer, and connectivity via hydrological features and rock composition and soil texture (Moser et al. 2005;Guitet et al., 2014;. GDCs may also be linked to natural geomorphological and hydrological disturbance processes, which are relevant to vegetation diversity and distributions (e.g. ...
... Geodiversity therefore succeeded in capturing unique dimensions of environmental heterogeneity that have theoretical mechanistic links to species richness, and which add explanatory power when modelling vascular plant species richness patterns (Stein at al., 2014). This is consistent with our first hypothesis (H1), which was based on theorized links between biodiversity and the presence and diversity of both landforms and surface materials -reflecting the presence of more resources and greater habitat and niche variety (Moser et al. 2005;Lawler et al., 2015), and possibly the results of some disturbance processes (le . Also consistent with H1 was the decline in magnitude of the geodiversity contribution with increasing extent, at both grain sizes, as other variables (particularly broad-scale climate) took over. ...
... Indeed, the geophysical environment may be an important determinant of biotic patterns and therefore requires more explicit consideration in ecological research should allow us to implicitly capture these abiotic processes and conditions. These may include, for example: resources such as nutrients, water, and light; habitat diversity; microclimatic and sheltering effects; and soil moisture, texture and pH Keith 2011;Moser et al. 2005) (also see PAPER I). pH may be especially important in determining vegetation patterns and species diversity, as shown in arctic environments (Walker 2000;Ross et al. 2012). ...
EXTENDED THESIS ABSTRACT Context Understanding spatial patterns of biodiversity and species’ distributions is important for scientific theory, and for conservation and management of the natural world. Climatic variables are widely recognised as strong correlates of species richness over large spatial extents. Correlates of species richness at smaller extents (regional and landscape scales) are less well established, but environmental heterogeneity is widely thought to be important. A large number of environmental heterogeneity measures have been used, but in particular there is a growing interest in ‘geodiversity’, which I define here as the diversity of abiotic terrestrial and hydrological nature, comprising earth surface materials and landforms. Recent research has emphasised both geodiversity’s inherent value and its potential as a correlate and predictor of spatial biodiversity and species’ distribution patterns. However, despite this clear potential of geodiversity for improving our understanding of how patterns of life relate to environmental heterogeneity, its incorporation into biodiversity and species’ distribution modelling is substantially underdeveloped. In this thesis, using a macroecological approach I begin to address some of these knowledge gaps by analysing the relationships between geodiversity data, and its constituent ‘geofeatures’, and species richness and distributions for multiple taxa and across several scales (grain size and extent) and geographic locations. My main aims in this thesis are to more fully evaluate geodiversity itself, and improve our understanding of its role with respect to the spatial patterning of biodiversity, both conceptually and empirically. Locations and Spatial Scales Analyses were carried out within and across Great Britain (England, Scotland, and Wales) and Finland. The order of the four quantitative papers generally reflects the largest spatial extent (i.e. size of the study area) at which they were conducted, from national (PAPERS II and III) through landscape (PAPER IV), to the local scale (vegetation plots within a small upland river catchment; PAPER V). PAPER II is a study across several spatial extents (from landscape to national) and uses two grain sizes (1 km2 and 100 km2). PAPER I is a review paper that considers multiple scales and geographic locations conceptually. Time period Present day: data were from between 1995 and 2016 across all of the quantitative studies. Taxa Multiple: alien and native vascular plants across Great Britain (PAPER II); threatened bryophytes, beetles, fungi, lepidoptera, lichens, mammals, molluscs, and vascular plants across Finland (PAPER III); common and rare vascular plants across the Cairngorms, Scotland (PAPER IV); angiosperms, conifers, fungi, lichens, liverworts, lycophytes, mosses, and pteridophytes (and productivity) across an upland river catchment within the Cairngorms (PAPER V); and conceptual consideration of multiple taxa (PAPER I). Methods For studies in Great Britain, plant data were provided by the Botanical Society of Britain and Ireland (BSBI) for PAPERS II and IV, and by the Centre for Ecology and Hydrology (CEH) for PAPER V. The threatened species data in Finland were from Finnish Environment Institute (PAPER II). Species richness (PAPERS II, III, and IV), rarity-weighted richness (RWR; PAPER III), species’ distributions (PAPERS IV and V), and productivity (measured using NDVI from colour infrared aerial imagery; PAPER V) were all analysed using Boosted Regression Tree (BRT) modelling, allowing comparisons between studies. For geodiversity data in the British studies, I compiled geodiversity data on landforms, soils, hydrological and geological features using existing national datasets (e.g. British Geological Survey), and used a geomorphometric method to extract landform coverage data (landforms included: hollows, ridges, valleys, and peaks). These data were analysed alongside environmental data, which varied between papers, relating to climate, standard topography (e.g. slope; elevation), land use, and human population. The sources of other geodiversity data in Finland, and environmental data on topography and climate, came from a variety of sources, which are detailed within each paper. Results Geodiversity improved biodiversity and species’ distribution models throughout all of the quantitative analyses and generally declined in importance as spatial scale coarsened beyond the landscape scale. At most spatial scales and in most places, the roles of climate and/or coarse topography dominated, and geodiversity played a relatively small role, as was expected. Geodiversity, however, made consistent positive contributions to the models independently of traditionally used topographic metrics such as standard deviation of elevation and slope. Taxonomically, geodiversity: (i) was slightly more relevant for native vascular plants than alien in Great Britain (PAPER II); (ii) of similar relevance to common and rare vascular plants in the Scottish Highlands, except that the coverage of soil parent material was especially important for rare species’ distributions (PAPER IV); of similar relevance to most sessile taxa (angiosperms, fungi, mosses, liverworts, lichens, pteridophytes, and lycophytes; conifers were not related to geodiversity) in an upland Scottish river catchment (PAPER V); and more important for threatened vascular plants and bryophytes over other studied taxa in Finland (PAPER II). Geodiversity also improved models of productivity, and the variability in productivity, in PAPER V. Main conclusions and Future Directions Geodiversity improves our understanding of, and ability to model, the relationship between biodiversity and environmental heterogeneity at multiple spatial scales, by allowing us to get closer to the real-world conditions and processes that affect life. I found that the greatest benefit comes from measuring ‘geofeatures’, which describe the constituent parts of geodiversity separately, rather than as one combined variable. Automatically extracted landform data, the use of which is novel in ecology, biogeography and macroecology, proved particularly valuable throughout this body of work, and as too did data from expert geological and hydrological maps. The idea of ‘Conserving Nature’s Stage’ (CNS), and identifying areas that are most capable of supporting high biodiversity into the future, the benefits and caveats of which are discussed in this thesis, has recently emerged. It requires a sound empirical and conceptual basis, to which my research contributes. In this thesis, I have gone some way towards demonstrating the conceptual and empirical value of incorporating geodiversity into ecological analyses across multiple spatial scales, paving the way for this recent approach to be more extensively used for theoretical and applied purposes. I accomplished this by carrying out an assessment of existing geodiversity literature and, importantly, looking forwards to consider the prospects of geodiversity within ecology (PAPER I), supported by four quantitative studies. The conservation significance is emphasised in PAPER III. Much remains to be done, however, and future research directions are detailed in PAPER I. We need to develop predictive models to test the role of geodiversity across an array of geographical and taxonomic domains, as well as to assess metrics beyond species richness and species’ distributions. One example may involve beta diversity: does spatial turnover in species relate to spatial turnover in geofeatures? Fully analysing the role of geodiversity through time will also be important, including in relation to refugia, given predicted environmental changes in climate. In progressing with this line of enquiry, we will improve our knowledge and understanding of patterns of life on Earth and, specifically, how the geophysical landscape helps shape them.
... Energy factors and habitat heterogeneity were common ecological drivers of RCs between vascular plants and vertebrates in subtropical and temperate regions [11,31] rather than climatic stability, the productivity hypothesis, and soil properties. That might be correlated with the dominant and unique effects of energy and habitat heterogeneity on Diversity 2022, 14, 499 9 of 13 the richness patterns of multiple taxonomic groups at the regional or local scale via direct effects on the rate of genetic evolution [60][61][62][63]. ...
... That confirmed that the RCs among taxonomic groups in subtropical regions were stronger than those in temperate regions (p < 0.001, Figure 2b). The above differences might be related to the effect of abiotic factors on species richness of multiple taxonomic groups: energy generally plays more an important role in driving richness patterns of taxonomic groups than longitude [61,[63][64][65]. Further, RCs between vascular plants were promoted by area and PET (energy factor) in subtropical regions, whereas they were promoted by elevation range and longitude in temperate regions. ...
Identifying indicator taxa is a solution to the problem of a lack of diverse data. However, the variation between studies on richness correlations (RCs) among taxa from different climate regions makes the application value of indicator taxa questionable. Few studies have compared the RCs among climatic regions in a single study, leaving the variation in RCs and the underlying ecological drivers among climatic regions unknown. In this study, data were compiled on vascular plants, vertebrates (including mammals, birds, reptiles, and amphibians), and environmental factors across 219 nature reserves located in subtropical and temperate regions of China to examine RCs among taxonomic groups and underlying ecological mechanisms. Results showed that the climatic region could affect between-taxon correlations in species richness and that the effectiveness of vascular plants as suitable indicator taxa for vertebrates varied with the climatic region and target taxa. Energy (temperature and evapotranspiration) and habitat heterogeneity (area and elevation range) were ecological drivers of RCs among taxonomic groups in the subtropical and temperate regions. The differences in the effect of abiotic factors on RCs among taxonomic groups caused the difference in RCs between subtropical and temperate regions. Our findings provide new evidence for understanding the variation of RCs and the underlying mechanisms and highlight the positive role of climatic variables and habitat heterogeneity in determining RCs between vascular plants and vertebrates.
... It is especially problematic when it involves organisms from different kingdoms and various body sizes (Jordano, 2016). Sampling taxa is far easier than sampling interactions, using naturalist knowledge (Moser et al., 2005), camera traps (Steenweg et al., 2017) or environmental DNA (Bohmann et al., 2014). A convenient case to study networks in space is then to build a potential network at the regional scale, the metaweb, using expert knowledge or machine learning methods to complete interaction databases (Strydom et al., 2021). ...
Trophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. We present here the R package metanetwork, which will ease the representation, the exploration and analysis of trophic metanetwork data sets that are increasingly available. Our main methodological advance consists in suitable layout algorithm for trophic networks, which is based on trophic levels and dimension reduction in a graph diffusion kernel. In particular, it highlights relevant features of trophic networks (trophic levels, energetic channels). In addition, we developed tools to handle, compare visually and quantitatively and aggregate those networks. Static and dynamic visualisation functions have been developed to represent large networks. We apply our package workflow to several trophic network data sets.
... Water plays an essential role in facilitating plant photosynthesis, nutrient transport, and metabolism (Nobel 2009). Conversely, Energy, in the form of temperature, radiation and productivity, also impact species richness via (i) trophic cascades which states that plant richness is limited by the energy owing through food web and (ii) physiological mechanism which states that the ambient energy inputs are more deterministic rather than food availability for species richness (Hawkins et al. 2003; Moser et al. 2005). Climatic variables are instrumental in explaining approximately 50 to 70% of variations in species richness distributions, underscoring the signi cant role of climate (O'Brien 1998). ...
Introduction
Conservation efforts have traditionally focused on biodiversity hotspots, overlooking the essential ecological roles and ecosystem services provided by cold spots. Cold spots are areas outside biodiversity hotspots, characterized by low species diversity and harboring rare species living in threatened habitats.
Aim
This study aims to predict the present and future plant species distribution in cold spots across India, considering various environmental and non-environmental variables.
Location
India
Methods
The Indian national-level plant species database generated through the project ‘Biodiversity Characterization at Landscape Level’ was used. The species modelling (70% randomly selected training data) was carried out for four major biogeographic zones of India namely Arid and semi-arid zone, Deccan peninsula, and Gangetic plain. Generalized Linear Model (GLM), Generalized Boosted Model (GBM), Random Forest (RF), Support Vector Machine (SVM), and ensemble modeling were compared to predict species distribution. Future representative concentration pathways (RCP4.5 & RCP8.6) were used to forecast species distribution.
Results
The study demonstrated good predictive ability with water and energy variables dominating in all zones, showing a strong agreement with the observed data (30% subset of the original data). Temperature annual range, annual precipitation, and precipitation of the driest month (bio7, bio12, and bio14) significantly influenced (r > 0.4) plant species patterns in the arid and semi-arid zone. Ensemble modeling showed improved results when validated with observed data, exhibiting a significant reduction in the RMSE and an improved correlation (r=0.8). Non-environmental variables (elevation and human influence index) showed significant influence in combination with water and energy variables in the Deccan peninsula zone.
We observed continuous species loss in both future climate scenarios. Among biogeographic zones, the semi-arid and arid zones showed the maximum probable increase in species, with 69% and 52.5% of grids gaining species in 2050 (RCP4.5) and 69% and 84.7% of grids gaining species in 2070 (RCP8.6) respectively.
Conclusion
The study provides insights into the species richness distribution of cold spots in major Indian biogeographic zones, supporting their climate-derived patterns at a macro-scale. Ensemble modeling proves to be more accurate than individual models, emphasizing its potential for conservation efforts. The study calls for a performance-based conservation approach, prioritizing criteria to safeguard valuable ecosystems and prevent species loss.
... Unlike woody-species richness, the influences of elevation and terrain ruggedness index affect the herb richness insignificantly. This suggests woody species richness is more dependent on physiography than herb richness, which supports that physiography is not a prominent determinant in grasslands (Moser et al., 2005;Marini et al., 2009). The slope does not show a significant impact on herb or woody species richness, it is an important variable in overall plant richness. ...
The Indian parts of the Eastern Himalayas extend over 5,24,190 km2 and have >52% contribution to the whole Eastern Himalayas. The vegetation is broadly dominated by evergreen broadleaved forests with a dense canopy cover. Its complex physiography supports the rich diversity of about 5800 species in India with trees and shrubs accounting for >55% of its total species pool. Herbs are abundant representing >34% of its total plant population (Panda (2018) Environmental determinants of plant richness in Indian Himalaya. Ph.D. Thesis, submitted to Indian Institute of Technology Kharagpur, p 218). Several studies have been done to understand the underlying causes of rich species diversity of the Eastern Himalayas. Most of the studies focus on the overall plant richness pattern along an elevation gradient (Grytnes and Vetaas, Am Nat 159:294−304, 2002; Bhattarai et al. J Biogeogr 31:389−400, 2004; Behera et al. For Ecol Manage 207(3):363–384, 2005; Behera and Kushwaha, Biodivers Conserv 16:851−865, 2007; Chettri et al. (2010) Biodiversity in the Eastern Himalayas: status, trends and vulnerability to climate change. International Centre for Integrated Mountain Development (ICIMOD); Acharya et al. Acta Oecol 37(4):329–336, 2011; Sharma et al. Biodivers Conserv 28(8):2085–2104, 2019). A little emphasis is given to understanding life-form richness (Manish et al., 2017). No study accounts for unraveling the causes of species-environmental relationships of the Indian Eastern Himalayas involving climate, physiognomy, soil, and disturbance, simultaneously. A distinctive study on the relationships between water-energy dynamics and environmental heterogeneity of plant life-forms of the Indian Eastern Himalayas is rarely attempted. Therefore, a study that disentangles the plant-environmental relationships of the Indian Eastern Himalayas has great ecological significance. It is crucial for good management and conservation practices of this mountain ecosystem.Keywords
Disturbance
Herbs
Generalized additive model
Life forms
Plant richness
Structural equation model
Soil
Woody species
... While most of these studies are regional (Whittaker et al., 2007;Svenning & Skov, 2007;Marini et al., 2008;Wang et al., 2009), some global analyses are also done (Kreft & Jetz, 2007;Hawkins et al., 2011;Sommer et al., 2010). Emphasis is given to European regions and temperate forests, e.g., the Alps (Moser et al., 2005;Albuquerque et al., 2011;Pérez & Font, 2012). Two major studies are in Africa (O'Brien et al., 2000;Thuiller et al., 2006) and some in Asia, particularly in China (Li et al., 2013;Qian, 2013). ...
Data, data collection, selection, and methodology play key roles in ecological analysis. Data collected by appropriate methodology, and with the proper organization are essential for good interpretation. Based on the scientific problem to answer, data collection procedures are designed for sampling. And an appropriate sampling method solves major parts of the research and the results are considered logical. Therefore, quality data determines the accuracy of the research and ecological interpretations, in particular. However, it is not always possible to preplan data collection; and suitable data for analysis need preprocessing. Preprocessing looks into the quality aspects of the data and helps in preparing a reasonable dataset for analysis. It involves the careful removal of correlated variables, replacement or removal of missing values, transformations, and feature selection. Data types and sources are also crucial for quality research, where a scientific approach to feature optimization matters a lot. This chapter discusses all these issues related to proper data selection and modeling in ecological analysisKeywords
Data filtering
Decision tree
Multicollinearity
Principal component analysis
Species distribution modelling
... Qian (2013) advocates a strong correlation between elevation and climate ultimately shapes the woody richness in mountains. This also explains why physiography is not a prominent determinant in grasslands (Moser et al., 2005;Marini et al., 2008). Independently, the slope does not show a significant impact on herb or woody species richness or overall plant richness. ...
The Western Himalayas is geomorphologically complex with an altitudinal extent of >8000 m and is dominated by herbs accounting for >63% of its species pool. Shrubs and trees represent >30% of the species pool (Panda (2018) Environmental determinants of plant richness in Indian Himalaya. Ph.D. Thesis, submitted to Indian Institute of Technology Kharagpur, 218 p). In general, the southern part of the Western Himalayas is species-rich, with an angiosperm diversity of about 19,395 species in the Indian state of Himachal Pradesh, i.e., 7% of the world’s total (Karthikeyan (2000) A statistical analysis of flowering plants of India. In: NP Singh, DK Singh, PK Hajra and BD Sharma (eds) Flora of India introductory volume part II, 201–217, New Delhi). Understanding the causes of high species richness in the Western Himalayas has always been an interesting topic and crucial for its sustainable biodiversity management. Several studies highlight the species diversity, community structure, and distribution patterns of the Western Himalayas (Chawla et al., 2008; Sharma et al. Sci World J 2014), and along the elevation gradient of its adjacent areas (Oommen and Shanker, Ecology, 86:3039–3047, 2005; Wang et al. Divers Distrib 13:845–854, 2007; Yan et al., 2015). But a comprehensive account of species-environment relationships in Indian parts of the Western Himalayas is rarely documented. No study accounts for unraveling causes of species-environment relationships involving climate, physiognomy, soil, and disturbance, simultaneously. A study that focuses on the relationships between water-energy dynamics and environmental heterogeneity on plant life-forms of the Indian Western Himalayas is lacking in the literature. Therefore, the study that disentangles the environmental determinants of the life form richness of the Indian Western Himalayan plants has great ecological significance and is crucial for good management practices and conservation of this mountain ecosystem.Keywords
Herbs
Human footprintsGeneralized additive model
Life forms
Plant richness
Structural equation modelWoody species
... Die Verbreitungsdaten wurden mit Umweltvariablen in Beziehung gesetzt. Die zur Berechnung verwendeten Umweltvariablen werden ausführlich in MOSER et al. (2005) vorgestellt, so dass hier nur kurz auf die verwendeten Variablen eingegangen wird (Tab. 1): Die potenzielle Evapotranspiration (das ist die maximal mögliche Verdunstung durch Pflanzendecke und Bodenoberfläche unter den gegebenen Klimabedingungen) zur Sommersonnenwende (PET) ist sehr eng mit Temperatur und der für Photosynthese zur Verfügung stehenden Energiemenge korreliert. ...
... Mountain pastures are complex semi-natural systems located in the subalpine and alpine belts, displaying a wide variety of sizes, shapes, and elevational zones (Nettier et al., 2017;Peringer et al., 2013). They are also among the richest mountain ecosystems in terms of species thanks to extensive human management (animal grazing) over the centuries (Kampmann et al., 2008;Nicod et al., 2019) and climatic gradient (Kikvidze et al., 2011;Moser et al., 2005). In all major mountains of Europe, livestock farming systems rely on high-elevation grasslands to feed the herds. ...
Mountain pastures are essential for maintainig biodiversity and local economies. Despite the great value and fragility of these ecosystems, an up-to-date overview of extent and type of alpine pastures is lacking in many areas of the Alps. In this study, the interpretation of ancillary information combined with expeditious field campaigns, and the harmonization of classification methodologies allowed us to: (1) define the spatial extent of mountain pastures; (2) identify the non-grazeable percentage in these areas; (3) Characterize and map pasture types within the Gran Paradiso National Park (Italy), where 4596 ha of grazeable areas were mapped. Among the 13 categories identified, the three most represented in the park are Bare thermophile grasslands (38%), Nardus swards (20%), and Alpine intermediate grasslands (18%). The maps obtained in this study are useful for animal management during the grazing season, and have the capability of geographically assessing potential forage avaibility through modeling and remote sensing data.
... mentation(EEA, 2011;Jaeger, 2000;Moser et al., 2005;Schmiedel & Culmsee, 2016). Population density was also extracted from EEA(EEA, 2009). ...
Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad‐scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental‐scale management plans for biodiversity conservation. We modeled EU habitat richness at continental scale as a function of geographic, climatic, and anthropogenic variables. We found geographical variables were by far the most strongly correlated with habitat richness, followed by climate. However, anthropogenic variables gained importance when considering their interactions, with important implications for conservation planning.
... Isto sugere que a partição de energia entre as espécies, a diferenciação de habitat e a tolerância a ambientes variáveis podem ser os principais fatores ecológicos que determinam a variação na riqueza de Squamata no Cerrado -o que corrobora a "hipótese da energia disponível", que prediz que o particionamento de energia entre as espécies é um fator chave na determinação da riqueza de espécies (WRIGHT, 1983). De acordo com as previsões desta hipótese, a riqueza deve estar altamente correlacionada com temperatura, precipitação e evapotranspiração potencial, porque uma maior energia disponível pode suportar mais espécies (FRASER;CURRIE, 1996;MOSER et al., 2005). ...
No contexto da Biologia da Conservação, o Capítulo 04 discute os princípio teóricos e metodológicos de modelagem climática e distribuição geográfica de espécies, demostrando a urgência da manutenção da riqueza de espécies para a conservação do bioma.
... The regression equations for these figures are described in Table S3 (Supplementary Material 5) Species found in colder areas have a greater freezing tolerance (Sakai 1975). The latitudinal and elevational distribution ranges of individual species are narrower than those of the three functional types, and the factors affecting plant distributions change from the large, overall climatic conditions to factors like light and edaphic conditions at smaller scales (Moser et al. 2005;Takahashi and Murayama 2014;Ohdo and Takahashi 2020). Therefore, a test of the abundant-center hypothesis would be more ideal for individual species than for the overall functional type because the limiting abiotic factors of species distributions differ among plant species within a functional type (Toledo et al. 2012). ...
As per the abundant-center hypothesis, the cold- and warm-edges of the latitudinal and elevational distributions of vegetation are the result of physiological limitations caused by abiotic stress. The stand-level productivity per leaf mass of plants is an integrated physiological measure of whole-plant carbon gain. The abundant-center hypothesis specifically predicts that the productivity per leaf mass decreases at cold-edges and warm-edges. In the Japanese archipelago, the dominant functional types of trees change from evergreen hardwoods in the south to deciduous hardwoods and evergreen conifers in the north, forming latitudinal ecotones. This study tested the abundant-center hypothesis by analyzing the productivity per leaf mass of each functional type along a gradient of mean annual temperature (MAT), using forest inventory data. Although productivity per leaf mass was variable along the MAT, it neither increased nor decreased with MAT for each functional tree type. The productivity per leaf mass was also noted to not decrease at the cold-edges for evergreen and deciduous hardwoods or at the warm-edges for deciduous hardwoods and evergreen conifers. Productivity per leaf mass was not positively correlated with abundance. Thus, this study did not support the abundant-center hypothesis. Instead, physiological or ecological limitations, particularly at the seedling and sapling stages, may be the important process affecting the distribution edges of these three functional types.
... Reviews include [10][11][12]. On a regional scale (resolution 5-20 km), links between Ns and climate were mostly studied; links at this scale were weaker, but depend on groups or life forms of plants [13][14][15]. ...
Links with climate of richness of species (Ns), genera (Ng) and families (Nf) for 28 polygons each 400 km2 in Middle Volga were studied. Negative correlations with temperatures T and positive with precipitation P of the warm period were revealed, and T and P most strongly affected diversity. Closest links with climate were for Nf, and the least for Ns. We estimated gradients of T and P in four geographic directions. The most pronounced are northern cold-humid and southeastern thermo-arid trends. The northern trend is characterized by a decrease in T by 0.34°C and an increase in P by 17 mm per 100 km; southeast- with an increase in T by 0.27°C and a decrease in P by 15 mm. The cold-humid trend provides the most favorable conditions for the growth of diversity in the region. In it, Ns increased by 36, Ng-by 17, Nf-by 6 per 100 km. For floras with highest Nf and Ng, closer links with T, P and directions are revealed; in contrast to Ns. This indicates the ecological plasticity of the diversity, with different responses to climate variations for different taxonomic levels, which contribute to the preservation of diversity in a heterogeneous climate.
... This use of annual rainfall and minimum monthly PET probably originates as the model was developed in South Africa, where snowfall is very rare (and hence, rainfall = precipitation), and minimum PET was used to capture seasonality of thermal regime. However, here we evaluate a more flexible WED model that includes not only the woody plants in a region where snowfall is common and where the minimum mean monthly PET will be insufficiently discriminating (Moser et al. 2005). Therefore, we use precipitation and annual PET, as suggested by the Holdridge equation (cf. ...
Spatial variation in plant species diversity is well-documented but an overarching first-principles theory for diversity variation is lacking. Chemical energy expressed as Net Primary Production (NPP) is related to a monotonic increase in species richness at a macroscale and supports one of the leading energy-productivity hypotheses, the More individuals Hypothesis. Alternatively, water-energy dynamics (WED) hypothesizes enhanced species richness when water is freely available and energy supply is optimal. This theoretical model emphasises the amount and duration of photosynthesis across the year and therefore we include the length of the growing season and its interaction with precipitation. This seasonal-WED model assumes that biotemperature and available water represent the photosynthetically active period for the plants and hence, is directly related to NPP, especially in temperate and alpine regions. This study aims to evaluate the above-mentioned theoretical models using interpolated elevational species richness of woody and herbaceous flowering plants of the entire Himalayan range based on data compiled from databases. Generalized linear models (GLM) and generalized linear mixed models (GLMM) were used to analyse species richness (elevational gamma diversity) in the six geopolitical sectors of the Himalaya. NPP, annual precipitation, potential evapotranspiration (derived by the Holdridge formula), and length of growing season were treated as the explanatory variables and the models were evaluated using the Akaike Information Criterion (AIC) and explained deviance. Both precipitation plus potential evapotranspiration (PET), and NPP explain plant species richness in the Himalaya. The seasonal-WED model explains the species richness trends of both plant life-forms in all sectors of the Himalayan range better than the NPP-model. Despite the linear precipitation term failing to precisely capture the amount of water available to plants, the seasonal-WED model, which is based on the thermodynamical transition between water phases, is reasonably good and can forecast peaks in species richness under different climate and primary production conditions.
... Besides competition for light, it is likely that root competition takes place in dense alpine grasslands (Grabherr, 1989). Naud et al. (2019) showed a unimodal relationship of species richness per 1 m × 1 m plot with elevation whereby species diversity was limited by competition at low elevation and by a smaller species pool at high elevation (Moser et al., 2005). However, at the mesoscale, there is a decrease in the richness of vascular plants along the elevation gradient above the treeline (Theurillat et al., 2003). ...
The alpine life zone is expected to undergo major changes with ongoing climate change. While an increase of plant species richness on mountain summits has generally been found, competitive displacement may result in the long term. Here, we explore how species richness and surface cover types (vascular plants, litter, bare ground, scree and rock) changed over time on different bedrocks on summits of the European Alps. We focus on how species richness and turnover (new and lost species) depended on the density of existing vegetation, namely vascular plant cover. We analyzed permanent plots (1 m × 1 m) in each cardinal direction on 24 summits (24 × 4 × 4), with always four summits distributed along elevation gradients in each of six regions (three siliceous, three calcareous) across the European Alps. Mean summer temperatures derived from downscaled climate data increased synchronously over the past 30 years in all six regions. During the investigated 14 years, vascular plant cover decreased on siliceous bedrock, coupled with an increase in litter, and it marginally increased on higher calcareous summits. Species richness showed a unimodal relationship with vascular plant cover. Richness increased over time on siliceous bedrock but slightly decreased on calcareous bedrock due to losses in plots with high plant cover. Our analyses suggest contrasting and complex processes on siliceous versus calcareous summits in the European Alps. The unimodal richness-cover relationship and species losses at high plant cover suggest competition as a driver for vegetation change on alpine summits.
... We also performed alternative selections of plots with 75% and 90% cumulative cover of species with trait and phylogenetic data to assess the effect of a more conservative cumulative cover threshold on the model results (Appendix S2). Then, we built a set of climatic variables known to affect alpine vegetation (Körner, 2003;Moser et al., 2005;Nagy & Grabherr, 2009) using data from the CHELSA bioclimatic database at ~1-km spatial resolution (Karger et al., 2017 for the spatial aggregation of plots and unmeasured regional effects on the estimated functional dissimilarity, we calculated the pair-wise geographical distances between plots. Finally, we modelled functional community dissimilarity against these three distanced-based predictors using multiple regression on distance matrices (MRM) with the "lm" function. ...
Questions
What are the functional trade‐offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities?
Location
Global.
Methods
We compiled a data set of alpine vegetation with 5,532 geo‐referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade‐offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance.
Results
The first two PCA axes explained 66% of the species’ functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible.
Conclusions
Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.
... Although the current understanding of the regularities is far from complete [1], SR is associated with climate and energy required for photosynthesis, which explains more than 80% of SR dispersion in a global scale. At the regional level, the relationships between SR and environmental factors are usually weaker due to a narrower range of environmental conditions [2,3]. The ecological and morphological characteristics of the floristic composition of the study area are often described using the spectrum of life forms (LF) [4]. ...
Specially protected natural conservation areas in the Middle Volga River region serve to preserve both rare and endangered species and the entire biotic complex, including typical floristic communities of vascular plants. We have identified 25 sites, 100 km ² each, where the flora is represented in full the most. We studied the relationships between the general species richness (SR) and the richness of particular life forms (LF) of vascular plants with climate and relief using multiple regression methods. Our study shows that the special function of March precipitation is the factor that influences the most the spatial change of the SR and LF. When increasing the precipitation in the model by only 1 mm, this leads to a decrease in the number of species by 7.1%. Winter precipitation and temperature are important factors as well; together they are responsible for 70-82% of the SR variation. These close links made it possible to develop the maps of the species richness of the study area. The SR model did not include solar radiation, one of the most important environmental factors, as a significant predictor. This factor was omitted due to the analysis of the number of species of particular LF, which showed the maximum illumination of the slopes as a highly significant factor for number of them. The two dominant LFs (hemicryptophytes and therophytes), which account for 73% of the total number of species, depend oppositely on the illumination. This fact indicates a decrease in competition between LFs due to their separation in space, since hemicryptophytes, in contrast to therophytes, predominate on well-illuminated slopes. In addition, opposite LF responses lead to omitting of illumination factor from the SR model for all species in the region.
... Temperature change with elevation is one of the strongest drivers of biotic stress affecting the spatial distribution of the mountain vegetation (Jump et al., 2009;Körner, 2007;Körner and Paulsen, 2004). Although several studies overall reported a peak in species richness at middle elevations (Rahbek, 1995;Grytnes, 2003), there is evidence that temperature represents a major constraint for plant diversity at high elevation in the Alps (Moser et al., 2005;Pellissier et al., 2012), supporting the hypothesis that fewer species are physiologically adapted to cold alpine environments (Körner, 1999). In line with this, temperature change is a strong determinant for plant trait variation along elevation both at the intra-and inter-specific level (Midolo et al., 2019;Read et al., 2014). ...
Functional traits of mountain grassland communities strongly depend upon temperature variation along elevational gradients. However, little is known to what degree the direction of such trait-temperature relationships is shaped by other environmental factors or land-use types. Here, we investigated context-dependent patterns of plant functional trait variation in alpine grassland communities. Specifically, we tested whether temperature (degree-days) variation along an elevational gradient, interacts with water availability, soil properties and land-use type to moderate such patterns. We used cover-abundance and plant-trait data from 236 grassland relevés of the Swiss Alps along an elevational range of 500–2400 m a.s.l. with plant traits being specific leaf area (L), seed releasing height (H) and seed mass (S). We used indices capturing different dimensions of plant functional diversity as response variables, i.e. community weighted mean (CWM), trait range (TR) and functional dispersion (FDis). Land-use type and water availability interacted significantly with degree-days determining the responses of multiple plant traits community attributes. Specific leaf area (CWML) and seed releasing height (CWMH) increased with temperature in meadows and pastures, while no significant trend was detected in fallows. In meadows, seed mass (CWMS) increased and was at the same time less constrained (higher TRS) with increasing temperature. In pastures and fallows, by contrast, no seed trait-temperature trends were detected. In addition, water availability interacted with increasing temperature affecting functional dispersion: FDisL decreased only in sites with higher site water balance and TRS and FDisS increased in sites with low mean summer precipitation. Our findings suggest that functional diversity of grasslands might respond to climate warming with strong ecological differences depending on land-use types and water availability. Based on our results, managed meadows and pastures most likely change in direction to species with more acquisitive strategies, whereas in fallows, no specific trajectory of change is expected.
... Indeed, the value of the vascular flora of Torrelodones is particularly high, contributed to by 767 types of vascular plants. A comparison of the number of taxa identified in the 21.9 km 2 over which the municipal terminus extends with the records of other countries and areas in Europe corroborates this assertion: 1521 species in Fennoscandia (1,288,125 km 2 in Denmark, Norway, Sweden and Finland) [88] (Saetersdal et al., 1998); 2922 indigenous and neophytic taxa in areas of high diversity like the Austrian Alps (53,500 km 2 ) [89]; 1423 species in Belgium (32,592 km 2 ) (Stieperaere, 1979) [90]; 2049 species in the British Isles (315,134 km 2 ) [91]; 3556 in the Czech Republic (78,866 km 2 ) [92]; 3660 species in Germany (357,386 km 2 ) [93]; 6276 species including 739 non-native elements in the Iberian Peninsula (583,832 km 2 ) [91]. Some 1 km 2 UTM grids in Torrelodones house more than 300 species. ...
In line with the Urban Agenda for the EU, this article highlights the importance of local actions in the conservation of biodiversity, both through specific activities and by increasing the availability of information. As such, the policies and projects related to the conservation of biodiversity have been analyzed here at different levels and, in particular, the initiatives undertaken in the Madrid Region, Spain. Consequently, two cases are presented that demonstrate the role that local administrations can play in improving the biodiversity database, and hence, in the effective protection of areas of significant environmental value. First, we will examine the effects that creating an environmental inventory of vegetation, flora and landscape has had in Torrelodones. Second, among the more recent environmental policies implemented in the municipality of Madrid are those that resulted in the environmental recovery of the urban section of the Manzanares River. Both these actions demonstrate how local authorities can contribute to the conservation of biodiversity at relatively low expense and in line with EU guidelines. Notably, this occurred despite the fact that competences in environmental matters in Spain are not municipal. In this context, the paper reflects on the untapped potential of the General Urban Planning Plans (PGOU) in deep knowledge and sustainable and responsible management of municipal environmental values.
... Mountain ecosystems are among the most varied and rich in terms of endemic and high-value species (e.g. Vare et al. 2003;Moser et al. 2005;Spehn and Korner 2005). Mountains support about one-quarter of the planet's biodiversity and have nearly half of the world's biodiversity hotspots (Singh 2011). ...
Medicinal, aromatic, wild food and other health and wellness-related natural plant resources found in Himalayan highlands include rare, endangered and threatened plant species and non-timber wild products. These are commonly described as NTFPs and MAPs. Sustainable wild harvesting and primary processing of these herbs for addressing poverty of poor pastoralists, farmers and local traders is a major challenge. Medicinal plants not only play a pivotal role in providing primary healthcare for poor people in mountain areas; increasingly, these niche products are being gathered, processed and sold in national and international markets for higher cash income. Prominent examples of high-value but threatened medicinal plants that are commonly used in the Ayurvedic and Tibetan systems of traditional medicine (Sowa Rigpa) are as follows: Ophiocordyceps sinensis, Neopicrorhiza scrophulariiflora, Picrorhiza kurroa, Nardostachys grandiflora, Dactylorhiza hatagirea, Podophyllum hexandrum, Aconitum spp., etc. Experience gathered to date suggests that technical, socioeconomic, institutional and policy inputs and instruments are required to develop niche and high-volume production in pastoral systems. This chapter analyses and recommends the following actions in enhancing future scope: (a) raising awareness through different formal and informal education means, (b) skill development in sustainable harvesting as well as grazing management, (c) production of organic and sustainably managed products, (d) integration of agricultural and pastoral livelihoods with off-farm activities through value chain development of major niche products that have high-value capturing potential, (e) improvement of degraded pasture and farmlands to enhance productivity of niche products and services, (f) conservation through sustainable use-oriented policy and legal reforms to implement integrated strategies of linking conservation of wild fauna and flora with sustainable pastoral production systems and (g) expansion of ecologically sensitive low-input high-return tourism, using pastoralists to provide services, particularly through their indigenous knowledge and improved local production practices. These measures are expected to help Himalayan countries to achieve several SDGs especially goal nos.1 and 2.
... Similar factors are also used on the regional scale (resolution ~10 km) [7,8]. Due to narrower climate variation ranges, the relationships with natural factors are usually weaker on this scale: for instance, they explain 50% of the SR variance in the Austrian Alps [9]. In the course of separate studies of plant groups in the mountains and foothills of California [7], the value of this parameter varied from 62% (shrubs) to 88% (perennial grasses). ...
... Nevertheless, they face many challenges, such as the effectiveness of reserve design, governance (Pressey et al. 2015), and anthropogenic change (Foxcroft et al. 2017), with generally few restrictions currently in place for preventing the introduction of non-native species (Pyšek et al. 2003). Most protected areas in Europe are in a mosaic of land use types that can form a network of potential sources for non-native species introductions (e.g., Foxcroft et al. 2017;Meiners and Pickett 2013). In addition, recent evidence shows that there is almost no difference in the patterns of non-native and invasive species inside and outside protected areas, suggesting that currently habitat protection has little or no effect on non-native species richness (e.g. ...
Networks of protected areas are fundamental for biodiversity conservation, but many factors determine their conservation efficiency. In particular, on top of other human-driven disturbances, invasions by non-native species can cause habitat and biodiversity loss. Jointly understanding what drives patterns of plant diversity and of non-native species in protected areas is therefore a priority. We tested whether the richness and composition of native and non-native plant species within a network of protected areas follow similar patterns across spatial scales. Specifically, we addressed three questions: (a) what is the degree of congruence in species richness between native and non-native species? (b) do changes in the composition of non-native species across ecological gradients reflect a similar turnover of native species along the same gradients ? (c) what are the main environmental and human disturbance drivers controlling species richness in these two groups of species? Species richness and composition of native and non-native plant species were compared at two spatial scales: the plot scale (10 m × 10 m) and the Protected Area scale (PA). In addition, we fit Generalized Linear Models to identify the most important drivers of native and non-native species richness at each scale, focusing on environmental conditions (climate, topography) and on the main sources of human disturbance in the area (land use and roads). We found a significant positive correlation between the turnover of native and non-native species composition at both plot and PA scales, whereas their species richness was only correlated at the larger PA scale. The lack of congruence between the richness of native and non-native species at the plot scale was likely driven by differential responses to fine scale environmental factors, with non-natives favoring drier climates and milder slopes (climate and slope). In addition, more non-native species were found closer to road-ways in the reserve network. In contrast, the congruence in the richness of native and non-native species at the broader PA scale was mainly driven by the common influence of PA area, but also by similar responses of the two groups of species to climatic heterogeneity. Thus, our study highlights the strong spatial dependence of the relationship between native and non-native species richness and of their responses to environmental variation. Taken together, our results suggest that within the study region the introduction and establishment of non-native species would be more likely in warmer and dryer areas, with high native species richness at large spatial scale but intermediate levels of anthropogenic disturbances and mild slope inclinations and elevation at fine scale. Such an exhaustive understanding of the factors that influence the spread of non-native species, especially in networks of protected areas is crucial to inform conservation managers on how to control or curb non-native species.
... This use of rainfall and minimum PET is probably because the model was developed in South Africa, where snowfall is very rare (rainfall = precipitation), and minimum PET may express a low probability of water deficiency. Here, we evaluate a more general WED model for twelve different types of organisms that include not only wood plants in a region where snowfall is common and where minimum PET will be a proxy for frozen water and not moist conditions (Moser et al., 2005). Therefore, we use precipitation and annual PET, expressed in mm per year as suggested by the Holdrige formula (cf. ...
Aim: Variation in diversity is a well-documented spatial pattern in biogeography, but an overarching climate-based theory of diversity is lacking. We evaluate two models of species richness related to species-richness-energy theory. One is based on net primary production (NPP) or the more individuals hypothesis (MiH), and the other is a model based on water-energy dynamics (WED). We use taxa from three kingdoms along an extensive elevation-temperature gradient. Both WED and NPP-MiH are based on thermal energy, but the question is whether energy operates through regulating production and chemical (potential) energy only (NPP-MiH), or if kinetic energy as regulator of available liquid water is needed (WED). Location: Central Himalayas. Methods: The biodiversity, that is, elevational gamma diversity, of 12 taxa containing animals, plants, and fungi was estimated from range data along an elevation gradient. Generalized linear models were fitted to the species richness data, and the Akaike information criterion (AIC) and deviance explained were used to evaluate the NPP-MiH and WED models. In addition, we tested the relationships with precipitation and length of growing season (LGS) and their interaction. Results: The peaks in richness of the taxa are dispersed along the entire Himalayan bioclimatic gradient from the subtropics to the alpine zone. WED performs best for all taxa along the entire gradient. In the non-tropical zone, NPP-MiH is best for reptiles , and NPP-MiH and WED are equally good for mammals and amphibians. Including the length of the growing season in the WED model improves the AIC for eight taxa, and WED is superior for combined cross-taxon biodiversity along the entire gradient, but WED and NPP-MiH are equally good in the non-tropical zone. Conclusion: Water-energy dynamics is able to predict peaks in species richness under different climate and primary production conditions; hence, WED is better and more general than NPP-MiH. The interaction with precipitation and the length of the growing season, which also reflects primary production, improve the model for several organism groups. Hence, LGS may improve and unify future mechanistic first-principle model of biodiversity. K E Y W O R D S elevational gamma diversity, elevation-temperature, gradient, length of growing season, more individuals hypothesis, net primary production, species richness, water-energy dynamics Editor: Dr. Jenny McGuire
... Many maps of floristic richness have been made in different parts of the world, including the species richness of Switzerland ( Fig. 11.4) by Wohlgemuth (1998), using data taken from the atlas of the Swiss flora by Welten and Sutter (1982), as illustrated in Chap. 4 by Fig. 4.17; the richness of Spermatophytes and Pteridophytes of part of the Białowieza forest (Poland), subdivided into quadrats of 100 m on a side, and of the forest associations ( Fig. 11.5) (Faliński and Mulenko 1995); the species richness of Spain by Lobo et al. (2001), based on 254 UTM grid cells (Fig. 11.6); the richness of vascular plants in California (Fig. 11.7) (Williams et al. 2004) the distribution of vascular plants of Austria by Moser et al. (2005) evaluated in sampling areas of 5 Â 3 arc minutes; and the species richness of South Africa by Thuiller et al. (2006) based on a mesh of 25 Â 25 km. ...
... We used GRASP script (Generalized regression analysis and spatial prediction v.2.5, Lehmann et al. 2002a) to predict spatial distribution diversity. We chose to test this tool as a coral reef fish biodiversity predictor as it has been proved to be a very useful tool in predicting biodiversity distribution in terrestrial ecosystems and in the prediction of benthic coral reef communities' cover (Ferrier et al. 2002;Lehmann et al. 2002b;Garza-Pérez et al. 2004;Moser et al. 2005;Maggini et al. 2006). GRASP uses GAM's models to relate response variables, such as biodiversity, with environmental variables. ...
The assessment of biodiversity in coral reefs requires the application of geographic information systems (GIS), remote sensing and analytical tools in order to make cost-effective spatially explicit predictions of biodiversity over large geographic areas. Here we present a spatially explicit prediction for coral reef fish diversity index, as well as habitat classification according to reef fish diversity index values in Chinchorro Bank Biosphere Reserve, one of the most important plain/atoll type reef systems in the Caribbean. We have used extensive ecological data on depth, fish and habitat characteristics to perform such prediction. Fish species assemblages and different biotic variables of benthic organisms were characterized using visual censuses and video-transects, respectively at 119 sampling stations. The information was integrated in a GIS, along with satellite imagery (LANSDAT 7 ETM?) and a digital bathymetric model. From the recorded data and a hierarchical classification procedure, we obtained nine different classes of habitats. We used a generalized regression analysis and spatial prediction methodology to create predictive maps (GIS layers) of the different reef benthic components, and a second modeling run produced predictive maps of coral reef fish diversity index. Predictive accuracy of the diversity index map presented a good correlation coefficient (r = 0.87), with maximum diversity index values en reefscapes composed of aggregation of coral colonies with seagrass beds. The implementation of our application was successful for the prediction of fish diversity hot spots and surrogate habitats.
... Moreover, area and environmental heterogeneity are usually positively correlated, further confounding attempts to distinguish their respective influences on species richness (see Báldi 2008, and literature cited therein). Thuiller et al. (2006) observed that species richness is best explained by the so-called species-favourableness hypothesis (SFH; Pianka 1966; Mourelle and Ezcurra 1996;Moser et al. 2005), stating that better life conditions promote higher richness. Similar results were also obtained by Richerson and Lum (1980) and Currie (1991). ...
Unravelling patterns of species richness is a fundamental prerequisite to understand evolutionary and ecological dynamics, aiding to set efficient conservation activities. The Species–Area Relationship (SAR) is one of the most general patterns in ecology. Focusing on a Mediterranean area as case study, we investigated SAR and the drivers underlying species richness. We gathered data from all floras published for circumscribed areas in Tuscany after 1970 and then we fitted SAR models based on Arrhenius’ power function for the whole established flora, and for native and alien species separately. SAR residuals, which express the actual species richness free of area-effect, were modelled through spatially explicit Generalised Linear Models (GLMs) using geographic, climatic, and anthropogenic explanatory variables. The most relevant predictor for species richness is the grain of the study area, while environmental drivers play a minor role. Topographic heterogeneity and the amount of precipitation show a positive effect on total floristic richness, while the spatial heterogeneity of annual temperature range shows a negative effect. Native and alien species richness are positively correlated, but different combinations of drivers are involved to explain the patterns of the two different species pools. A fundamental factor driving species richness is the insularity: islands host, proportionally, fewer native species and more alien species than mainland areas. Alien species richness is positively affected by landscape heterogeneity. Finally, we present for the first time a method to draft maps of SAR-predicted floristic richness, integrated by the influence of environmental drivers.
... One could then assume that combining individual species predictions allows the prediction of SR at each modelled unit. From the theoretical perspective, MEM relies on the existence of macro ecological controls on community assembly, whereas S-SDM relies on a Gleason [7] an overlay of species and therefore inherits assumptions typically associated with SDM, such as equilibrium and niche stability [8,9] . For instance, growing season temperature might mostly express the amount of energy that can be shared between species in MEM, but would rather express the limit to the growth period of single species in SDMs [10] . ...
or to predict future patterns of biodiversity under global change. The aim of the present study was the prediction of spatial distribution of plant species richness in the Valdarreh Rangelands, Mazandaran, Iran by Macroecological Modelling (MEM) and Stacked Species Distribution Models (S-SDM). Materials & Methods This experimental study was carried out in the Valdarreh rangelands. In the present study compared the direct, macroecological approach for modeling species richness with the more recent approach of stacking predictions from individual species distributions. Both approaches performed in reproducing observed patterns of species richness along an elevation gradient were evaluated. MEM was implemented by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually, assuming a binomial distribution. Findings The direct MEM approach yielded nearly unbiased predictions centered around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by The S-SDM approaches. This method also cannot provide any information on species identity and, thus community composition. Predicted SR by S-SDM was correlated by a Spearman p of 0.76 with the observed SR. The MEM-predicted SR achieved a Spearman rank correlation of 0.32 with S-SDM. The species richness along the elevational gradient for MEM and S-SDM were 0.21 and 0.82, respectively. Conclusion MEM and S-SDM have complementary strengths and both can be used in combination to obtain better species richness predictions.
... As climate change continues, entire communities begin to migrate. Alpine vegetation contains a high proportion of endemic species and their diversity is subject to spatiotemporal variation of climate changes (Heikkinen and Neuvonen, 1997;Gough et al., 2000;Moser et al., 2005). ...
Vegetation in high altitude areas normally exhibits the strongest response to global warming. We investigated the tundra vegetation on the Changbai Mountains and revealed the similarities and differences between the north and the southwest slopes of the Changbai Mountains in response to global warming. Our results were as follows: 1) The average temperatures in the growing season have increased from 1981 to 2015, the climate tendency rate was 0.38°C/10yr, and there was no obvious change in precipitation observed. 2) The tundra vegetation of the Changbai Mountains has changed significantly over the last 30 years. Specifically, herbaceous plants have invaded into the tundra zone, and the proportion of herbaceous plants was larger than that of shrubs. Shrub tundra was transforming into shrub-grass tundra. 3) The tundra vegetation in the north and southwest slopes of the Changbai Mountains responded differently to global warming. The southwest slope showed a significantly higher degree of invasion from herbaceous plants and exhibited greater vegetation change than the north slope. 4) The species diversity of plant communities on the tundra zone of the north slope changed unimodally with altitude, while that on the tundra zone of the southwest slope decreased monotonously with altitude. Differences in the degree of invasion from herbaceous plants resulted in differences in species diversity patterns between the north and southwest slopes. Differences in local microclimate, plant community successional stage and soil fertility resulted in differential responses of tundra vegetation to global warming.
... As hypothesized, this decline in diversity seems to be related with the existence of a regional gradient generated by the intense summer drought whose effect is diluted from Mediterranean type climate to the sub-Antarctic regions where water stress is practically absent and soil water is available throughout the growing season. Although some authors have suggested that water deficit is not a critical determinant of plant diversity in alpine habitats [1] our results concurs with others in temperate mountains [67][68][69], and particularly in Mediterranean regions [22,23,70]. ...
Mountains are considered excellent natural laboratories for studying the determinants of plant diversity at contrasting spatial scales. To gain insights into how plant diversity is structured at different spatial scales, we surveyed high mountain plant communities in the Chilean Andes where man-driven perturbations are rare. This was done along elevational gradients located at different latitudes taking into account factors that act at fine scales, including abiotic (potential solar radiation and soil quality) and biotic (species interactions) factors, and considering multiple spatial scales. Species richness, inverse of Simpson’s concentration (Dequiv), beta-diversity and plant cover were estimated using the percentage of cover per species recorded in 34 sites in the different regions with contrasted climates. Overall, plant species richness, Dequiv and plant cover were lower in sites located at higher latitudes. We found a unimodal relationship between species richness and elevation and this pattern was constant independently of the regional climatic conditions. Soil quality decreased the beta-diversity among the plots in each massif and increased the richness, the Dequiv and cover. Segregated patterns of species co-occurrence were related to increases in richness, Dequiv and plant cover at finer scales. Our results showed that elevation patterns of alpine plant diversity remained constant along the regions although the mechanisms underlying these diversity patterns may differ among climatic regions. They also suggested that the patterns of plant diversity in alpine ecosystems respond to a series of factors (abiotic and biotic) that act jointly at different spatial scale determining the assemblages of local communities, but their importance can only be assessed using a multi-scale spatial approach.
... Barthlott et al. (2007) also highlight the role of geodiversity as a driving mechanism for habitat variation, which would indicate greater biodiversity in more geodiverse areas. Each element of the physical environment influences the development of organisms, whereby, rock types may provide different kinds of nutrients (e.g., Moser et al. 2005); geomorphological diversity is an important factor controlling the variability of habitats (e.g., Burnett et al. 1998); and both geology and geomorphology influence the soil, which will, in turn provide resources for biological elements (Parks and Mulligan 2010). It is thus expected that an analysis of geodiversity has the potential to be integrated into biodiversity studies, contributing to understanding distribution patterns and the effects of environmental changes. ...
The natural variability of geological, geomorphological, pedological, and hydrological elements can be described and assessed in terms of geodiversity. This geodiversity is intrinsically linked to biodiversity, since the physical environment provides the conditions in which biological elements develop. The use of geodiversity as a tool for environmental studies is of growing importance, describing and highlighting the importance of the physical environment and strengthening the idea of holistic approach of the nature. This work consisted of a qualitative mapping of the geodiversity in Armação dos Búzios municipality, in Rio de Janeiro State, southeastern Brazil. Based on integration of the physical environment elements, geodiversity units were defined, in which the geological substrate, relief forms, and soil types are similar. The hydrological influence was also taken into account in specific units. Subsequently, each geodiversity unit was analyzed in terms of its regional type of vegetation, in order to investigate the correlation between spatial distributions of the physical and biological environments. As a result, a Geodiversity Map of Armação dos Búzios was created, describing the physical environment of the area. The inclusion of data on vegetation types showed direct correspondence of the Geodiversity Map and the biological environment, since each geodiversity unit is occupied by specific vegetation types. This result shows that the use of geodiversity as a tool to understand vegetation distribution patterns is valid and should be explored further within the contexts of land management and nature conservation. It is expected that this product becomes a tool for territorial management and an incentive for the development of furthermore research focused on holistic approaches to nature.
... This use of rainfall and minimum PET is probably because the model was developed in South Africa, where snowfall is very rare (rainfall = precipitation), and minimum PET may express a low probability of water deficiency. Here, we evaluate a more general WED model for twelve different types of organisms that include not only wood plants in a region where snowfall is common and where minimum PET will be a proxy for frozen water and not moist conditions (Moser et al., 2005). Therefore, we use precipitation and annual PET, expressed in mm per year as suggested by the Holdrige formula (cf. ...
Aims
Phylogenetic niche conservatism ( PNC ) predicts that closely related species will have similar distributions along major environmental gradients, e.g. temperature. We test this theory by comparing the central tendencies of temperature for selected woody genera, and investigating whether these genera have a similar rank order (sequence) across continents and hemispheres. A strong correlation may indicate niche conservatism, as inherited temperature tolerance would best explain a positive correlation.
Location
Peru (Andes) and Nepal (Himalaya).
Methods
Elevation and temperature ranges for all species belonging to eight disjunct genera of woody plants were compiled. Central tendencies of congeneric species along the temperature gradient were established by means of reciprocal averaging and weighted average temperature. We correlated the rank order of genera from the Himalaya and Andes, and tested if the order in the Himalaya could predict the order in the Andes, using permutation procedure.
Results
Most genera exhibit a bell‐shaped or curvilinear pattern with the maximum number of congeneric species in the centre of the temperature range, but some curvilinear responses and monotonic increases are found in Andes. The order of generic optima along the temperature gradient in each region is highly correlated (ρ > 0.81), as well as the size of the temperature range and minimum temperature limit (ρ > 0.90).
Conclusion
The analyses verify the conjecture that the maximum number of congeneric species is found towards the centre of the temperature range of the genus. This may be caused by newly evolving species not dispersing very far from their ancestors and inherent temperature tolerances. Inherent temperature tolerance and covariates such as primary production and soil conditions are the main factors that may explain consistency of the rank order of disjunct genera along temperature gradients between continents and hemispheres. Hence temperature tolerances within a clade are conserved over time and space.
Abstract Few studies have evaluated how climate is mechanistically related to species richness in mountain environments. We used path analysis to evaluate predictions of several mechanistic hypotheses based on their hypothesized mechanism relating climate with richness of darkling beetles (Coleoptera: Tenebrionidae). We modeled the influence of spatial covariation on climatic variables and tenebrionid richness. Results showed that richness peaks at mid elevations, chiefly influenced by precipitation and temperature, both directly and indirectly through geographic range sizes. The best fitting model explains 84% of the variance of tenebrionid richness. We suggest this pattern is induced by a water-energy balance along the altitudinal gradient. At low elevations, energy availability is high but water deficit may limit species richness; in contrast, at high elevations water availability is high, but energy deficit may limit species richness. These results suggest high susceptibility of the study region to future global climate change.
Trophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. A crucial step toward the understanding of those metanetworks is to build appropriate tools to handle and represent them. We present here the R package metanetwork, which will ease the exploration and the analysis of trophic metanetwork datasets that are increasingly available. Our main methodological advance consists in suitable layout algorithm for trophic networks, which is based on trophic levels and dimension reduction of a graph diffusion kernel. In particular, it highlights relevant features of trophic networks (trophic levels, energetic channels). In addition, we developed graphical tools to handle, compare and aggregate those networks. Static and dynamic visualisation functions have been developed to represent large networks. We apply our package workflow to several trophic network data sets.
According to Article 17 of Habitats Directive Member States have to draw up reports to the European Commission every six years on the results of their surveillance of the conservation status of habitat types and species. On the basis of the Member State reports the European Commission prepares a com-posite report. Since the Commission has delivered a reporting format and a common methodology for the Article 17 reports in 2005 Member States have delivered standardized reports for the period 2000–2006 (report 2007), 2007–2012 (report 2013) and 2013–2018 (report 2019).
The Austrian Federal Provinces in fulfilling their competency for nature conservation have delivered the Article 17 reports in 2007, 2013 and 2019 after they have commissioned the Environment Agency Austria (EAA) to prepare these reports.
The contract between the Austrian Federal Provinces and the EAA for drafting the Article 17 report 2019 also included the monitoring of 31 habitat types and 38 species. These data together with other already existing monitoring data (e. g. from the Austrian Forest Inventory) and complementary data (e. g. bio-tope mappings, inventories, project reports, publications, extracts from data bases) built a basis of 235.756 records for species and 361.137 for habitat types for the period 1995–2018 which are stored and managed in the so-called Article 17-occurrence database.
Building on the occurrence database distribution maps have been elaborated, distinguishing between historical and actual occurrences. The latter are in principle records stemming from the reporting period 2013–2018. If distribution data from this period are not sufficient for displaying the range we have ex-tended the time span by previous reporting periods. In this case we have dis-tinguished actual records in “recent” (actual reporting period 2013–2018) and “subrecent” records (previous reporting period(s)). The distribution maps dis-playing only the actual records in 10x10 km grids are a central product of the Article 17 report and have been submitted to the European Commission.
On the basis of the more detailed distribution maps and occurrence informations the parameters range, area, structure and functions and future pro-spects for habitat types and range, population, habitat for the species and future prospects for species have been assessed. The rational for the assess-ment is the analysis of the actual status and the trends of the parameters as well as favourable reference values for the parameters range, area and population.
The Austrian Article 17 report 2019 was delivered for 71 habitat types with 63 assessments in the alpine and 54 assessments in the continental region and for 211 species with 171 assessments in the alpine and 174 in the continental re-gion.
18 % of habitat type assessments and 14 % of species assessments are favourable for Austria but 44 % for habitat types and 34 % for species have been assessed as unfavourable bad.
For habitat types as well as for species 3 % of the assessments are unknown due to a lack of data.
Related to the biogeographical regions of Austria there are significant better assessments in the alpine region compared to the continental region. This is not only true for the analysis of the number of assessments but also for the assessments weighted by the area (habitat types) or the population size in 1x1 km raster grids (species).
Habitat types have 27 % of favourable assessments but 67 % of the related areas are favourable in the alpine region. In the continental region 7 % of assessments are favourable and only 0,05 % of the related areas. The better situ-ation in the alpine region is also true for species but the relation of the number of assessments to the weighted assessments is different in the continental region: 12 % of the assessments are favourable but 26 % of the population in the unit 1x1 km-grids.
Study of NDVI for dark coniferous, light coniferous, deciduous, and mixed forests and climate features in Volga basin has shown that most strong links between NDVI and climate are observed for dark coniferous forests. The main climate features for all forests were continentality, variability of temperature estimated as its standard deviation, winter temperature, sum of negative temperatures, Kira’s coldness index, and snow index. Potential evapotranspiration in October was also important — in November, average temperature changes from positive to negative in the region. The relation of NDVI to average annual temperature was relatively weak, and weaker — with precipitation. The latter is related to that water deficit is not a limiting factor for forests in the region. In general, summer NDVI for all forests was strongly related to winter, rather than summer temperatures. This was better expressed for dark coniferous forests. This may be explained by both winter frosts, and effects of so-called winter drought. The latter is expressed in that at the end of winter when plant roots are still frozen but transpiration
is already essential, above-ground parts of plants loose water, and this may be expressed later, during growing season. Maximal values of water deficit (defined as the difference between potential and actual evaportanspiration) were found when forests do not grow: 251 mm/year for dark coniferous forest, 254 for mixed, 282 for light coniferous, 326 for.
The research study was undertaken with 3 major objectives. Primarily to screen the fern flora along with their spatial distribution and to conduct an index based diversity assessment of the fern flora in the Kudremukh Nation Park (KNP) of Western Ghats. Secondly to identify the edaphic factors responsible for fern distribution, and most importantly to contribute to the knowledge of DNA barcodes of the pteridophytes in the Indian context. The study revealed a highly diverse but uneven distribution of 46 different ferns species belonging to 19 different families in the region. The reason for uneven diversity and richness of the fern flora throughout the region was found to be more affected by edaphic factors than environmental or structural habitat factors as the soil quality indices (SQI) suggested that the diversity and richness in fern flora increased with increase in overall soil quality. Although the PCA analysis revealed that the availability of soil components such as percentage moisture content of the soil and soil nutrients such as K and P played a crucial role along with the limiting concentration effects of Cu in influencing the richness and diversity of fern flora in KNP. DNA barcoding was successfully accomplished for 87.5% of the screened fern flora in the KNP with rbcL loci while due to low PCR amplification rates MatK loci was successful for only 41.6% of the screened fern flora and hence deemed inappropriate for barcoding studies in ferns. Utilizing the rbcL nucleotide and amino acid sequence polymorphism a new variant of P. vittata i.e. variety ‘Nano’ was also reported.
A single quantitative index d has been introduced for the spectrum of seven life forms (LFs) characterizing the proportions of their species richness (SR) in the Middle Volga region at 25 sites 100 km² in size each. It is established that d grows with moisture provision. All significant relationships between the SR of different LFs are positive. However, a different sign is identified between the fractions of the number of species of each LF of the total number of species or the relative species richness (RSR). For example, a close negative relationship was found between the RSR of LFs dominating in the region, hemicryptophytes and annual herbs (therophytes). Using the regression models, the specificity of links for the SR and RSR of seven LFs with climate and topography is shown. It was established that precipitation is more important for some LFs in the region and temperature is more important for others. The links are closer when taking into account the slope insolation, but the signs of links between it and the SR of different LFs may be different. According to regression models, SR and RSR maps of hemicryptophytes and therophytes are calculated. The maps show the separation of these LFs in space: the location of hemicryptotes to flat water divide areas and therophytes to the northeastern slopes. In the region under study, the main environmental factors differentiating these LFs in space are the energy of solar radiation and the precipitation of March and winter. This separation of LFs po-tentially leads to reduced competition between them.
This study deals with the relationship between the species richness of vascular plants in 10 × 10-km plots and climate indices in the Middle Volga Region. The most significant indices have been revealed: precipitation and temperature in March, temperature in October, and winter precipitation, with their combined effect accounting for 74% of variation in species richness. In view of relatively low climate gradients, a special function of total precipitation in March has been used in analysis, which describes the nonlinear dependence of the richness of vascular plants on the amount of March precipitation in the form of a peak. An ecological interpretation of these relationships is given and a species richness map is constructed. It is hypothesized that minor variations of intra-annual temperature and precipitation indices in the area with low climate gradients may become critical factors for the spatial change in the number of vascular plant species.
The geographical patterns of species richness and underlying mechanisms are among the central issues of ecology. The Himalaya, a global biodiversity hotspot, lacks spatially explicit representation of plant richness patterns and predictor environmental covariates. The rugged Himalayan terrain limits large-scale field surveys, we, therefore, disentangle the role of remotely sensed environmental proxies for characterization of Plant Functional Types (PFTs) and prediction of plant richness in an alpine area in Western Himalaya. Alpine plant richness was recorded in cluster plots (10 random quadrants of 1 m² in approximately 1-ha area) across 97 sites in Pithoragarh district in part of the Western Himalaya (India). The dominant PFTs were mapped based on support vector machine classification of Landsat 8 image. The satellite-derived climate, landscape, and topographic variables were correlated to plant richness using generalized linear model (GLM) with poisson distribution to unravel species richness-environment linkages in the study area. The dominant PFTs mapped were herbaceous meadow, Danthonia grassland, Kobresia sedge meadow, moist scrub, and dry scrub. The GLM based plant richness model explained 70% variation in alpine plant richness. The environmental factors such as vegetation vigor, elevation, landscape diversity and moisture were observed to influence alpine plant richness of the study area. The study presents a valuable baseline spatial database for judicious management of alpine plant resources and climate change studies.
Field data collection can be expensive, time consuming, and difficult; insightful research requires statistical analyses supported by sufficient data. Pilot studies and power analysis provide guidance on sampling design but can be challenging to perform, as ecologists increasingly collect multiple types of data over different scales. Despite a growing simulation literature, it remains unclear how to appropriately design data collection for many complex projects. Approaches that seek to achieve realism in decision‐making contexts, such as management strategy evaluation and virtual ecologist simulations, can help. For a relatively complex analysis, we develop and demonstrate a flexible simulation approach that informs what data are needed and how long those data will take to collect, under realistic fieldwork constraints. We simulated data collection and analysis under different constraint scenarios that varied in deterministic (field trip length, travel, and measurement times) and stochastic (species detection and occupancy rates and inclement weather) features. In our case study, we fit plant height data to a multispecies, three‐parameter, nonlinear growth model. We tested how the simulated data sets, based on the varying constraint scenarios, affected the model fit (parameter bias, uncertainty, and capture rate). Species prevalence in the field exerted a stronger influence on the data sets and downstream model performance than deterministic aspects such as travel times. When species detection and occupancy were not considered, the field time needed to collect an adequate data set was underestimated by 40%. Simulations can assist in refining fieldwork design, estimating field costs, and incorporating uncertainties into project planning. We argue that combining data collection, analysis, and decision‐making processes in a flexible virtual setting can help address many of the decisions that field ecologists face when designing field‐based research.
We use regional distribution patterns and frequencies of the Styrian vascular plants to describe the floristic differences and peculiarities of the Styrian landscapes. The largest contrast in terms of flora stretches along the border between the alpine areas of Styria and the predominantly colline Styrian Foreland. To a certain extent, the latter also includes the colline altitudinal belt of the inner alpine valleys and basins. A second clear line of contrast runs between the crystalline Central Alps with predominantly siliceous rocks, and the mountainous landscapes dominated by carbonates, such as the Northern Calcareous Alps, parts of the Grauwacke zone and the Grazer Bergland. Further, less significant differences arise between some subunits within these landscapes. In comparison to other parts of Austria, the Ennstal, the upper Murtal, the Grazer Bergland and the Eisenerzer and Mürzsteg Alps are particularly species rich. They also host many species with a Styrian distribution center within Austria.
Understanding the factors affecting the species richness of alien and native plant is a key issue for predicting the spread of alien species and protecting rare and endangered native species in nature reserves. To investigate the factors affecting alien and native species richness in temperate nature reserves of China, we used a database of 25 nature reserves in Shandong Province of northern China, and studied the relationship of alien and native plant species richness with climatic and anthropogenic factors, as well as area and elevation range. We found that most of the nature reserves in Shandong Province have been invaded by alien plant species. The distribution of alien and native species responds to the same climatic factors, and temperature and precipitation exert strong effects on both groups. Alien and native plant species richness are positively correlated. Human activity is more effective for explaining richness of alien than for native species. Simultaneously, human activity has stronger effects on alien herbaceous than on alien woody plants. Our results suggest that native species richness is mainly explained by climatic factors, whereas alien species richness is mainly explained by climatic factors and human activity together.
There are 14 main mountain regions in Europe ranging from the Mediterranean to the Arctic between 35–80°N (Chap. 1). The high mountains across Europe differ in extent and altitude, glaciation history, geology, and ecological conditions (Chap. 1), and their plant species composition varies considerably (Chaps. 3.1–3.10).
A more general biogeographic theory of island species number is produced by replacing area with a more direct measure of available energy in the models of MacArthur and Wilson and Preston. This theory, species-energy theory, applies to islands that differ in their per-unit-area productivity due to differences in physical environment, such as climate. Examination of data on species number of angiosperms and of land and freshwater birds on islands worldwide, demonstrates that species-energy theory can explain 70-80% of the variation in species number, and further suggests the existence of regular geographic trends in resource utilization or species-abundance patterns. The concepts embodied in species- energy theory can in principle be used to develop predictions of species' abundances and probabilities of occurrence on an island. -from Author
Much of the variance in species richness of terrestrial organisms has been related to levels of available energy (the species richness-energy hypothesis). In contrast, the global patterns of coral diversity have been hypothesized to depend mainly on disturbance and historical factors. In this study, we test several general diversity hypotheses as they relate to hermatypic corals by examining the relationships between coral generic richness at 130 sites worldwide and descriptors of the environment that would be suggested by the hypotheses. The best environmental predictors of diversity are mean annual ocean temperature and an estimate of regional coral biomass, which suggests that available energy limits regional generic richness. In contrast, we found little evidence supporting other ecological hypotheses, including the hypotheses that disturbance or environmental stability is an important control of diversity. We also investigated historical hypotheses proposed to explain coral distributions. We found a relationship between coral richness and up-current island density that is consistent with vicariance models of speciation and theories of coral dispersal. Using multiple regression, 71% of the variation in coral generic richness could be statistically explained using a combination of variables representing both ecological and historical factors. Similar patterns exist for both coral species and reef fishes.
Climatic fluctuations during Quaternary glaciations had a significant influence on the distribution of taxa and on their intraspecific genetic structure. In this paper, we test hypotheses on Pleistocene refugia for mountain plants in the eastern part of the European Alps derived from palaeoenvironmental and geological results, with new data on distributional patterns of 288 vascular plant endemics and molecular phylogeographies of selected species. High numbers of endemics are found in calcareous regions at the southern and the eastern border of the Eastern Alps, which remained unglaciated during the Pleistocene. The distribution of local endemic taxa in general, and of silicicolous taxa in particular, shows a clear relationship with hypothetical glacial refugia in the southern, southeastern, easternmost, and northeastern Alps. Molecular phylogeographic data from several silicicolous alpine species (Androsace alpina, Androsace wulfeniana, Eritrichium nanum, Phyteuma globulariifolium, Ranunculus glacialis, Saponaria pumila) are not completely congruent. However, all genetically defined population groups are in congruence with hypothetical refugia. In general, results from distributions of endemic taxa and data from intraspecific phylogeography are compatible with previously hypothesized refugia suggesting that refugial situations have shaped the current patterns. The combination of patterns of endemism with molecular phylogeographic data provides an efficacious approach to reveal glacial refugia in vascular plants.
In this paper a multivariate linear regression model is proposed for predicting and mapping regional species richness in areas below the timberline according to environmental variables. The data used in setting up the model were derived from a floristic inventory. Using a stepwise regression technique, five environmental variables were found to explain 48.9% of the variability in the total number of plant species: namely temperature range, proximity to a big river or lake, threshold of minimum annual precipitation, amount of calcareous rock outcrops and number of soil types. A considerable part of the unexplained variability is thought to have been influenced by variations in the quality of the botanical inventory. These results show the importance of systematic floristic sampling in addition to conventional inventories when using floristic data as a basis in nature conservation. Nevertheless it is still possible to interpret the resulting diversity patterns ecologically. Regional species richness in Switzerland appears to be a function of: (i) environmental heterogeneity; (ii) threshold values of minimum precipitation; and (iii) presence of calcareous rock outcrops. According to similar studies, environmental heterogeneity was the strongest determinant of total species richness. In contrast to some studies, high productivity decreased the number of species. Furthermore, the implications of this work for climate change scenarios are discussed.
The richness pattern of native vascular plants in North America (north of Mexico) was studied at the generic level. North America was divided into thirteen geographical regions, which were latitudinally grouped into four horizontal zones (northern, north-middle, south-middle, and southern zones); and longitudinally grouped into three vertical zones (eastern, central, and western zones). The native vascular flora of North America consisted of 1904 genera in 235 families and eighty-three orders. Along the latitudinal gradient, generic richness (in terms of the number of genera) showed a striking increase with decreasing latitude. The southern zone had more than four times as many genera as did the northern zone (with a difference of 1436 genera). 93.3% of genera in the northern zone also occurred in the southern zone. Along the longitudinal gradient, the central zone had the highest generic richness and the eastern zone had the lowest, but the difference in generic richness between the two zones was only sixty-one genera. The western and eastern zones shared 60% or more of their genera. Generic richness of vascular plants in North America was highly correlated (r=0.965) to available environmental energy (expressed by annual potential evapotranspiration).
This paper presents models based on empirical data which can be used to predict the patterns of species richness of vascular
plants at the poorly explored mesoscale. Using generalized linear modelling, multiple regression models of species richness
in the Kevo Nature Reserve, North Finland, are built with a training set of 257 grid squares and 33 environmental variables.
We validated the accuracy of the derived models with an independent test set of 100 grid squares. Two different modelling
approaches are used: one where species richness is treated straightforwardly as the response variable, and another where it
is tentatively stratified into two groups according to taxon types, i.e. alpine taxa versus wide-spread and silvine (forest)
taxa. However, the latter approach only marginally improved the accuracy of the predictions of total number of species. Linear
altitudinal variables were among the best predictors of vascular plant richness at the mesoscale. As variables involving altitude
are crude surrogates for energy-related factors, the results support the available energy hypothesis and advocate its significance
in richness-environment relationships. Other important predictors of species richness included length of rivers and brooks,
abundance of cliff walls, occurrences of steep-sided gorges and valleys, and relative abundance of gabbro in bedrock. However,
the accuracy of the predictions in the derived models is relatively modest. This points towards the necessity of field work
as a final guarantee to identify local hotspots of vascular plant species in a subarctic landscape.
The extent to which nutrient limitation affects species composition, abundance, and productivity of the alpine tundra is an ongoing area of ecological inquiry. At Niwot Ridge in the Front Range of Colorado, plant species richness and foliage production were studied with respect to N and P additions in three alpine communities varying in snowpack depth and duration. These effects were also measured in conjunction with a snowpack enhancement experiment. Measurements of plant responses were made 4 yr following the initiation of the manipulations. The addition of either N or P enhanced plant foliage productivity (P = 0.05 and P = 0.03, respectively). Nitrogen additions had a negative effect on the species richness censused in 1-m² plots (P < 0.001), while P additions had no effect on species richness (P > 0.60). Snowpack did not affect foliage productivity (P = 0.20), but species richness was negatively affected (P < 0.001). Snowpack also appeared to mediate species-specific responses to N and P additions. In the alpine, the relationship between species diversity and plant productivity is mediated by species-specific traits. After 4 yr, the increased production by plant species sensitive to P additions did not reduce species richness. This suggests that production-induced competitive exclusion is not a generalization that can be used to explain the decline in species richness. Moreover, the reduction in species richness due to N addition occurred across all of the tundra communities studied here. These communities differ with respect to the strength of other potential limiting resources such as light (self-shading) or water. Thus, this negative response is best explained by changes in soil chemistry that resulted directly or indirectly from N additions.
Warum kartieren wir die Schweizer Flora? Weil es höchste Zeit ist zu inventarisieren in einer Zeit, wo der Mensch Umwelt und Natur bedenkenlos in Anspruch nimmt, wo wir doch so vieles noch nicht wissen, unsere Landschaften sehr ungleich kennen, wo unsere bisherige Information zu überaltern droht, wo neue systematische Erkenntnisse neue Nachforschungen verlangen. Pourquoi cartographier la flore suisse? Il est urgent de l’entreprendre puisque l’homme agresse notre environnement et la nature sans aucune retenue, qu’il est tant de choses que nous ignorons, que les connaissances très inégales que nous avons sur notre pays menacent de dater, et que les progrès de la systématique exigent de nouvelles recherches. Perchè un nuovo censimento della flora svizzera? La risposta potrebbe essere: perchè in un’epoca, in cuil’uomo si è appropriate dell’ambiente e della natura in modo sconsiderato, quando si conosce così poco del nostro paesaggio naturale e le informazioni disponibili sono subito sorpassate dagli eventi, quando le cognizioni sistematiche acquisite impongono nuove ricerche, non è più possibile attendere oltre con un inventario del genere.
The extent to which nutrient limitation affects species composition, abundance, and productivity of the alpine tundra is an ongoing area of ecological inquiry. At Niwot Ridge in the Front Range of Colorado, plant species richness and foliage production were studied with respect to N and P additions in three alpine communities varying in snowpack depth and duration. These effects were also measured in conjunction with a snowpack enhancement experiment. Measurements of plant responses were made 4 yr following the initiation of the manipulations. The addition of either N or P enhanced plant foliage productivity (P = 0.05 and P = 0.03, respectively). Nitrogen additions had a negative effect on the species richness censused in 1-m2 plots (P < 0.001), while P additions had no effect on species richness (P > 0.60). Snowpack did not affect foliage productivity (P = 0.20), but species richness was negatively affected (P < 0.001). Snowpack also appeared to mediate species-specific responses to N and P additions. In the alpine, the relationship between species diversity and plant productivity is mediated by species-specific traits. After 4 yr, the increased production by plant species sensitive to P additions did not reduce species richness. This suggests that production-induced competitive exclusion is not a generalization that can be used to explain the decline in species richness. Moreover, the reduction in species richness due to N addition occurred across all of the tundra communities studied here. These communities differ with respect to the strength of other potential limiting resources such as light (self-shading) or water. Thus, this negative response is best explained by changes in soil chemistry that resulted directly or indirectly from N additions.
The patterns of species richness in the south-western Cape Province, South Africa, at a quarter-degree scale are documented for several plant taxa typical of the Cape flora, i.e. Restionaceae, Ericaceae, Proteaceae, Pentaschistis (Nees) Stapf (Poaceae) and Aspalathus L. (Fabaceae). The patterns of species richness are very similar for all taxa investigated. These patterns are correlated to a range of environmental factors: precipitation, altitude, substratum and vegetation type. It is shown that total precipitation is the best predictor for the patterns of species richness, but that this is to some extent correlated with the range of precipitation and the altitude range. To test for the effect of individual factors, selected samples in which One environment factor varied, were compared. This clearly showed that rainfalls is the best predictor. The number of substrate types, curiously, is not strongly correlated to the patterns of species richness.
The mapping scheme for the Flora of Central Europe forms the basis for the preparation of a distributional atlas. This atlas should contain the maps of all Central European vascular plants (Pteridophyta and Spermatophyta) based on grid units of 10′ long. × 6′ lat. The maps will cover Austria, western and central Czechoslovakia, Germany (G.D.R. and G.F.R.), Switzerland, northern Italy and northwestern Yugoslavia (north of 45° N and west of 19° 10′ E), together with some neighbouring territories.
Work on the mapping scheme was started a few years ago in most Central European countries with the help of numerous voluntary collaborators, many local working groups, and several regional centers. The current activity is characterized by international cooperation and the accumulation of data prepared for modern machine handling. A “Check list of the vascular plants of Central Europe” (Ehrendorfer & al., cf. fig. 1) and a grid system based on geographical longitudes and latidudes supply the numerically coded taxonomical and geographical reference units. The system of data handling is demonstrated in fig. 2: Records from field work as well as herbarium and literature sources are first incorporated into printed field lists (fig. 3), punch cards with text (fig. 4) or data forms (fig. 5). Records are then transferred to punched cards or magnetic tape, partly through mark‐sensing coding‐forms and mark‐sensing reader. Finally, lists of records as well as distributional maps will be available by automatic printing from tabulators and/or data plotters.
10 sample maps demonstrate the design and information value of the distributional maps for the atlas; at the same time they illustrate the considerable deficiencies in our present knowledge of actual distribution in higher plants. Everybody interested in Central European floristics and geobotany is therefore invited to participate in regional or national organizations of the mapping scheme in order to realize the project of a distributional atlas of the Central European flora.
Some theories and experimental studies suggest that areas of low plant species richness may be invaded more easily than areas of high plant species richness. We gathered nested-scale vegetation data on plant species richness, foliar cover, and frequency from 200 1-m2 subplots (20 1000-m2 modified-Whittaker plots) in the Colorado Rockies (USA), and 160 1-m2 subplots (16 1000-m2 plots) in the Central Grasslands in Colorado, Wyoming, South Dakota, and Minnesota (USA) to test the generality of this paradigm. At the 1-m2 scale, the paradigm was supported in four prairie types in the Central Grasslands, where exotic species richness declined with increasing plant species richness and cover. At the 1-m2 scale, five forest and meadow vegetation types in the Colorado Rockies contradicted the paradigm; exotic species richness increased with native-plant species richness and foliar cover. At the 1000-m2 plot scale (among vegetation types), 83% of the variance in exotic species richness in the Central Grasslands was explained by the total percentage of nitrogen in the soil and the cover of native plant species. In the Colorado Rockies, 69% of the variance in exotic species richness in 1000-m2 plots was explained by the number of native plant species and the total percentage of soil carbon. At landscape and biome scales, exotic species primarily invaded areas of high species richness in the four Central Grasslands sites and in the five Colorado Rockies vegetation types. For the nine vegetation types in both biomes, exotic species cover was positively correlated with mean foliar cover, mean soil percentage N, and the total number of exotic species. These patterns of invasibility depend on spatial scale, biome and vegetation type, spatial autocorrelation effects, availability of resources, and species-specific responses to grazing and other disturbances. We conclude that: (1) sites high in herbaceous foliar cover and soil fertility, and hot spots of plant diversity (and biodiversity), are invasible in many landscapes; and (2) this pattern may be more closely related to the degree resources are available in native plant communities, independent of species richness. Exotic plant invasions in rare habitats and distinctive plant communities pose a significant challenge to land managers and conservation biologists.
Total richness was best modelled by number of communities, high elevation species by area, northern species by area, endemic species by number of communities and rare species by maximum elevation. Elevation, number of peaks and area were all relatively important predictors, while isolation was unimportant. In multiple regression models, linear formulations were almost always the strongest. For total species richness, the best multiple regression model was linear and the most important predictor was the number of peaks. Rare species richness increased faster with area or elevation than any other richness category (slope coefficients for log (rare species) - log (area) models were 0.30 for the whole data set and 0.49 for the eight largest areas). Distance between mountains almost always had a positive, though unsually minor, effect on species richness. Distance between mountain areas is probably a poor measure of ecological isolation and historic extinctions have shaped species-area relations. -from Authors
This paper is an attempt, using statistical modelling techniques, to understand the patterns of vascular plant species richness at the poorly studied meso-scale within a relatively unexplored subarctic zone. Species richness is related to floristic-environmental composite variables, using occurrence data of vascular plants and environmental and spatial predictor variables in 362 1 km2 grid squares in the Kevo Nature Reserve. Species richness is modelled in two different way. First, by detecting the major floristic-environmental gradients with the ordination procedure of canonical correspondence analysis, and subsequently relating these ordination axes to species richness by generalized linear modelling. Second, species richness is directly related to the composite environmental factors of explanatory variables, using partial least squares regression. The most important explanatory variables, as suggested by both approaches, are relatively similar, and largely reflect the influence of altitude or altitudinally related variables in the models. The most prominent floristic gradient in the data runs from alpine habitats to river valleys, and this gradient is the main source of variation in species richness. Some local environmental variables are also relatively important predictors; the grid squares rich in vascular plant taxa are mainly located in the lowlands of the reserve and are characterized by rivers and brooks, as well as by abundant cliff walls. The two statistical models account for approximately the same amount of variation in the species richness, with more than half of the variation unexplained. Potential reasons for the relatively modest fit are discussed, and the results are compared to the characteristics of the diversity-environment relationships at both broader- and finer-scales.
With the rise of new powerful statistical techniques and GIS tools, the development of predictive habitat distribution models has rapidly increased in ecology. Such models are static and probabilistic in nature, since they statistically relate the geographical distribution of species or communities to their present environment. A wide array of models has been developed to cover aspects as diverse as biogeography, conservation biology, climate change research, and habitat or species management. In this paper, we present a review of predictive habitat distribution modeling. The variety of statistical techniques used is growing. Ordinary multiple regression and its generalized form (GLM) are very popular and are often used for modeling species distributions. Other methods include neural networks, ordination and classification methods, Bayesian models, locally weighted approaches (e.g. GAM), environmental envelopes or even combinations of these models. The selection of an appropriate method should not depend solely on statistical considerations. Some models are better suited to reflect theoretical findings on the shape and nature of the species’ response (or realized niche). Conceptual considerations include e.g. the trade-off between optimizing accuracy versus optimizing generality. In the field of static distribution modeling, the latter is mostly related to selecting appropriate predictor variables and to designing an appropriate procedure for model selection. New methods, including threshold-independent measures (e.g. receiver operating characteristic (ROC)-plots) and resampling techniques (e.g. bootstrap, cross-validation) have been introduced in ecology for testing the accuracy of predictive models. The choice of an evaluation measure should be driven primarily by the goals of the study. This may possibly lead to the attribution of different weights to the various types of prediction errors (e.g. omission, commission or confusion). Testing the model in a wider range of situations (in space and time) will permit one to define the range of applications for which the model predictions are suitable. In turn, the qualification of the model depends primarily on the goals of the study that define the qualification criteria and on the usability of the model, rather than on statistics alone.
. Generalized additive models (GAMs) are a non-parametric extension of generalized linear models (GLMs). They are introduced here as an exploratory tool in the analysis of species distributions with respect to climate. An important result is that the long-debated question of whether a response curve, in one dimension, is actually symmetric and bell-shaped or not, can be tested using GAMs. GAMs and GLMs are discussed and are illustrated by three examples using binary data. A grey-scale plot of one of the fits is constructed to indicate which areas on a map seem climatically suitable for that species. This is useful for species introductions. Further applications are mentioned.
Predictable geographic patterns in the distribution of species richness, especially the latitudinal gradient, are intriguing because they suggest that if we knew what the controlling factors were we could predict species richness where empirical data is lacking (e.g. tropics). Based on analyses of the macro-scale distribution of woody plant species richness in Southern Africa, one controlling factor appears to be climate-based water-energy dynamics. Using the regression models of climate's relationship to species richness in Southern Africa, I was able to describe an Interim General Model (IGM) and to predict first-order macro-scale geographic variations in woody plant species richness for the continent of Africa, as well as elsewhere in the world—exemplified using South America, the United States and China.
In all cases, the geographic pattern of variation in species richness is in accord with geographic variations in vegetation (visual comparison with vegetation maps) and net primary productivity. What validation was possible (Africa and U.S.A.) suggests that the IGM provides ‘reasonable’ estimates for actual woody plant species richness where species richness is in relative equilibrium with climate. Areas of over- or under-prediction support the contention of earlier workers that edaphic, topographic, historical, and dispersal factors need to be considered in a more complete explanation for spatio-temporal variations in species richness.
In addition to providing a means for systematically estimating woody plant species richness where present-day empirical data is lacking, the Interim General Model may prove useful for modelling the effects of climate change (past/future) on species richness (and, by association, the vegetation).
The six major hypotheses of the control of species diversity are restated, examined, and some possible tests suggested. Although several of these mechanisms could be operating simultaneously, it is instructive to consider them separately, as this can serve to clarify our thinking, as well as assist in the choice of the best test situations for future examination. 65 references.
Recent studies at the macro-scale have demonstrated that geographic gradients in the richness of plants, in particular of woody plants such as trees and shrubs, can be viewed as by-products of water-energy dynamics. According to this view, they are climatic rather than latitudinal/longitudinal gradients, relating to coincident and predictable variations in planetary surface-atmosphere thermal dynamics and consequent patterns in biological activity. Previous analyses have shown that a two-variable model capturing the dynamic relationship between energy (heat/light) and water (rainfall) accounts for most of the variation in woody plant richness across southern Africa at species, genus, and family levels. Here we move towards a more complete explanation, while demonstrating how geographic analysis of residuals can be used to identify the type and sequence of additional variables for inclusion, either at the same or at more discrete scales of analysis. Residual geographic variation in richness from the two-variable model displays a geographic pattern unrelated to longitude and latitude. Regional clusters of under- and over-prediction point to macro-scale variation in topographic relief as a significant factor. When topographic relief is added as a third variable, the explanatory power (R2) increases by 7 to 12%, and the subsequent pattern of variation in residuals becomes even more unpredictable. What clustering remains points to other macro-, and meso- or micro-scale variables that need to be considered. Such a top-down, trans-scalar approach permits systematic and objective development of more complete explanations, while the three-variable macro-scale model developed herein is the basis for a powerful research tool for ecologists, biogeographers, conservationists and bio-climatologists alike.
Hypotheses that attempt to explain latitudinal gradients in species diversity are reviewed. Some hypotheses are circular, i.e. they are based on the assumption that some taxa have greater diversity in the tropics. These include explanations assuming different degrees of competition, mutualism, predation, epiphyte load, epidemics, biotic spatial heterogeneity, host diversity, population size, niche width, population growth rate, environmental harshness, and patchiness at different latitudes. Other explanations are not supported by sufficient evidence, i.e. there is no consistent correlation between species diversity and environmental stability, environmental predictability, productivity, abiotic rarefaction, physical heterogeneity, latitudinal decrease in the angle of the sun above the horizon, area, aridity, seasonality, number of habitats, and latitudinal ranges. The ecological and evolutionary time hypotheses, as usually understood, also cannot explain the gradients, nor does the temperature dependence of chemical reactions permit predictions on species richness. Only differences in solar energy are consistently correlated with diversity gradients along latitude, altitude and perhaps depth. It is concluded that greater species diversity is due to greater "effective" evolutionary time (evolutionary speed) in the tropics, probably as the result of shorter generation times, faster mutation rates, and faster selection at greater temperatures. There is an urgent need for experimental studies of temperature effects on speed of selection.
We related plant species richness data from 1260 sites in forty physiographically homogeneous units ranging in size from 1104 km<sup>2</sup> to 69,196 km<sup>2</sup> in the southern and western half of southern Africa to mean potential evapotranspiration (PET) (an index of energy availability), mean annual precipitation (MAP) and AREA There was a significant negative relationship between PET and plant species richness and a weaker but significant positive relationship between MAP and plant richness On its own, AREA was not significantly correlated with richness. A multiple regression model which incorporated all three variables in the set of significant regressors accounted for 57% of the variance in regional plant species richness. We suggest that our data form part of a more general unimodal (hump-backed) pattern between richness and environmental controls and that at high PET values plant richness may be reduced
The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation. A generalization of the analysis of variance is given for these models using log-likelihoods. These generalized linear models are illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables) and gamma (variance components). The implications of the approach in designing statistics courses are discussed.
Global warming, resulting from increased concentrations of greenhouse gases, may affect ecosystems in different ways and to various extents (Emanuel et al. 1985; Bolin et al. 1986; Solomon and Shugart 1993, etc.). Coral reefs, mangroves, the arctic tundra, and high mountain ecosystems are particularly vulnerable (Markham et al. 1993).
With a simple model, I show that comparisons of invasibility between regions are impossible to make unless one can control for all of the variables besides invasibility that influence exotic richness, including the rates of immigration of species and the characteristics of the invading species themselves. Using data from the literature for 184 sites around the world, I found that nature reserves had one-half of the exotic fraction of sites outside reserves, and island sites had nearly three times the exotic fraction of mainland sites. However, the exotic fraction and the number of exotics were also dependent on site area, and this had to be taken into account to make valid comparisons between sites. The number of native species was used as a surrogate for site area and habitat diversity. Nearly 70% of the variation in the number of exotic species was accounted for by a multiple regression containing the following predictors: the number of native species, whether the site was an island or on the mainland, and whether or not it was a nature reserve. After controlling for scale, there were significant differences among biomes, but not continents, in their level of invasion. Multiple biome regions and temperate agricultural or urban sites were among the most invaded biomes, and deserts and savannas were among the least. However, there was considerable within-group variation in the mean degree of invasion. Scale-controlled analysis also showed that the New World is significantly more invaded than the Old World, but only when site native richness (probably a surrogate for habitat diversity) is factored out. Contrary to expectation, communities richer in native species had more, not fewer, exotics. For mainland sites, the degree of invasion increased with latitude, but there was no such relationship for islands. Although islands are more invaded than mainland sites, this is apparently not because of low native species richness, as the islands in this data set were no less rich in native species than were mainland sites of similar area. The number of exotic species in nature reserves increases with the number of visitors. However, it is difficult to draw conclusions about relative invasibility, invasion potential, or the roles of dispersal and disturbance from any of these results. Most of the observed patterns here and in the literature could potentially be explained by differences between regions in species properties, ecosystem properties, or propagule pressure.