Antje Ahrends

Antje AhrendsRoyal Botanic Garden Edinburgh

26.14
· PhD
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    Upon publication of the original article [1], the authors noticed that the figure labelling for Fig. 4 in the online version was processed wrong. The top left panel should be panel a, with the panels to its right being b and c. d and e should be the panels on the lower row, and f is correct. The graphs themselves are all correct. It is simply the letter labels that are wrong.
    Leaf cuticle micromorphology has been cited as an important set of taxonomic characters in gymnosperms, but previous studies have largely been based on small sample sizes. The premise of this study was to understand whether external factors affect cuticular micromorphology of Podocarpaceae. Two example species, Prumnopitys andina and Podocarpus salignus , were studied. Of 21 sampled characters, nine (c.43% of the total) were visually assessed as being moderately reliable or highly reliable for taxonomic discrimination for both species, with an additional six (c.29%) being moderately reliable or highly reliable for only one or other of the example species, and six characters (c.29%) unreliable for both. Seven of the most variable stomatal characters were selected for further analysis to establish whether environmental factors affect them. The relationship between these seven stomatal characters, the environment and climate was analysed using the R ‘vegan’ package and climate data gathered from WorldClim. Our results showed that both species had larger stomata in moist and shady conditions, and a higher density of (smaller) stomata in sunny and drier conditions. An additional novel finding was the presence of stomata on the adaxial leaf surface in 46% of samples of Prumnopitys andina : the first record of adaxial stomata in this species, highlighting the necessity of studying multiple samples of a given species. In conclusion, these results indicate that larger sample sizes than have hitherto been employed in cuticle micromorphological studies are necessary to fully document the amount of phenotypic variation that exists.
    China is investing immense resources for planting trees, totalling more than US$ 100 billion in the past decade alone. Every year, China reports more afforestation than the rest of the world combined. Here, we show that China's forest cover gains are highly definition-dependent. If the definition of ‘forest’ follows FAO criteria (including immature and temporarily unstocked areas), China has gained 434 000 km2 between 2000 and 2010. However, remotely detectable gains of vegetation that non-specialists would view as forest (tree cover higher than 5 m and minimum 50% crown cover) are an order of magnitude less (33 000 km2). Using high-resolution maps and environmental modelling, we estimate that approximately 50% of the world's forest with minimum 50% crown cover has been lost in the past approximately 10 000 years. China historically lost 1.9–2.7 million km2 (59–67%), and substantial losses continue. At the same time, most of China's afforestation investment targets environments that our model classes as unsuitable for trees. Here, gains detectable via satellite imagery are limited. Conversely, the regions where modest gains are detected are environmentally suitable but have received little afforestation investment due to conflicting land-use demands for agriculture and urbanization. This highlights the need for refined forest monitoring, and greater consideration of environmental suitability in afforestation programmes.%U http://rspb.royalsocietypublishing.org/content/royprsb/284/1854/20162559.full.pdf
    Population genetic structure was studied in two Scaevola (Goodeniaceae) species across their ranges in New Caledonia. Scaevola Montana is locally common and distributed primarily on ultramafic substrates, and is used for ecological restoration of mining sites. Scaevola coccinea is a narrow endemic restricted to ultramafic soils in a single valley, where intensive mining activity occurs. We compared levels of diversity and differentiation in the two species using nuclear microsatellites, so as to understand the spatial scale at which populations become isolated. We also measured environmental distances among sites as a crude proxy to estimate where adaptive differentiation may occur. Populations of S. Montana were sampled over a total distance of ∼500km. In contrast, the total range of S. coccinea is 12×6km. Greater allelic diversity and gene diversity was detected within populations of S. Montana than S. coccinea. Both species show high levels of population differentiation (S. Montana FST≤0.437; S. coccinea FST≤0.54). The marked population structure in S. coccinea despite the close proximity of the sampled populations is associated with its pollination by territorial birds and no observed seed-dispersal agents, compared with the greater vagility of insect pollination and bird dispersal of S. Montana. In S. coccinea, given the high levels of differentiation, we highlight the importance of each individual population for the conservation of intra-specific biodiversity in this species. In S. Montana, we used a combination of the genetic data and environmental characteristics of each of the sample sites to outline general guidelines on seed sources for restoration programs.
    Effective conservation of threatened species requires a good understanding of their habitat. Most primates are threatened by tropical forest loss. One population of the critically endangered kipunji monkey Rungwecebus kipunji occurs in a restricted part of one forest in southern Tanzania. This restricted range is something of an enigma. We collated woody vegetation data to assess habitat quality in and around the core kipunji range (Vikongwa) compared to other nearby forests. Habitat quality in Vikongwa was high compared to other regional and African forests, in that tree stem density, basal area, species richness and availability of kipunji dietary species were all comparatively high. However, the nearby Sanje forest, where the kipunji is absent, had comparable habitat to Vikongwa. We concur with previous research that the kipunji is dependent on old growth forest. However, the availability of comparable vegetation in at least one nearby forest suggests that habitat is not the only reason for the kipunji's restricted range.
    Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha−1. Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases.
    Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the pre-satellite era. Here we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitised historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a five-fold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha−1 yr−1. This is at least three-fold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha−1, compared to a committed loss of 11.9 (7.2-16.6) Mg C ha−1 within areas lacking such protection. Furthermore, for nine protected areas where LULCC data is available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics.
    China is one of the most significant providers of pollination ecosystem services globally. In addition to having unparalleled bee diversity, China has more than eight million managed bee colonies, and it is the world's major honey producer. Yet, pollinators in China, especially bumble bees (Bombus spp.) and honey bees (Apis spp.), are likely at risk. Massive pollinator declines in various countries have rightly grabbed the attention of beekeepers, scientists, policymakers, and the general public, but research has almost exclusively focused on the U.S. and Europe, while countries with significantly higher pollination resources (such as China) have received far less attention. This perspective piece questions and highlights the risks to wild and managed pollinators in China and critical research gaps. We show that there may be a “pollination gap” in China for crops dependent on insect pollination and we examine the potential causes. Specifically, we assess the risks associated with land-use intensification, pesticide poisoning, climate change, invasive species, and other factors affecting the survival of bee pollinators in Asia. If true, the effects of declining pollinator populations in China would be felt globally, and with so much at stake, this problem merits careful consideration in the development of agriculture, economic, and conservation policies.
    The rapidly growing car industry in China has led to an equally rapid expansion of monocul-ture rubber in many regions of South East Asia. Xishuangbanna, the second largest rubber planting area in China, located in the Indo-Burma biodiversity hotspot, supplies about 37% of the domestic natural rubber production. There, high income possibilities from rubber drive a dramatic expansion of monoculture plantations which poses a threat to natural forests. For the first time we mapped rubber plantations in and outside protected areas and their net present value for the years 1988, 2002 (Landsat, 30 m resolution) and 2010 (Rapi-dEye, 5 m resolution). The purpose of our study was to better understand the pattern and dynamics of the expansion of rubber plantations in Xishuangbanna, as well as its economic prospects and conservation impacts. We found that 1) the area of rubber plantations was 4.5% of the total area of Xishuangbanna in 1988, 9.9% in 2002, and 22.2% in 2010; 2) rubber monoculture expanded to higher elevations and onto steeper slopes between 1988 and 2010; 3) the proportion of rubber plantations with medium economic potential dropped from 57% between 1988 and 2002 to 47% in 2010, while the proportion of plantations with lower economic potential had increased from 30% to 40%; and 4) nearly 10% of the total area of nature reserves within Xishuangbanna has been converted to rubber monoculture by 2010. On the basis of our findings, we conclude that the rapid expansion of rubber plantations into higher elevations, steeper terrain, and into nature reserves (where most of the remaining forests of Xishuangbanna are located) poses a serious threat to biodiversity and environmental services while not producing the expected economic returns. Therefore, it is essential that local governments develop long-term land use strategies for balancing economic benefits with environmental sustainability, as well as for assisting farmers with the selection of land suitable for rubber production.
    We present an analysis of changes of state, pressures and conservation responses over 20 years in the Tanzanian portion of the Coastal Forests of Eastern Africa biodiversity hotspot. Baseline data collected during 1989–1995 are compared with data from a synthesis of recently published papers and reports and new field work carried out across the region during 2010–2014. We show that biodiversity endemism values are largely unchanged, although two new species (amphibian and mammal) have been named and two extremely rare tree species have been relocated. However, forest habitat continues to be lost and degraded, largely as a result of agricultural expansion, charcoal production to supply cities with cooking fuel, logging for timber and cutting of wood for firewood and building poles. Habitat loss is linked to an increase in the number of species threatened over time. The government-managed forest reserve network has expanded slightly but has low effectiveness. Three forest reserves have been upgraded to National Parks and Nature Reserves, which have stricter protection and more effective enforcement. There has also been rapid development of village-owned forest reserves, with more than 140 now existing; although usually small, they are an important addition to the areas being managed for sustainable resource use, and also provide tangible benefits to local people. Human-use pressures remain intense in many areas, and combined with emerging pressures from mining, gas and oil exploration, many endemic species remain threatened with extinction.
    The great bulk of the present knowledge of the Tree of Life comes from many phylogenies, each with relatively few tips, but with lots of diversity concerning taxa and characters sampled and methods of analysis used. For several biodiversity hotspots this is the kind of data available and ready to be used to have a better understanding on the evolutionary patterns and to identify areas with remarkable evolutionary history. But relying on data coming from independent studies raises some methodological challenges of standardization, comparability and assessments of bias to make the best use of the currently available information. To bring light to this subject here we analyzed the distribution of phylogenetic diversity in New Caledonia, a biodiversity hotspot characterized by strong rates of regional and internal endemicity. We used a dataset with 18 phylogenies distributed in 16 study sites, and based our analysis on the measure Ws sum. Our study comprises the analysis of (1) the role of the number of phylogenies on site’ scores and a strategy of standardization of the dataset by the number of phylogenies; (2) the influence of species richness on site scores and the design of the measure Ws ranks to focus on the most divergent species of each phylogeny; (3) an assessment of the influence of individual phylogenies; (4) a resampling strategy using multiple phylogenies to verify the results’ stability.
    p>Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha<sup>-1</sup>. Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases.</p
    Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the pre-satellite era. Here we quantify the LULCC history across the 33.9 million ha watershed of Tanzania’s Eastern Arc Mountains, using geo-referenced and digitised historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a five-fold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha-1 yr-1. This is at least three-fold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha-1, compared to a committed loss of 11.9 (7.2-16.6) Mg C ha-1 within areas lacking such protection. Furthermore, for nine protected areas where LULCC data is available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics.
    The first decade of the new millennium saw a boom in rubber prices. This led to rapid and widespread land conversion to monoculture rubber plantations in continental SE Asia, where natural rubber production has increased >50% since 2000. Here, we analyze the subsequent spread of rubber between 2005 and 2010 in combination with environmental data and reports on rubber plantation performance. We show that rubber has been planted into increasingly sub-optimal environments. Currently, 72% of plantation area is in environmentally marginal zones where reduced yields are likely. An estimated 57% of the area is susceptible to insufficient water availability, erosion, frost, or wind damage, all of which may make long-term rubber production unsustainable. In 2013 typhoons destroyed plantations worth US$ >250 million in Vietnam alone, and future climate change is likely to lead to a net exacerbation of environmental marginality for both current and predicted future rubber plantation area. New rubber plantations are also frequently placed on lands that are important for biodiversity conservation and ecological functions. For example, between 2005 and 2010 >2500 km2 of natural tree cover and 610 km2 of protected areas were converted to plantations. Overall, expansion into marginal areas creates potential for loss-loss scenarios: clearing of high-biodiversity value land for economically unsustainable plantations that are poorly adapted to local conditions and alter landscape functions (e.g. hydrology, erosion) - ultimately compromising livelihoods, particularly when rubber prices fall.
    1. Key Points • This report describes an analytical procedure aimed at ranking Notifiable Features in Scotland according to the risk posed to them by climate change. • As well as discussing the results of this ranking process, it looks at potential adaptive management approaches for the most highly ranked features within that list. • Different analytical approaches were necessary for Earth Science and Biodiversity Features, and each are reported separately • Further work is underway to discuss the results with relevant experts, to develop new analytical procedures, and to explore the adaptation actions that might be applied http://www.climatexchange.org.uk/files/7014/2132/8263/CXC_Risk_Assessment_summary_report_update_Dec_14.pdf
    Detailed knowledge of species distributions, endemism patterns and threats is critical to site prioritization and conservation planning. However, data from biodiversity inventories are still limited, especially for tropical forests, and even well recognized hotspots remain understudied. We provide an example of how updated knowledge on species occurrence from strategically directed biodiversity surveys can change knowledge on perceived biodiversity importance, and facilitate understanding diversity patterns and the delivery of conservation recommendations.
    The Eastern Arc Mountains are believed to support some of the oldest tropical forest in the world. The current distribution of this forest is highly fragmented due to a combination of long-term effects of past changes in global climate and more recent deforestation. We sought to explore the hypothesized antiquity and long-term isolation of the Eastern Arc montane forests based on an assessment of the geographical distribution and interspecies similarity of chloroplast DNA sequence variation in five forest trees. Data were used to investigate regional patterns of diversity and population structure based on intraspecific phylogenies, and results were interpreted against hypotheses on ecosystem age and connectivity. Regional diversity was high, with up to 22 chloroplast DNA haplotypes being recorded within a species across the sampled populations. Geographical concordance of genetic and geographic structure was weak to absent in all species and there was little similarity of genetic structure between species. Haplotype sharing between mountain blocks was extremely limited. The generally weak phylogeographical structure, in conjunction with high regional diversity and genetic uniqueness of individual mountain forests does not support the assumption of widespread genetic connectivity of the mountain forests, indicating instead a pattern of past isolation and ongoing diversification. Our findings substantially add to understanding patterns of diversity in this region and lend weight to calls to use more sophisticated biodiversity assessments when setting regional conservation and research funding priorities.
    Background: The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results: We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C ha-1) than woody savanna (51 Mg C ha-1). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C ha-1 yr-1 (c. 2% of the stocks of carbon per year).
    Camellia seed oil is well known for its industrial uses. However, despite the increasing use of this oil, few studies have investigated which factors impact seed oil production. Thus, the aims of this study are to identify which factors influence the percentage seed oil of Camellia reticulata, a by investigating both seed and environmental variables. Firstly, fruit traits were studied and correlated against percentage seed oil data, and then environmental variables linked to seed oil production were investigated. The first experiments analyzed how well fruit characteristics (size, length, weight, seed number, seed oil) of the Camellia plants predict percentage seed oil. The second experiment modelled the effect of environmental variables (soil, elevation, temperature and rainfall) on seed oil production. The results indicated that the kernel ratio per fruit, seed weight to fruit weight ratio and fruit weight positively influenced percentage seed oil while, when these previous effects are accounted for, the number of seeds reduced percentage seed oil. The environmental model showed that seed oil was influenced most strongly by elevation and soil type, with haplic Acrisols providing the highest seed oil. Thus it is clear that Camellia seed oil is affected by a variety of factors, and these should be taken into account when selecting species and cultivars for the planting of Camellia stands for oil production. (C) 2013 Elsevier B.V. All rights reserved.
    New Caledonia is a global biodiversity hotspot facing extreme environmental degradation. Given the urgent need for conservation prioritisation, we have made a first-pass quantitative assessment of the distribution of Narrow Endemic Species (NES) in the flora to identify species and sites that are potentially important for conservation action. We assessed the distributional status of all angiosperm and gymnosperm species using data from taxonomic descriptions and herbarium samples. We characterised species as being NES if they occurred in 3 or fewer locations. In total, 635 of the 2930 assessed species were classed as NES, of which only 150 have been subjected to the IUCN conservation assessment. As the distributional patterns of un-assessed species from one or two locations correspond well with assessed species which have been classified as Critically Endangered or Endangered respectively, we suggest that our distributional data can be used to prioritise species for IUCN assessment. We also used the distributional data to produce a map of "Hotspots of Plant Narrow Endemism" (HPNE). Combined, we used these data to evaluate the coincidence of NES with mining activities (a major source of threat on New Caledonia) and also areas of conservation protection. This is to identify species and locations in most urgent need of further conservation assessment and subsequent action. Finally, we grouped the NES based on the environments they occurred in and modelled the habitat distribution of these groups with a Maximum Entropy Species Distribution Model (MaxEnt). The NES were separable into three different groups based primarily on geological differences. The distribution of the habitat types for each group coincide partially with the HPNE described above and also indicates some areas which have high habitat suitability but few recorded NES. Some of these areas may represent under-sampled hotspots of narrow endemism and are priorities for further field work.
    Despite the availability of several studies to clarify taxonomic problems on the highly threatened yews of the Hindu Kush-Himalaya (HKH) and adjacent regions, the total number of species and their exact distribution ranges remains controversial. We explored the use of comprehensive sets of morphological, molecular and climatic data to clarify taxonomy and distributions of yews in this region. A total of 743 samples from 46 populations of wild yew and 47 representative herbarium specimens were analyzed. Principle component analyses on 27 morphological characters and 15 bioclimatic variables plus altitude and maximum parsimony analysis on molecular ITS and trnL-F sequences indicated the existence of three distinct species occurring in different ecological (climatic) and altitudinal gradients along the HKH and adjacent regions Taxus contorta from eastern Afghanistan to the eastern end of Central Nepal, T. wallichiana from the western end of Central Nepal to Northwest China, and the first report of the South China low to mid-elevation species T. mairei in Nepal, Bhutan, Northeast India, Myanmar and South Vietnam. The detailed sampling and combination of different data sets allowed us to identify three clearly delineated species and their precise distribution ranges in the HKH and adjacent regions, which showed no overlap or no distinct hybrid zone. This might be due to differences in the ecological (climatic) requirements of the species. The analyses further provided the selection of diagnostic morphological characters for the identification of yews occurring in the HKH and adjacent regions. Our work demonstrates that extensive sampling combined with the analysis of diverse data sets can reliably address the taxonomy of morphologically challenging plant taxa.
    Principal component analysis of 15 bioclim variables and altitude. Map showing the environmental variations among the three species of Taxus based on principal component 2 of a PCA. (PDF)
    Niche equivalency and similarity tests according to Broennimann et al. (2012) between T. contorta and T. wallichiana. The top two graphs depict the species niches along the first two axes of a PCA calibrated on the entire environmental space in the two study areas. The bottom left graph shows to the contribution of each of the environmental variables to the ordination axes and the percentage of variance explained by these axes. The three histograms on the bottom right show the observed niche overlap (red line with diamond) and the simulated niche overlaps (grey bars) resampled for the niche identity test (upper histogram), and for the niche similarity test (two bottom histograms) cf. Warren et al. 2008 (Broennimann et al. 2012). The bottom left histogram (“Similarity 2->1”) compares observed niche overlap in the two ranges of T. contorta and T. wallichiana to simulated niche overlap when niches are drawn at random from the T. wallichiana range. In the bottom right histogram (“Similarity 1->2”) niches are drawn at random from the T. contorta range. (TIFF)
    Niche equivalency and similarity tests according to Broennimann et al. (2012) between T. wallichiana and T. mairei. The top two graphs depict the species niches along the first two axes of a PCA calibrated on the entire environmental space in the two study areas. The bottom left graph shows to the contribution of each of the environmental variables to the ordination axes and the percentage of variance explained by these axes. The three histograms on the bottom right show the observed niche overlap (red line with diamond) and the simulated niche overlaps (grey bars) resampled for the niche identity test (upper histogram), and for the niche similarity test (two bottom histograms) cf. Warren et al. 2008 (Broennimann et al. 2012). The bottom left histogram (“Similarity 2->1”) compares observed niche overlap in the two ranges of T. wallichiana and T. mairei to simulated niche overlap when niches are drawn at random from the T. mairei range. In the bottom right histogram (“Similarity 1->2”) niches are drawn at random from the T. wallichiana range. (TIFF)
    Specimens examined. List of specimens examined for the morphometric analysis and GenBank accession numbers of the samples used in the molecular analysis. (PDF)
    Statistics of univariate ANOVA among Taxus of the Hindu Kush-Himalaya and adjacent regions for 19 bioclimatic variables. (PDF)
    Niche equivalency and similarity tests according to Broennimann et al. (2012) between T. contorta and T. mairei. The top two graphs depict the species niches along the first two axes of a PCA calibrated on the entire environmental space in the two study areas. The bottom left graph shows to the contribution of each of the environmental variables to the ordination axes and the percentage of variance explained by these axes. The three histograms on the bottom right show the observed niche overlap (red line with diamond) and the simulated niche overlaps (grey bars) resampled for the niche identity test (upper histogram), and for the niche similarity test (two bottom histograms) cf. Warren et al. 2008 (Broennimann et al. 2012). The bottom left histogram (“Similarity 2->1”) compares observed niche overlap in the two ranges of T. contorta and T. mairei to simulated niche overlap when niches are drawn at random from the T. mairei range. In the bottom right histogram (“Similarity 1->2”) niches are drawn at random from the T. contorta range. (TIFF)
    Principal component analysis of 15 bioclim variables and altitude. Map showing the environmental variations among the three species of Taxus based on principal component 1 of a PCA. (PDF)
    Morphological characters used. Qualitative and quantitative characters used in the morphometric analyses (adopted from Möller et al. 2007). Character 11 shaded grey was modified in the present study. (PDF)
    Correlation matrix of 19 Bioclim variables and altitude. (PDF)
    trnL-F sequence matrix. Variable position of the cpDNA sequences (trnL-F) of 36 accessions sampled across the distribution range of all three species of Taxus. (PDF)
    Ecological niche models of yews in Nepal. Comparison of ecological niche models for A. T. contorta, B. T. wallichiana and C. T. mairei developed on training data where Nepal was left out, and predicted to Nepal. The corresponding AUC values for these models are 0.858 (T. contorta), 0.926 (T. wallichiana) and 0.672 (T. mairei). When T. contorta is predicted by T. wallichiana and T. mairei the corresponding AUC values are 0.835 and 0.8 respectively. When T. wallichiana is predicted by T. contorta and T. mairei the AUC values are 0.871 and 0.706. Finally, when T. mairei is predicted by T. contorta and T. wallichiana the AUC values are 0.723 and 0.776. It should be noted that these AUC scores partly reflect differences in the training data available to the models. T. mairei is better predicted by T. contorta and T. wallichiana, as outside of Nepal the species has few occurrences in a comparable environment. (PDF)
    ITS sequence matrix. Variable position of the nrDNA sequences (ITSLeu-4) of 33 accessions sampled across the distribution range of all three species of Taxus. (PDF)
    Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as 'lowland tropical forest' are often used, termed 'Tier 1 type' analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC 'Tier 2' reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92-6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment.
    The spatial distribution of the size of the cell 95% CI (expressed as a percentage) for the aboveground live carbon pool, using both original land cover categories. (TIF)
    The carbon values, confidence limits and percent error for all five IPCC carbon pools using the original land cover categories. M - Median carbon storage (Mg ha−1); lCI - Lower 95% confidence interval of carbon storage (Mg ha−1); uCI - Upper 95% confidence interval of carbon storage (Mg ha−1); % - Percent error (%); n – Sample size). (DOCX)
    The carbon values and confidence limits for the aboveground live carbon pool using the original and harmonised land cover categories without any form of weighting. These values are not significantly different from the weighted values shown in Table 3 and Table S3 when a paired t-test is performed (p-value<0.693). The range of landscape values derived from these (1.22 [0.91–1.61] Pg C and 1.70 [1.46–1.98] Pg C for original and harmonised land cover categories respectively) overlap those derived from the weighted values and are also significantly higher than previous estimates (Table 2). (Area (million ha); M - Median carbon storage (Mg ha−1); lCI - Lower 95% confidence interval of carbon storage (Mg ha−1); uCI - Upper 95% confidence interval of carbon storage (Mg ha−1); n – Sample size). (DOCX)
    The spatial distribution of aboveground live carbon storage and associated pixel errors within the study area, based on combining the original land cover map with our regionally appropriate carbon values (Table 3). (TIF)
    Ratios used in the derivation of understudied aboveground carbon pools. (DOCX)
    Citations for the data included in Tables S2, S3, S4. (DOCX)
    Aim Effective conservation of biodiversity relies on an unbiased knowledge of its distribution. Conservation priority assessments are typically based on the levels of species richness, endemism and threat. Areas identified as important receive the majority of conservation investments, often facilitating further research that results in more species discoveries. Here, we test whether there is circularity between funding and perceived biodiversity, which may reinforce the conservation status of areas already perceived to be important while other areas with less initial funding may remain overlooked.
    Over the last few decades, resources for descriptive taxonomy and biodiversity inventories have substantially declined, and they are also globally unequally distributed. This could result in an overall decline in the quality of biodiversity data as well as geographic biases, reducing the utility and reliability of inventories. We tested this hypothesis with tropical tree records (n = 24,024) collected from the Eastern Arc Mountains, Tanzania, between 1980 and 2007 by 13 botanists, whose collections represent 80% of the total plant records for this region. Our results show that botanists with practical training in tropical plant identification record both more species and more species of conservation concern (20 more species, two more endemic and one more threatened species per 250 specimens) than untrained botanists. Training and the number of person-days in the field explained 96% of the variation in the numbers of species found, and training was the most important predictor for explaining recorded numbers of threatened and endemic species. Data quality was related to available facilities, with good herbarium access significantly reducing the proportions of misidentifications and misspellings. Our analysis suggests that it may be necessary to account for recorder training when comparing diversity across sites, particularly when assessing numbers of rare and endemic species, and for global data portals to provide such information. We also suggest that greater investment in the training of botanists and in the provisioning of good facilities would substantially increase recording efficiency and data reliability, thereby improving conservation planning and implementation on the ground.
    Tropical forest degradation emits carbon at a rate of approximately 0.5 Pgxy(-1), reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 kmxy(-1), and an inner wave of lower value charcoal production 2 kmxy(-1). This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mgxha(-1); 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.
    Aim Data shortages mean that conservation priorities can be highly sensitive to historical patterns of exploration. Here, we investigate the potential of regionally focussed species distribution models to elucidate fine-scale patterns of richness, rarity and endemism. Location Eastern Arc Mountains, Tanzania and Kenya. Methods Generalized additive models and land cover data are used to estimate the distributions of 452 forest plant taxa (trees, lianas, shrubs and herbs). Presence records from a newly compiled database are regressed against environmental variables in a stepwise multimodel. Estimates of occurrence in forest patches are collated across target groups and analysed alongside inventory-based estimates of conservation priority. Results Predicted richness is higher than observed richness, with the biggest disparities in regions that have had the least research. North Pare and Nguu in particular are predicted to be more important than the inventory data suggest. Environmental conditions in parts of Nguru could support as many range-restricted and endemic taxa as Uluguru, although realized niches are subject to unknown colonization histories. Concentrations of rare plants are especially high in the Usambaras, a pattern mediated in models by moisture indices, whilst overall richness is better explained by temperature gradients. Tree data dominate the botanical inventory; we find that priorities based on other growth forms might favour the mountains in a different order. Main conclusions Distribution models can provide conservation planning with high-resolution estimates of richness in well-researched areas, and predictive estimates of conservation importance elsewhere. Spatial and taxonomic biases in the data are essential considerations, as is the spatial scale used for models. We caution that predictive estimates are most uncertain for the species of highest conservation concern, and advocate using models and targeted field assessments iteratively to refine our understanding of which areas should be prioritised for conservation.
    Moist lower montane vegetation has rarely been classified beyond broad zonational belts over large altitudinal ranges due to highly diverse species composition and structure. This study shows it is possible to further classify such forest types within Bwindi-Impenetrable National Park (BINP), and that these assemblages can be explained by a combination of environmental conditions and past management. Botanical and environmental data were collected along some 4000 m of linear transects from the area surrounding Mubwindi Swamp, BINP. Ordination using Nonmetric Multidimensional Scaling (NMDS) and classification using Two-way Indicator Species Analysis (TWINSPAN) successfully identified four different species assemblages. These forest types were then named on the basis of the ecological characteristics of the species within the group, and the environmental conditions influencing the distribution and past disturbance of the forest. The techniques used were in agreement for three out of the four forest types identified. Analysis using an environmental overlay showed a significant association between forest type and altitude. The results of this study indicate that a regional classification of forest types within moist lower montane forest belt using only tree species is possible, and that the forest types identified can be explained by environmental conditions and past management.
    Over the past 15 years the Tanzanian government has promoted participatory forest management (both joint forest management and community-based forest management) as a major strategy for managing natural forests for sustainable use and conservation. Such management is currently either operational or in the process of being established in > 3.6 million ha of forest land and in > 1,800 villages. Data from three case studies of forests managed using participatory and non-participatory forest management approaches suggest that community involvement in forest management is correlated with improving forest condition. In our first case study we demonstrate increasing basal area and volume of trees per ha over time in miombo woodland and coastal forest habitats under participatory forest management compared with similar forests under state or open access management. In our second case study three coastal forest and sub-montane Eastern Arc forests under participatory forest management show a greater number of trees per ha, and mean height and diameter of trees compared to three otherwise similar forests under state management. In our third case study levels of cutting in coastal forest and Eastern Arc forests declined over time since initiation in participatory forest management sites. We conclude that participatory forest management is showing signs of delivering impact in terms of improved forest condition in Tanzanian forests but that further assessments need to be made to verify these initial findings.
    Over the past 15 years the Tanzanian government has promoted participatory forest management (both joint forest management and community-based forest manage- ment) as a major strategy for managing natural forests for sustainable use and conservation. Such management is cur- rently either operational or in the process of being established in . 3.6 million ha of forest land and in . 1,800 villages. Data from three case studies of forests managed using participatory and non-participatory forest management approaches sug- gest that community involvement in forest management is correlated with improving forest condition. In our first case study we demonstrate increasing basal area and volume of trees per ha over time in miombo woodland and coastal forest habitats under participatory forest management compared with similar forests under state or open access management. In our second case study three coastal forest and sub-montane Eastern Arc forests under participatory forest management show a greater number of trees per ha, and mean height and diameter of trees compared to three otherwise similar forests under state management. In our third case study levels of cutting in coastal forest and Eastern Arc forests declined over time since initiation in participatory forest management sites. We conclude that participatory forest management is show- ing signs of delivering impact in terms of improved forest condition in Tanzanian forests but that further assessments need to be made to verify these initial findings.
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