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Use of hedgerows by mammals in an intensive agricultural landscape
Abstract
Agricultural intensification causes habitat modification, sometimes leading to habitat loss and subsequent loss of connectivity. Remaining species in these agriculture-dominated landscapes often use hedgerows, such as windbreaks or riparian strips, as movement corridors or even as habitats. However, the understanding of the use of these hedgerows by mammals is limited and could be improved with the use of high-resolution remote sensing data, which are unbiased, detailed and repeatable. The aim of this study was to assess the attributes that affect medium- and large-sized mammals’ use of hedgerows, with in situ and remotely sensed data (including LiDAR and multispectral images) in an agriculture-dominated landscape in southern Québec. Twenty-three hedgerows were selected and characterized with both field surveys and remote sensing analyses, like LiDAR metrics and vegetation indices. Wildlife frequentation of each hedgerow was measured using camera traps, from late spring to early fall in 2018. 431 mammal detections were obtained among all 23 hedgerows. From this, seven species were recorded, all of them opportunistic and well adapted to agricultural environment. Results showed significant differences in mammal use of hedgerows. Coefficients of the better-ranked models based on AICc indicated a positive relationship between hedgerow length and their use by mammals, and a negative relationship with the hedgerow width. Hedgerow use by mammals also increased as tree cover and understory density increased, and as human disturbance decreased. These results characterized for the first time the variables influencing hedgerow use by a broad set of medium- and large-sized mammal species and confirmed their use as movement corridors and/or habitat. This study also confirmed the complementary usefulness of variables derived from remote sensing combined with field data. The low explanatory power of variables often cited in the literature (e.g. NDVI, gappiness) also highlights the need to further explore their specific influence on mammals. The information provided by this study supports the beneficial role played by hedgerows for wildlife conservation in intensive agricultural landscapes. Management guidelines are provided as well as future research avenues.
... Over the last one hundred years, the pace of landscape deterioration has increased because of increased human population growth and the concomitant increased demand for food (Petellier-Guittier et al., 2020). In the Western Cape Province, where more than 50% of South Africa's agricultural exports originate, this is no different. ...
... Over the last one hundred years, the pace of landscape deterioration has increased because of increased human population growth and the concomitant increased demand for food (Petellier-Guittier et al., 2020). In the Western Cape Province, where more than 50% of South Africa's agricultural exports originate, this is no different. ...
... Such vertical stratification describes the presence of different age classes or life forms existing at certain heights (e.g., herbs, shrubs, and trees). In particular, understorey vegetation in forests Vogeler et al., 2014) and shrub vegetation such as hedgerows in agricultural landscapes (Pelletier-Guittier et al., 2020) are often considered important factors for species richness, as they provide nesting and foraging habitats, affect visibility and prey abundance, and alter the nearsurface microclimate (Stickley & Fraterrigo, 2021). On the other hand, vegetation can also act as an obstacle, and it has been shown that forest-dwelling aerial insectivores, such as some bird species or bats, prefer forests without a shrub layer as an optimal foraging habitat (Lesak et al., 2011;Rauchenstein et al., 2022). ...
Ecosystem structure, especially vertical vegetation structure, is one of the six essential biodiversity variable classes and is an important aspect of habitat heterogeneity, affecting species distributions and diversity by providing shelter, foraging, and nesting sites. Point clouds from airborne laser scanning (ALS) can be used to derive such detailed information on vegetation structure. However, public agencies usually only provide digital elevation models, which do not provide information on vertical vegetation structure. Calculating vertical structure variables from ALS point clouds requires extensive data processing and remote sensing skills that most ecologists do not have. However, such information on vegetation structure is extremely valuable for many analyses of habitat use and species distribution. We here propose 10 variables that should be easily accessible to researchers and stakeholders through national data portals. In addition, we argue for a consistent selection of variables and their systematic testing, which would allow for continuous improvement of such a list to keep it up‐to‐date with the latest evidence. This initiative is particularly needed not only to advance ecological and biodiversity research by providing valuable open datasets but also to guide potential users in the face of increasing availability of global vegetation structure products.
... To clarify the resource depletion issues and environmental impacts induced by intensive agriculture, LCA has been widely applied in intensive agriculture systems [9,72,73]. For instance, Pelletier-Guittier et al. [74] evaluated the attributes of hedgerows used by mammals under an intensive agricultural landscape and showed that hedgerows were beneficial for wildlife conservation in intensive agricultural landscapes. To assess the environmental impact of different wheat production systems with different fertilization intensities and types, Charles et al. [75] conducted a LCA by considering both yield and quality of the product and found that optimal combinations of variety, fertilization and land use are necessary for the best production strategies design. ...
Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.
... HALs covered by vegetation act in the landscape similarly as hedgerows, but their origin and character are different. The importance of hedgerows in rural landscapes has already been well documented [41], especially their effect on biodiversity [42][43][44][45][46], microclimate [47], erosion rates and pesticide flow in the landscape [48,49]. By contrast, plužiny still await their recognition. ...
Knowledge about past agricultural land management can bring solutions for future needs. One undervalued historical type of historical rural landscape in temperate Europe is termed plužiny. It consists of individual historical agricultural landforms framed by linear woody vegetation. Our multidisciplinary research quantified the distribution of plužiny in Czechia, utilizing archive materials, geographic information systems, and field surveys for verification. Several case studies give merit to the societal relevance of plužiny and justification for their protection and inclusion in landscape planning. We have assessed the contribution of plužiny to secondary geodiversity by describing the landforms morphometrically, using geophysical imaging of their inner structure, and assessing the possible downslope erosive segregation of soil particles. The results of these analyses prove the positive effect of these landscape features on secondary geodiversity and biodiversity at the species level through the process of induced landscape diversification. The results also document management changes during the last 170 years and provide a basis for assessing their present-day endangerment. Although plužiny are less known compared to bocage landscapes of Western Europe, they are similarly valuable. Landscape managers should better recognize the ecological, cultural, and aesthetic values of plužiny as historical agricultural landforms and protect them as a bio-cultural heritage.
... 9a ,11 ). Vegetative strips often delineate natural field boundaries within agricultural landscapes (Lacoeuilhe et al. 2016;Pelletier-Guittier, Theau & Dupras 2020), or are intentionally planted to provide cover to an adjacent agricultural field (Zheng, Zhu & Xing 2016;Fang 2021). We excluded studies that examined short-term (<12 months) within-field strips, e.g. ...
Agricultural intensification and land clearing for agriculture has resulted in loss of biodiversity worldwide, land degradation and reduced the quality of ecosystems services that assist agriculture. Vegetative strips such as hedgerows and shelterbelts have the potential to provide ecosystem service benefits that improve agricultural production and environmental sustainability. A complex, interdisciplinary body of evidence exists examining the various social, physical, chemical, biological and ecological effects of vegetative strips. Here we provide an update to a systematic map of evidence regarding the social and environmental effects of vegetative strips within boreal and temperate regions. We track temporal changes in research trends since the previous map published on this topic in 2015. We followed the approach the previous map, searching databases using an identical search string. We used pre-defined eligibility criteria and layered article screening, reporting the reasons for article exclusion. We extracted meta-data and descriptively summarised the results to allow comparison to the previous map, producing an interactive database that serves as a comprehensive and up-to-date map of new evidence on top of the previous findings. We found many trends that were consistent with the previous map, including terminology trends, study regions, vegetative strip type, strip location and measured outcomes. We also found that there were key changes in the publication frequency of studies examining some biodiversity-related ecosystem services. In addition, several knowledge gaps identified in the previous map have been filled. A small number of countries in the Global North continue to drive major changes in publication trends.
... Non-crop floral resources also impact parasite epidemiology. For example, strips of native plants along field edges, called 'hedgerows', can support higher richness and abundance of beneficial insects, mammals, and birds [13][14][15]. Farms also feature unmanaged, weedy species along field margins that can attract biodiversity [16]. If non-crop resources from hedgerows and weeds attract and aggregate hosts, this may lead to parasite amplification. ...
Urbanization is associated with increases in impervious land cover, which alters the distribution of resources available to wildlife and concentrates activity in un‐built spaces such as parks and gardens. How resource shifts alter the dynamics of parasite and pathogen transmission has not been addressed for many important species in urban systems. We focus on urban gardens, resource‐rich “islands” within the urban matrix, to examine how the availability of floral resources at local and landscape scales influences the prevalence of 6 RNA viruses and 3 parasites in honey bees and bumble bees. Because parasites and pathogens are transmitted at flowers between visitors, we expected that floral abundance would concentrate bees within gardens, amplifying infection rates in pollinators, unless increases in floral resources would enhance bee diversity enough to dilute transmission. We found that garden size and flowering perennial plant abundance had a positive, direct effect on parasite and pathogen richness in bumble bees, suggesting that resource provisioning amplifies transmission. We also found that parasitism rates in honey bees were positively associated with parasites and pathogens in bumble bees, suggesting spillover between species. Encouragingly, we found evidence that management may mitigate parasitism through indirect effects: garden size had a positive impact on bee diversity, which in‐turn was negatively associated with parasite and pathogen richness in bumble bees. Unexpectedly, we observed that that parasite and pathogen richness in honey bees had no significant predictors, highlighting the complexity of comparing transmission dynamics between species. Although floral resources provide bees with food, we suggest more research on the tradeoffs between resource provisioning and disease transmission to implement conservation plantings in changing landscapes.
... vLEs are often linearly shaped and are frequently situated on the border between agricultural fields where they provide a multitude of agroecosystem services [1]. They act as a habitat and movement corridor for animals and plant species and have a key role in the maintenance of biodiversity in intensive agricultural landscapes [2][3][4]. Furthermore, their typical geometrical arrangement following the edges of agricultural parcels and their association with non-vegetated elements like ditches and fences creates networks of landscape elements [5]. Such networks affect the parcel's and catchment's hydrology since they create both hydrological discontinuities and connections with variable intensity across the landscape. ...
Rural European landscapes are characterized by a variety of vegetated landscape elements. Although it is often not their main function, they have the potential to affect river discharge and the frequency, extent, depth and duration of floods downstream by creating both hydrological discontinuities and connections across the landscape. Information about the extent to which individual landscape elements and their spatial location affect peak river discharge and flood frequency and severity in agricultural catchments under specific meteorological conditions is limited. This knowledge gap can partly be explained by the lack of exhaustive inventories of the presence, geometry, and hydrological traits of vegetated landscape elements (vLEs), which in turn is due to the lack of appropriate techniques and source data to produce such inventories and keep them up to date. In this paper, a multi-step methodology is proposed to delineate and classify vLEs based on LiDAR point cloud data in three study areas in Flanders, Belgium. We classified the LiDAR point cloud data into the classes ‘vegetated landscape element point’ and ‘other’ using a Random Forest model with an accuracy classification score ranging between 0.92 and 0.97. The landscape element objects were further classified into the classes ‘tree object’ and ‘shrub object’ using a Logistic Regression model with an area-based accuracy ranging between 0.34 and 0.95.
... Non-crop floral resources also impact parasite epidemiology. For example, strips of native plants along field edges, called 'hedgerows', can support higher richness and abundance of beneficial insects, mammals, and birds [13][14][15]. Farms also feature unmanaged, weedy species along field margins that can attract biodiversity [16]. If non-crop resources from hedgerows and weeds attract and aggregate hosts, this may lead to parasite amplification. ...
As the global agricultural footprint expands, it is increasingly important to address the link between the resource pulses characteristic of monoculture farming and wildlife epidemiology. To understand how mass-flowering crops impact host communities and subsequently amplify or dilute parasitism, we surveyed wild and managed bees in a monoculture landscape with varying degrees of floral diversification. We screened 1509 bees from 16 genera in sunflower fields and in non-crop flowering habitat across 200 km2 of the California Central Valley. We found that mass-flowering crops increase bee abundance. Wild bee abundance was subsequently associated with higher parasite presence, but only in sites with a low abundance of non-crop flowers. Bee traits related to higher dispersal ability (body size) and diet breadth (pollen lecty) were also positively related to parasite presence. Our results highlight the importance of non-crop flowering habitat for supporting bee communities. We suggest monoculture alone cannot support healthy bees.
... These shelterbelts provide food, browsing area, breeding and nesting ground, shelter from inclement weather, a refuge from predators, and safe travel corridors between habitat areas [117]. Across Canada, shelterbelts and other agroforestry systems, such as riparian plantings and alley cropping, were documented to increase the diversity and abundance of plants [118], mammals [119], avian communities [120][121][122][123], native bees [124] and other beneficial insects [121], benthic insect and fish diversity [125], and soil microbial communities [126][127][128]. ...
In Canada, the agricultural sector has long held a prominent economic, social and cultural position, from substantial evidence of extensive fishing and farming since the times of the first human settlements, to currently accounting for over 100 billion dollars of production and employing 2.3 million people. Steady growth in agricultural production in the country over several decades, supported by strong investment in public agricultural science, has allowed an increasing supply of a wide variety of food and agricultural goods to be available both within the country as well as allowing for substantial exports abroad and deep integration of the Canadian agricultural sector into global markets. Along with securing continued productivity growth in agricultural output for the future, policy makers and public sector agricultural scientists in Canada have become increasingly concerned with managing environmental externalities associated with agricultural production in order to achieve the objective of sustainable intensification of the sector. However, the process of identification of the best tools and practices to improve the sustainability of the agricultural sector in Canada has evolved over time due to shifting research priorities and dynamic changes in the problems facing the sector. In this paper we discuss applied and direct-to-farmer agricultural science research initiatives that are focused on identification and implementation of best environmental management practices at the farm level. We believe that involving farmers directly in scientific research and communication of scientific results provides for a deeper understanding of agro-environmental externalities. It also allows farmers to find greater adoption potential in their specific farm system, thus combining both environmental and economic sustainability. We trace the history of public agricultural science engagement with Canadian farmers to address economic and environmental problems in the sector. We then provide examples of successful public sector projects based in applied agricultural science research that foster effective farmer/scientist collaboration, leading to improved agriculture sustainability in Canada.
... This corridor is vital in ecological conduits that have been used in conservation planning and biological connectivity, especially in the valley margin [11][16] [21]. This corridor also has some functions as reducing wind velocity, limiting odors from the livestock industry, increase carbon sequestration, and reduce sediment in rivers or streams [6][7] [12][13] [14]. Detailed information about the corridor and vegetation types in Sekaran Village can be seen in Table 1. ...
Drought is the main problem faced in agricultural activities in Sekaran Village, Bojonegoro Regency. The primary agricultural commodities in Sekaran Village are corn and cattle breeding. Tree corridor planning is one of the proposed solutions to overcome this problem. This study aimed to develop a tree corridor plan for the agricultural area’s ecological sustainability in Sekaran Village by improving the quality and quantity of green open space. Spatial data obtained from the field survey using drone technology. Environmental variables used for corridor plan analysis were land cover, slope, road, and orthomosaic imageries. This study produced a tree corridor planning along 156.57 km located in agriculture land, roadsides, and valley/basin. The proposed tree species has ecological functions such as water absorption and improving microclimate, production functions (food and cattle feed), and aesthetic functions. Tree corridors will use a hedgerow model to form an integrated corridor system in Sekaran Village. Tree species recommended such as Swietenia mahogani, Delonix regia, Spathodea campanulata, Gliricidia sepium, Centrosema pubescens, Leucaena leucocephala, Mangifera indica, Artocarpus heterophyllus, Psidium guajava .
Over 80 illustrated design guidelines for conservation buffers are synthesized and developed from a review of over 1,400 research publications. Each guideline describes a specific way that a vegetative buffer can be applied to protect soil, improve air and water quality, enhance fish and wildlife habitat, produce economic products, provide recreation opportunities, or beautify the landscape. These science based guidelines are presented as easy-to-understand rules-of-thumb for facilitating the planning and designing of conservation buffers in rural and urban landscapes.
Vegetation structure is a crucial component of habitat selection for many taxa, and airborne LiDAR (Light Detection and Ranging) technology is increasingly used to measure forest structure. Many studies have examined the relationship between LiDAR-derived structural characteristics and wildlife, but few have examined those characteristics in relation to small mammals, specifically, small mammal diversity. The aim of this study was to determine if LiDAR could predict small mammal diversity in a temperate-mixed forest community in Northern Wisconsin, USA, and which LiDAR-derived structural variables best predict small mammal diversity. We calculated grid metrics from LiDAR point cloud data for 17 plots in three differently managed sites and related the metrics to small mammal diversity calculated from five months of small mammal trapping data. We created linear models, then used model selection and multi-model inference as well as model fit metrics to determine if LiDAR-derived structural variables could predict small mammal diversity. We found that small mammal diversity could be predicted by LiDAR-derived variables including structural diversity, cover, and canopy complexity as well as site (as a proxy for management). Structural diversity and canopy complexity were positively related with small mammal diversity, while cover was negatively related to small mammal diversity. Although this study was conducted in a single habitat type during a single season, it demonstrates that LiDAR can be used to predict small mammal diversity in this location and possibly can be expanded to predict small mammal diversity across larger spatial scales.
In agricultural landscapes, small woodland patches can be important wildlife refuges. Their value in maintaining biodiversity may, however, be compromised by isolation, and so knowledge about the role of habitat structure is vital to understand the drivers of diversity. This study examined how avian diversity and abundance were related to habitat structure in four small woods in an agricultural landscape in eastern England.
The aims were to examine the edge effect on bird diversity and abundance, and the contributory role of vegetation structure. Specifically: what is the role of vegetation structure on edge effects, and which edge structures support the greatest bird diversity?
Annual breeding bird census data for 28 species were combined with airborne lidar data in linear mixed models fitted separately at i) the whole wood level, and ii) for the woodland edges only.
Despite relatively small woodland areas (4.9 – 9.4 ha), bird diversity increased significantly towards the edges, being driven in part by vegetation structure. At the whole woods level, diversity was positively associated with increased vegetation above 0.5 m and especially with increasing vegetation density in the understorey layer, which was more abundant at the woodland edges. Diversity along the edges was largely driven by the density of vegetation below 4 m.
The results demonstrate that bird diversity was maximised by a diverse vegetation structure across the wood and especially a dense understorey along the edge. These findings can assist bird conservation by guiding habitat management of remaining woodland patches.
This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various energy flows and their resulting Energy Return on Investment (EROI). In the nineteenth century, Quebec agroecosystems were typical examples of historical organic agriculture, with a low dependence on external Inputs but a high dependence on biomass reused, mainly livestock feed and crop seeds. Following the full industrialization of Quebec agriculture by the 1960s, there have been massive injections of external inputs, but also steadily rising amounts of biomass reused due to livestock specialization and the decoupling of domesticated animals from crop farming. As a result of this transformation, the energy efficiency of agroecosystems diminished, despite the significant increases in both final produce and area productivity that were achieved.
The aim was to investigate the relationship between climate, topography and soil pH, as well as vegetation structure and the beta diversity of plants, butterflies and birds; and to investigate the correlations of (woody) plant beta diversity with animal beta diversity. Switzerland (central Europe). We used pairwise Sørensen dissimilarity as measure of total beta diversity and partitioned it into its turnover and nestedness components. Variation partitioning was used to assess the independent and cumulative effects of environmental predictors, with vegetation structure being derived from airborne light detection and ranging (LiDAR) data. We also checked for independent effects of plant and woody plant beta diversity on butterfly and bird beta diversity, respectively, and for independent effects of spatial distance on beta diversity. Climate emerged as the strongest statistical predictor of beta diversity across taxonomic groups, with large independent effects on species turnover. Climate effects were most pronounced for plants, followed by butterflies and birds. We also found large independent effects of vegetation structure on total beta diversity and its turnover component across taxonomic groups, particularly for birds. Plant and woody plant beta diversity substantially improved the predictions of butterfly and bird beta diversity, respectively. Spatial distance had hardly any independent effect on beta diversity. Climate is a stronger filter for plant communities than for butterfly and bird communities, which are more affected by vegetation structure, probably owing to associated resources and niches. Vegetation structure is a crucial predictor of beta diversity, and therefore contiguous and detailed 3-D habitat structure data are highly relevant to further our understanding of niche-based community assembly. Plant and animal beta diversity appear to be non-independent, suggesting that differences in the response times of interacting taxa should be accounted for in environmental change impact assessments on biodiversity.
Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1–10 cameras), and (2) by total season length (1–365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40–128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species.
Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we develop a framework integrating uncertainty in climate and land-use change projections with the latest developments in network connectivity research and spatial, multi-purpose conservation prioritization. We apply this framework to a set of fourteen vertebrate focal species in peri-urban Montreal, Canada. We show that accounting for connectivity in spatial prioritization strongly modifies conservation priorities, and that these priorities are robust to uncertain climate change. We use land-use change simulations to explore the robustness of species' habitat networks to alternative development scenarios. Setting conservation priorities based on habitat quality and connectivity maintains a large proportion of the region's connectivity despite anticipated habitat loss due to climate and land-use change. We found that the application of connectivity criteria alongside habitat quality criteria for protected-area design is area-efficient and does not necessarily amplify trade-offs among conservation criteria. Our approach and results are now being applied in and around the city of Montreal and are well suited to the design of ecological networks and green infrastructure for biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. This article is protected by copyright. All rights reserved.
Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse‐scale environmental variables such as the area of broad land‐cover types. Fine‐scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large‐scale datasets of their extent prevents their inclusion in large‐scale modelling studies.
We assessed whether a novel spatial dataset mapping linear and woody‐linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.
Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas.
Synthesis and applications. This study demonstrates that a national‐scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri‐environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.
Essential Biodiversity Variables (EBVs) have been suggested to harmonize biodiversity monitoring worldwide. Their aim is to provide a small but comprehensive set of monitoring variables that would give a balanced picture of the development of biodiversity and the reaching of international and national biodiversity targets. Globally, GEO BON (Group on Earth Observations Biodiversity Observation Network) has suggested 22 candidate EBVs to be monitored. In this article we regard EBVs as a conceptual tool that may help in making national scale biodiversity monitoring more robust by pointing out where to focus further development resources. We look at one country ?Finland ?with a relatively advanced biodiversity monitoring scheme and study how well Finland?s current biodiversity state indicators correspond with EBVs. In particular, we look at how national biodiversity monitoring could be improved by using available remote sensing (RS) applications. Rapidly emerging new technologies from drones to airborne laser scanning and new satellite sensors providing imagery with very high resolution (VHR) open a whole new world of opportunities for monitoring the state of biodiversity and ecosystems at low cost. In Finland, several RS applications already exist that could be expanded into national indicators. These include the monitoring of shore habitats and water quality parameters, among others. We hope that our analysis and examples help other countries with similar challenges. Along with RS opportunities, our analysis revealed also some needs to develop the EBV framework itself.
Riparian forests are often the last remaining areas of natural vegetation in agricultural and plantation forestry landscapes. Covering millions of hectares of land in Indonesia, industrial pulpwood plantations have rapidly replaced native forests. Our study aimed to better understand the conservation importance of linear remnants of riparian forest by examining their use by larger (>1 kg) mammal species. Our study site was located within an extensive acacia (Acacia mangium) plantation adjoining Tesso Nilo National Park in Sumatra, Indonesia. Camera traps were used to detect mammals at 57 sites to assess the effects of corridor design and land cover covariates and species behavioral traits on mammal habitat use of four linear riparian forests. We recorded 17 species (including one International Union for Conservation of Nature [IUCN] Critically Endangered, two Endangered, and four Vulnerable) in riparian forests inside the plantation, including the Sumatran tiger (Panthera tigris sumatrae), Malay tapir (Tapirus indicus), and sun bear (Helarctos malayanus). Some threatened species were only detected in the park buffer zone. Species varied in their responses to riparian forests, but distance to the national park, remnant width, and percent forest cover around the camera site were common predictors of remnant use. Many mammal species used riparian forests regardless of whether they were surrounded by intact acacia forests or recently cleared land. Our results indicate that linear remnant riparian forests 200 m in width can facilitate local (< 4 km) movements of many large mammal species in Sumatra, but wider riparian remnants would likely be more effective at promoting mammal movements over longer distances.
Windbreaks are a major component of agroforestry practices and play an important role in agroforestry ecosystems. They can reduce wind velocity and protect shelter crops from wind damage and soil from wind erosion. Porosity is one of the most important structural parameters that affect wind speed and is widely used in the study of wind protection provided by windbreaks. In this paper, a method to estimate porosity using high-resolution satellite imagery is represented. Porosity was difficult to estimate through the direct use of remote sensing data due to the poor relationship with vegetation indices. Thus, two intermediate variables, that is, CL
2 × LAI and CL × LAI × W, which were highly related to porosity, were selected. Leaf area index (LAI) and average tree crown length (CL) were estimated using vegetation indices, and W, which refers to the width of a windbreak, was identified using object-based image analysis. Porosity was estimated using a statistical relationship between porosity and intermediate variables. The average prediction accuracy of the estimated porosity value was 76.104 %. Based on the estimated porosity value, the windbreaks were grouped into three types, and their efficiency of wind protection was evaluated. The evaluation result indicated that the windbreaks have a very good protective structure in the study area and they can effectively shelter crops from wind damage and erosion. This study can provide a useful guide for studying the wind protection provided by windbreaks on spatial and temporal scales using remote sensing.
Hedges and lines of trees (woody linear features) are important boundaries that connect and enclose habitats, buffer the effects of land management, and enhance biodiversity in increasingly impoverished landscapes. Despite their acknowledged importance in the wider countryside, they are usually not considered in models of landscape function due to their linear nature and the difficulties of acquiring relevant data about their character, extent, and location. We present a model which uses national datasets to describe the distribution of woody linear features along boundaries in Great Britain. The method can be applied for other boundary types and in other locations around the world across a range of spatial scales where different types of linear feature can be separated using characteristics such as height or width. Satellite-derived Land Cover Map 2007 (LCM2007) provided the spatial framework for locating linear features and was used to screen out areas unsuitable for their occurrence , that is, offshore, urban, and forest areas. Similarly, Ordnance Survey Land-Form PANORAMA ® , a digital terrain model, was used to screen out where they do not occur. The presence of woody linear features on boundaries was modelled using attributes from a canopy height dataset obtained by subtracting a digital terrain map (DTM) from a digital surface model (DSM). The performance of the model was evaluated against existing woody linear feature data in Countryside Survey across a range of scales. The results indicate that, despite some underestimation, this simple approach may provide valuable information on the extents and locations of woody linear features in the countryside at both local and national scales. K E Y W O R D S classification, Countryside Survey, Land Cover Map 2007, landscape ecology, linear hedgerow network, rural planning
One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the 'lmerMod' class of the lme4 package, by overloading the anova and summary functions by providing p values for tests for fixed effects. We have implemented the Satterthwaite's method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I - III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using the Kenward-Roger approximation for denominator degrees of freedom (based on the KRmodcomp function from the pbkrtest package). Some other convenient mixed model analysis tools such as a step method, that performs backward elimination of nonsignificant effects - both random and fixed, calculation of population means and multiple comparison tests together with plot facilities are provided by the package as well.
Context
Detailed information on habitat needs is integral to identify conservation measures for declining species. However, field data on habitat structure is typically limited in extent. Remote sensing has the potential to overcome these limitations of field-based studies.
Objective
We aimed to assess abiotic and biotic characteristics of territories used by the declining wood warbler (Phylloscopus sibilatrix), a forest-interior migratory passerine, at two spatial scales by evaluating a priori expectations of habitat selection patterns.
Methods
First, territories established by males before pairing, referred to as pre-breeding territories, were compared to pseudo-absence control areas located in the wider forested landscape (first spatial scale, Nterritories = 66, Ncontrols = 66). Second, breeding territories of paired wood warblers were compared to true-absence control areas located immediately close-by in the forest (second spatial scale, Nterritories = 78, Ncontrols = 78). Habitat variables predominantly described forest structure and were mainly based on first and last pulse lidar (light detection and ranging) data.
Results
Occurrence of pre-breeding territories was related to vegetation height, vertical diversity and stratification, canopy cover, inclination and solar radiation. Occurrence of breeding territories was associated to vegetation height, vertical diversity and inclination.
Conclusions
Territory selection at the two spatial scales addressed was governed by similar factors. With respect to conservation, habitat suitability for wood warblers could be retained by maintaining a shifting mosaic of stand ages and structures at large spatial scales. Moreover, leaf-off lidar variables have the potential to contribute to understanding the ecological niche of species in predominantly deciduous forests.
Although satellite-based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS-EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS-EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long-term coordinated actions.
Context
The legacy of human use of Mediterranean ecosystems results in spatial and temporal heterogeneity of resources for wildlife. Understanding wildlife use of these ecosystems may be improved by including information on ecosystem type, structure, and function extracted from remote sensing data.
Objectives
To assess whether we can improve our understanding of wildlife-habitat use by including information on ecosystem type, structure and function.
Methods
We tested whether remote sensing derived descriptors of ecosystem type, structure (tree cover and patch size) and function (productivity and stress) determine the habitat of stone martens (Martes foina), common genets (Genetta genetta), and European badgers (Meles meles) in southern Portugal. We linked radio-tracking data from five stone martens, five genets and eight badgers with aerial photography, and some spectra-selectivity to classify vegetation, its structure, productivity and drought stress.
Results
Statistically-derived generalized linear mixed regression models using combinations of remotely sensed descriptors of ecosystem type, structure and function, performed better than single ecosystem type descriptors.
Conclusion
Inclusion of information on ecosystem functioning in predictive models of habitat use is more informative than ecosystem type alone, suggesting functional relationships between wildlife and their habitat. However, inclusion of both ecosystem type and function maybe limited to finer spatial resolutions. Our results illustrate the untapped potential of remote sensing to provide detailed descriptors of habitat at adequate spatial scales, now that they are freely available and are systematically collected over space and time. This information adds useful insights on wildlife-habitat relationships under changing patterns of land use and climate.
p>Se ha probado que los mapas que muestran explícitamente las relaciones especie-hábitat constituyen herramientas valiosas en aplicaciones de conservación y gestión, incluyendo la evaluación sobre qué especies y de qué forma se pueden ver afectadas por el cambio climático a gran escala, la fragmentación progresiva del hábitat y los usos del suelo a nivel local. Diversos estudios se han centrado en utilizar la teledetección como herramienta que permite caracterizar la vegetación para el análisis de la selección del hábitat y para cartografiar las relaciones con el entorno natural. Uno de los tipos de hábitats más difíciles de caracterizar mediante teledetección son los sistemas forestales verticales y horizontales complejos. Su caracterización es necesaria para estudiar los aspectos determinantes y/o limitantes para las especies. El uso de la teledetección activa mediante sensores LiDAR y RADAR ha suscitado gran interés en el ámbito de la investigación de especies de fauna silvestre en áreas forestales así como su gestión, dado el potencial de esta tecnología para representar características tridimensionales de estos hábitats. El objetivo de este artículo de revisión es analizar las aplicaciones de teledetección activa en los estudios de hábitat de fauna silvestre en zonas forestales a través de búsquedas de palabras claves en la Web of Science . Se presentan las métricas y métodos comúnmente utilizados, los avances recientes en la caracterización de hábitats forestales y se recomiendan líneas futuras de investigación en el área de teledetección que podrían beneficiar estudios sobre fauna silvestre en ámbitos forestales que actualmente o no existen o están infrautilizados. También se destaca el valor potencial de la fusión de datos de sensores activos y pasivos para la representación de múltiples dimensiones y escalas del hábitat forestal. Si bien el uso de la teledetección en estudios de hábitat de fauna silvestre se ha incrementado en los últimos años, la comunicación fluida entre las comunidades científicas relacionadas con la teledetección, la gestión forestal y la ecología es vital para garantizar el uso y comprensión adecuados de los datos, permitiendo un mejor conocimiento de las necesidades de los usuarios.
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To investigate the performance and relative importance of abiotic and biotic predictors of species richness of three taxa in forest-dominated landscapes across an environmentally heterogeneous mountain region. Switzerland (central Europe). We used a broad set of nationally available environmental predictors grouped into (1) climate, (2) topography and soil and (3) 3-D vegetation structure derived from airborne Light Detection and Ranging (LiDAR) data to spatially predict the forest species richness of vascular plants, butterflies and breeding birds. We used presence data of 212 plant, 157 butterfly and 92 bird species from multiple transect samples in > 220 1 km2 squares at elevations between 261 and 2123 m a.s.l. across 41,248 km2. We applied an ensemble modelling approach consisting of five modelling techniques and evaluated their predictive performance using the cross-validated percentage of explained variance of each predictor group separately and the combinations thereof. We investigated the relative importance and response of each predictor and partitioned the variation into independent and shared components per variable group. Climate performed best in predicting forest species richness across taxa. Vegetation structure particularly improved the predictions of butterfly and bird species richness, while soil pH was an important predictor for forest plant species richness. Climate appeared to be mainly indirectly related to butterfly species richness, via correlations with habitat type and structure. The strength and direction of the relationships between the predictors and species richness were taxon-specific with low cross-taxon congruence. The growing availability of LiDAR data offers powerful new tools for describing vegetation structure and associated animal habitat quality across large areas. This will further our understanding of niche-driven assembly processes in forest landscapes. Although climate was the dominant factor controlling species richness across taxa from different trophic levels, the taxon-specific distributional pattern and response to environmental conditions emphasize the difficulty of accounting for a range of taxa in prioritising biodiversity conservation measures.
A review of the commonly measured habitat factors that affect American martens and fishers is presented. Preferences for cover types and for specific habitat features by the North American Martes are compared, and biological principles are identified that may explain habitat selection by these species.
Two prominent limitations of species distribution models (SDMs) are spatial biases in existing occurrence data and a lack of spatially explicit predictor variables to fully capture habitat characteristics of species. Can existing and emerging remote sensing technologies meet these challenges and improve future SDMs? We believe so. Novel products derived from multispectral and hyperspectral sensors, as well as future Light Detection and Ranging (LiDAR) and RADAR missions, may play a key role in improving model performance. In this perspective piece, we demonstrate how modern sensors onboard satellites, planes and unmanned aerial vehicles are revolutionizing the way we can detect and monitor both plant and animal species in terrestrial and aquatic ecosystems as well as allowing the emergence of novel predictor variables appropriate for species distribution modeling. We hope this interdisciplinary perspective will motivate ecologists, remote sensing experts and modelers to work together for developing a more refined SDM framework in the near future.
The loss of natural habitats and the loss of biological diversity is a global problem affecting all ecosystems including agricultural landscapes. Indicators of biodiversity can provide standardized measures that make it easier to compare and communicate changes to an ecosystem. In agricultural landscapes the amount and variety of available habitat is directly correlated with biodiversity levels. Linear woody features (LWF), including hedgerows, windbreaks, shelterbelts as well as woody shrubs along fields, roads and watercourses, play a vital role in supporting biodiversity as well as serving a wide variety of other purposes in the ecosystem. Earth observation can be used to quantify and monitor LWF across the landscape. While individual features can be manually mapped, this research focused on the development of methods using line intersect sampling (LIS) for estimating LWF as an indicator of habitat availability in agricultural landscapes. The methods are accurate, efficient, repeatable and provide robust results. Methods were tested over 9.5Mha of agricultural landscape in the Canadian Mixedwood Plains ecozone. Approximately 97,000km of LWF were estimated across this landscape with results useable both at a regional reporting scale, as well as mapped across space for use in wildlife habitat modelling or other landscape management research. The LIS approach developed here could be employed at a variety of scales in particular for large regions and could be adapted for use as a national scale indicator of habitat availability in heavily disturbed agricultural landscape.
Wildlife crossing structures help animals cross safely under or over roads or other linear infrastructure and hence play an important role in the conservation of biodiversity. Measuring the rate of use by wildlife is an important first step in almost every evaluation of wildlife crossing structures. Unfortunately, the majority of studies of the use of crossing structures by wildlife lack a proper study design which limits the quality or reliability of the findings. The design and methods of each study to evaluate the use of crossing structures must be tailor‐made because of differences among structures in their design, goals, target species, landscape and road conditions. 15.1 Identify and describe the target species for the wildlife crossing structure being evaluated. 15.2 For each target species, define the intended type and frequency of use. 15.3 Design the study to enable a comparison of actual rate of use and minimum expected rate of use. 15.4 Use data from control plots to estimate the minimum expected rate of use of a crossing structure. 15.5 Select survey methods that monitor multiple species simultaneously and use more than one survey method for each species. 15.6 The timing, frequency and duration of the monitoring should allow for rigorous estimates of crossing structure use. 15.7 Measure explanatory variables to enable a comprehensive analysis of the monitoring data and comparison of crossing structure functioning. 15.8 Thorough analysis, reporting and sharing of data are critical. Taken individually, each study of the use of crossing structures by wildlife provides an important but basic understanding of their function. Adopting the guidelines presented in this chapter will improve the quality of each monitoring programme as well as permit robust meta‐analyses to optimise design, placement and management of wildlife crossing structures at much broader spatial scales.
Animal movement patterns in space and time are a central aspect of animal ecology. Remotely-sensed environmental indices can play a key role in understanding movement patterns by providing contiguous, relatively fine-scale data that link animal movements to their environment. Still, implementation of newly available remotely-sensed data is often delayed in studies of animal movement, calling for a better flow of information to researchers less familiar with remotely-sensed data applications. Here, we reviewed the application of remotely-sensed environmental indices to infer movement patterns of animals in terrestrial systems in studies published between 2002 and 2013. Next, we introduced newly available remotely-sensed products, and discussed their opportunities for animal movement studies. Studies of coarse-scale movement mostly relied on satellite data representing plant phenology or climate and weather. Studies of small-scale movement frequently used land cover data based on Landsat imagery or aerial photographs. Greater documentation of the type and resolution of remotely-sensed products in ecological movement studies would enhance their usefulness. Recent advancements in remote sensing technology improve assessments of temporal dynamics of landscapes and the three-dimensional structures of habitats, enabling near real-time environmental assessment. Online movement databases that now integrate remotely-sensed data facilitate access to remotely-sensed products for movement ecologists. We recommend that animal movement studies incorporate remotely-sensed products that provide time series of environmental response variables. This would facilitate wildlife management and conservation efforts, as well as the predictive ability of movement analyses. Closer collaboration between ecologists and remote sensing experts could considerably alleviate the implementation gap. Ecologists should not expect that indices derived from remotely-sensed data will be directly analogous to field-collected data and need to critically consider which remotely-sensed product is best suited for a given analysis.
Heterogeneous vegetation structure can create a variable landscape of predation risk—a fearscape—that influences the use and
selection of habitat by animals. Mapping the functional properties of vegetation that influence predation risk (e.g., concealment
and visibility) across landscapes can be challenging. Traditional ground-based measures of predation risk are location specific
and limited in spatial resolution. We demonstrate the benefits of terrestrial laser scanning (TLS) to map the properties of
vegetation structure that shape fearscapes. We used TLS data to estimate the concealment of prey from multiple vantage points,
representing predator sightlines, as well as the visibility of potential predators from the locations of prey. TLS provides
a comprehensive data set that allows an exploration of how habitat changes may affect prey and predators. Together with other
remotely sensed imagery, TLS could facilitate the scaling up of fearscape analyses to promote the management and restoration
of landscapes.
Wooded hedgerows do not cover large areas but perform many functions that are beneficial to water quality and biodiversity. A broad range of remotely sensed data is available to map these small linear elements in rural landscapes, but only a few of them have been evaluated for this purpose. In this study, we evaluate and compare various optical remote-sensing data including high and very high spatial resolution, active and passive, and airborne and satellite data to produce quantitative information on the hedgerow network structure and to analyse qualitative information from the maps produced in order to estimate the true value of these maps. We used an object-based image analysis that proved to be efficient for detecting and mapping thin elements in complex landscapes. The analysis was performed at two scales, the hedgerow network scale and the tree canopy scale, on a study site that shows a strong landscape gradient of wooded hedgerow density. The results (1) highlight the key role of spectral resolution on the detection and mapping of wooded elements with remotely sensed data; (2) underline the fact that every satellite image provides relevant information on wooded network structures, even in closed landscape units, whatever the spatial resolution; and (3) indicate that light detection and ranging data offer important insights into future strategies for monitoring hedgerows.
As human threats continue to impact natural habitats, there is an increasing need to regularly monitor the trends in large vertebrate populations. Conservation efforts must be directed appropriately, but field work necessary for data collection is often limited by time and availability of people. Camera traps are used as an efficient method to insure continuous sampling and to work in difficult to access areas. In the present study, we illustrate how this instrument is serving a diverse field of studies, such as animal behavior, population monitoring and fauna-flora interaction. By looking at the material and technical aspects of various models of camera trap for implementation in different field studies in animal ecology, we highlight the need to choose appropriate camera trap models for the target species and to set up solid sampling protocols to successfully achieve study objectives.
Light detection and ranging (lidar) is a useful tool for measuring three-dimensional habitat structure; hence, its use in habitat suitability models has been explored, both as a single resource and in combination with other remote-sensing techniques. Here, we evaluated the suitability of airborne lidar data in comparison with aerial photographs and field surveys for modelling the distribution of an endangered and cryptic forest species, the hazel grouse (Bonasa bonasia). The study was conducted in the Bavarian Forest National Park of southeast Germany. Subsequently, a prediction map for conservation planning was generated for a large area, which encompassed the National Park. We examined the utility of lidar data for generating a hazel grouse distribution model by using machine learning (boosted regression trees), and then compared the results to variables derived from field surveys and aerial photographs, both separately and in combination. The cross-validated discrimination ability of the model was slightly higher when using lidar data (area under the receiver operator characteristic curve (AUC), 0.79) compared to models using aerial photographs (AUC, 0.75) or field survey data (AUC, 0.78). The predictive performance consistently increased when combining the predictors from different sources, with an AUC of 0.86 being produced in the model combining all three data sources. The three data sources complemented one another, with each data source probably having an advantage at deriving one of three key aspects of the hazel grouse habitat, namely, vertically well-structured forest stands, horizontally mixed successional vegetation stages, and certain deciduous trees as food resources such as mountain ash (Sorbus aucuparia). In addition, the diverse lidar metrics might be applied to simultaneously characterize vertically and horizontally well-structured forest stands. We conclude that public available airborne lidar data are a viable source for creating habitat suitability maps for large areas and may have increased utility for detecting forest characteristics and valuable wildlife habitats.
Profil biologique des mammifères de l'est du Canada
A Northern Pocket Gopher can dig an amazing half a metre of tunnel through compacted clay soil in just 15 minutes. North American Beavers, along with humans, are the only mammals whose impact on their environment is so massive that it can be clearly seen with the naked eye from outer space. And there really are Narwhals - the single-tusked mammals that likely inspired the unicorn legend - living in the waters surrounding Greenland. Learning about any of these mammals on their own brings out fascinating traits and stories. But when considered alongside the entire mammal population of Canada - from the tiny Olive-Backed Pocket Mouse to the enormous Killer Whale, and the Arctic-dwelling Polar Bear to the more southerly Red Bat - a spectacular portrait emerges of the diversity and beauty of Canada’s animal life. The Natural History of Canadian Mammals is a beautifully illustrated, up-to-date guide to all 215 known species of mammals in Canada. It features brand-new, full-colour images of each species, as well as stunning photographs from Canadian Geographic magazine’s national photography competitions depicting the animals in their natural environments. Along with being a visual treat, this book is jam-packed with information accessible to readers at all levels. Detailed descriptions are provided of each mammal’s appearance, habitat, and behavior, while colour maps show their full distribution across Canada, North America, and globally. The book also includes practical guides on tracking and identification for readers who would like to learn how to spot mammals in the wild. Among its most special features is a series of colour plates with vignettes of the Canadian representatives of each group, sized relative to one another for easy comparison and linked to the full species accounts later in the book. Comprehensive and immensely valuable, The Natural History of Canadian Mammals will become a treasured companion for scientific researchers, animal lovers, and all those wishing to gain a greater appreciation of Canada’s natural wonders. The Canadian Museum of Nature, Canada’s national natural history museum, continues to author these wonderful books in its goal to inspire a greater understanding of the natural environment.
Pacific marten (Martes caurina) populations have become fragmented and constricted throughout their western range, often due to factors such as increased severity of wildfires and timber harvesting. Future population declines are predicted given decreasing snow packs and changes in vegetation communities. One element of marten habitat, rest and den structures, may be particularly vulnerable. These structures are used for protection from inclement weather and predation, as well as sites for parturition. Rest structures are often considered a limiting habitat element; characterizing their abundance, type, and distribution has been suggested as a way to evaluate habitat quality. We evaluated marten resting habitat, combining vegetation data from light detection and ranging technology (LiDAR) and ground-based surveys. From 2009–2013 and 2015–2017, we located 312 unique rest structures used by 31 martens (18 males, 13 females). With ground-based surveys, we examined selection of used structures by measuring the diameter at breast height for comparison of rest structures and trees located in random plots. For broader landscape-level predicted habitat, we paired used locations with 624 randomly-sampled locations, and optimized 14 habitat covariates at 12 spatial scales using case-controlled logistic regression. Each covariate’s optimized scale was used to develop a series of a priori hypothesized multi-scale habitat selection models. Martens selected woody structures that were larger than random structures (rest structures = 97.8 ± 31.0 cm; random = 52.7 ± 24.9 cm, x̅ ± SD, t = 21.6, p < 0.001). Marten habitat selection was also positively associated with increased canopy cover and structural complexity within 270 m radius of suitable rest structures and increased tree cover at the broadest scale evaluated (990 m). Our models revealed elevation was positively correlated with predicted marten resting habitat; average elevation at our used sites was 1940 m. Finally, our model depicted areas of predicted habitat near road systems, but we assumed this was an artifact from our sampling bias. Because both canopy cover and structural complexity were optimized at a 270 m radius, this may be an appropriate scale to consider for management activities such as establishing leave islands or focal areas of restoration. We provide one of the first evaluations of marten habitat incorporating the use of LiDAR, which can be broadly and accurately extrapolated for management planning and restoration prioritization.
In this review, we discuss the role of hedgerow structure and condition in determining the value of hedgerow habitat for biodiversity conservation within an agricultural context, to inform and evaluate hedgerow management decisions and policy. Through a systematic literature review, narrative synthesis and vote counting, key structural condition indicators were identified for a range of conservation priority taxa. Abundance, survival or fecundity of ground vegetation, birds, mammals and invertebrates were affected by height, width, woody biomass, foliar quality and quantity, and gappiness of hedgerows. Although general patterns may not occur, a response to a particular structural feature can vary both within and between taxonomic groups, many responses are synergistic and interdependent. In conclusion, the definition of a “good quality” hedgerow for biodiversity conservation should be expanded to include all those key structural features which are important across taxa. Furthermore, the importance of heterogeneity in hedgerow structural condition is highlighted, where no fixed set of hedgerow characteristics were found to benefit all taxa. If uniform hedgerow management is overprescribed, as has been the tendency with some agri-environment schemes, some species (including those of conservation concern) are likely to be adversely affected by a loss of suitable habitat or resource decline.
Agriculture is a primary factor underlying world-wide declines in biodiversity. However, different agricultural systems vary in their effects depending on their resemblance to the natural ecosystem, coverage across the landscape, and operational intensity. We combined data from the North American Breeding Bird Survey with remotely sensed measures of crop type and linear woody feature (LWF) density to study how agricultural type, woody structure and crop heterogeneity influenced the avian community at landscape scales across a broad agricultural region of eastern Canada. Specifically, we examined whether 1) avian diversity and abundance differed between arable crop agriculture (e.g., corn, soy) and forage (e.g., hay) and pastoral agriculture, 2) whether increasing the density of LWF enhances avian diversity and abundance, and 3) whether increasing the heterogeneity of arable crop types can reduce negative effects of arable crop amount. Avian diversity was lower in landscapes dominated by arable crop compared to forage agriculture likely due to a stronger negative correlation between arable cropping and the amount of natural land cover. In contrast, total avian abundance did not decline with either agricultural type, suggesting that species tolerant to agriculture are compensating numerically for the loss of non-tolerant species. This indicates that bird diversity may be a more sensitive response than bird abundance to crop cover type in agricultural landscapes. Higher LWF densities had positive effects on the diversity of forest and shrub bird communities as predicted. Higher crop heterogeneity did not reduce the negative effects of high crop amount as expected except for wetland bird abundance. In contrast, greater crop heterogeneity actually strengthened the negative effects of high crop amount on forest bird abundance, shrub-forest edge bird diversity and total bird diversity. We speculate that this was due to negative correlations between crop heterogeneity and the amount of shrub and forest habitat patches in crop-dominated landscapes in our study region. The variable response to crop heterogeneity across guilds suggests that policies aimed at crop diversification may not enhance avian diversity on their own and that management efforts aimed at the retention of natural forest and shrub patches, riparian corridors, and hedge-rows would be more directly beneficial.
Agricultural field margins are often recommended as a cost-effective and efficient method for wild bee conservation, in response to the threat imposed by global pollinator declines as a result of intensive agricultural practices. In this study we compared margin characteristics and wild bee community structure from sites with landscapes of varying agricultural intensity in order to (i) investigate if field margins are valuable for wild bee conservation in all types of landscapes, and (ii) determine which biotic and abiotic margin characteristics best support wild bee abundance and community richness. Margin surveys and wild bee community sampling, comprising pan traps and observations of foraging activity, were carried out over three years at 27 cereal field margins in Catalonia, Spain. Generalized linear models indicated a strong inverse relationship between surrounding landscape diversity and wild bee abundance. The proportion of Halictidae bees (common generalists) increased with decreasing landscape complexity. Floral richness exhibited a positive association with number of foraging bees and morphospecies richness, and was positively correlated with the proportion of shrubs and trees represented in the margins. It was observed that wider margins held a higher proportion of perennial plants and a lower proportion of Halictidae bees. Our study suggests that field margins are more crucial in intensively farmed areas than in heterogeneous landscapes where foraging resources are more abundant. Maintaining wide margins with high flowering plant richness, comprising perennial and shrub species, best supports a dense and diverse bee community. In more diverse landscapes, conservation efforts focused on maintaining the quality of existing natural patches may be most effective.
Predators affect prey directly by removing animals from the population and indirectly by modifying prey behavior. Humans have extirpated apex predators from many ecosystems, and the extent to which smaller predators, or humans themselves, can ecologically replace apex predators remains uncertain. White-tailed deer Odocoileus virginianus in the Eastern United States were released from their two most important predators a century ago following the extirpation of cougars Puma concolor and wolves Canis lupus. We studied the extent to which perceived predation risk from humans and a newly arrived mesopredator, the coyote, Canis latrans affects deer behavior, predicting that deer will be most vigilant in areas hunted by humans which also have the highest levels of coyote activity. We quantified deer vigilance rates in 33 natural areas of which 15 allowed hunting, across six states by evaluating the head posture of 3470 deer photographed at unbaited camera traps. We documented wide variation in coyote activity (0–2.5 detections/day) and human activity (0–306 detections/day), but contrary to our predictions, did not find strong positive relationships between deer vigilance and either of these predators. Deer vigilance was lower in areas with high levels of human recreation, suggesting that deer become habituated to the presence of humans. Vigilance increased across the fall season in both hunted and non-hunted populations, which suggests that increased vigilance may be associated more with mating behavior or environmental factors other than hunting. Our results show that variation in coyote and human activity does not significantly impact the vigilance behavior of white-tailed deer year-round, suggesting that deer rely on other risk-avoidance behaviors or neither are functioning as apex predators in the region.
In most agro-ecosystems, hedgerows provide important habitat for many species. Unfortunately, large scale destruction of hedges has stripped this structure from many landscapes. Replanting programs have attempted to restore hedgerow habitats, but the methods employed often fail to replace the unique micro-habitats (complex matrix of stones, logs and roots found along the base of the hedge) that provided key refuges to an array of animal species. We examined the influence of ground refuges on animal diversity in an agricultural landscape. We used non-lethal rapid biodiversity assessments to sample invertebrate and vertebrate taxa in 69 hedges having different levels of herbaceous cover, tree cover, and refuge availability. Co-inertia analyses compared hedge characteristics with the animal biodiversity sampled. We also used a functional index (accounting for body mass, trophic level, and metabolic mode of the species sampled) to compare hedges. In addition, large sedentary predators (e.g. snakes) were used as indicators of shelter presence/quality and as bio-indicators of food web structures. Finally we used unbiased Chao-estimates to evaluate species richness. All results were convergent and show that complexity of the base of the hedge (e.g., bank size and stone abundance) positively influenced biodiversity and predator abundance. Guidelines to restore hedgerows should integrate refuges that can be constructed by retaining the materials that are extracted during the planting of the hedges.
In European agricultural landscapes, forest fragmentation is one of the most serious threats to wildlife
populations viability. Ecological corridors are the management tool used to mitigate the effects of this
phenomenon and, in agro-ecosystems, they are traditionally represented by hedgerows. Hedgerows vary
dramatically in their internal structure and quality and their effectiveness as corridors depends both on
their physical features, such as width and continuity, and internal habitat conditions. Moreover, the
ecological requirements related to hedgerow structure are strongly species-specific. In this study, we
evaluated which characteristics make a hedgerow suitable for two mammal species sensitive to forest
fragmentation at two very different spatial scales: the European Badger and the Hazel Dormouse. The
study was carried out in a wide lowland area of northern Italy. Following a stratified cluster sampling
design, we surveyed 55 hedgerows. For each hedgerow, we collected both structural and floristic
variables and we evaluated how differently they affect hedgerows use by the European Badger and Hazel
Dormouse. Our results suggested that, in order to simultaneously increase landscape connectivity for
both mammal species, hedgerows should be wide and continuous. Moreover, they should be managed to
allow the growth of native species with a complex physical structure in the shrub layer and to promote
shrubs development by preventing an excessive tree canopy closure. The information we obtained by this
two-species approach provided crucial suggestions for a correct management of hedgerows, which could
be used for the conservation of any species with similar ecological requirements and a similar response to
fragmentation.
Camera trapping is widely used in ecological studies. It is often considered nonintrusive simply because animals are not captured or handled. However, the emission of light and sound from camera traps can be intrusive. We evaluated the daytime and nighttime behavioral responses of four mammalian predators to camera traps in road-based, passive (no bait) surveys, in order to determine how this might affect ecological investigations. Wild dogs, European red foxes, feral cats, and spotted-tailed quolls all exhibited behaviors indicating they noticed camera traps. Their recognition of camera traps was more likely when animals were approaching the device than if they were walking away from it. Some individuals of each species retreated from camera traps and some moved toward them, with negative behaviors slightly more common during the daytime. There was no consistent response to camera traps within species; both attraction and repulsion were observed. Camera trapping is clearly an intrusive sampling method for some individuals of some species. This may limit the utility of conclusions about animal behavior obtained from camera trapping. Similarly, it is possible that behavioral responses to camera traps could affect detection probabilities, introducing as yet unmeasured biases into camera trapping abundance surveys. These effects demand consideration when utilizing camera traps in ecological research and will ideally prompt further work to quantify associated biases in detection probabilities.
This book had its origin when, about five years ago, an ecologist (MacArthur) and a taxonomist and zoogeographer (Wilson) began a dialogue about common interests in biogeography. The ideas and the language of the two specialties seemed initially so different as to cast doubt on the usefulness of the endeavor. But we had faith in the ultimate unity of population biology, and this book is the result. Now we both call ourselves biogeographers and are unable to see any real distinction between biogeography and ecology.
There has been a recent surge of interest in remote sensing and its use in ecology and conservation. This book focuses explicitly on the Normalized Difference Vegetation Index (NDVI), a simple numerical indicator and powerful tool that can be used to assess spatio-temporal changes in green vegetation. The NDVI opens the possibility of addressing questions on scales inaccessible to ground-based methods alone; it is mostly freely available with global coverage over several decades. This text provides an authoritative overview of the principles and possible applications of the NDVI in ecology, environmental and wildlife management, and conservation. NDVI data can provide valuable information about temporal and spatial changes in vegetation distribution, productivity, and dynamics; allowing monitoring of habitat degradation and fragmentation, or assessment of the ecological effects of climatic disasters such as drought or fire. The NDVI has also provided ecologists with a promising way to couple vegetation with animal distribution, abundance, movement, survival and reproductive parameters. Over the last few decades, numerous studies have highlighted the potential key role of satellite data and the NDVI in macroecology, plant ecology, animal population dynamics, environmental monitoring, habitat selection and habitat use studies, and paleoecology. The chapters are organized around two sections: the first detailing vegetation indices and the NDVI, the principles behind the NDVI, its correlation with climate, the available NDVI datasets, and the possible complications and errors associated with the use of this satellite-based vegetation index. The second section discusses the possible applications of the NDVI in ecology, environmental and wildlife management, and conservation.
This chapter gives results from some illustrative exploration of the performance of information-theoretic criteria for model selection and methods to quantify precision when there is model selection uncertainty. The methods given in Chapter 4 are illustrated and additional insights are provided based on simulation and real data. Section 5.2 utilizes a chain binomial survival model for some Monte Carlo evaluation of unconditional sampling variance estimation, confidence intervals, and model averaging. For this simulation the generating process is known and can be of relatively high dimension. The generating model and the models used for data analysis in this chain binomial simulation are easy to understand and have no nuisance parameters. We give some comparisons of AIC versus BIC selection and use achieved confidence interval coverage as an integrating metric to judge the success of various approaches to inference.
Human modification of landscapes is one of the greatest threats facing biodiversity worldwide and conversion of native habitat to agricultural land is widely perceived as contributing significantly to biodiversity declines. However, some species have proven to be adaptable to human-induced habitat change. Here, we show that over the course of the relatively short period of co-existence between badgers (Meles meles) and humans in Ireland, badgers have adapted to using the man-made field boundaries that have replaced native woodland. Our study population, which was located in an intensively managed agricultural landscape, predominantly located their setts and latrines in or alongside hedgerows. In addition, for the first time, we show that badgers selectively foraged along field boundaries, with this behaviour perhaps linked to a greater diversity of dietary items in hedgerows and the potential cover from perceived threats offered by dense undergrowth. This preferential use of man-made landscape features has implications for how we assess habitat use in this species and perhaps also for modelling studies of bovine tuberculosis transmission in agricultural landscapes.
A fundamental challenge in restoration ecology is to understand when species are expected to colonize newly created habitat. Determining this is important for assessing progress toward restoration goals and, more generally, for gaining insight into ecosystem functioning and dynamics. We studied this question as it relates to mid- to large-sized terrestrial fauna in restored riparian habitats at the Sacramento River National Wildlife Refuge, in northern California. We used camera traps to document use of 16 riparian corridor sites of varying restoration age. Comparisons of species richness (diversity) and visitation frequency (activity) were made across different-aged sites. We found that predator diversity and activity levels tended to be higher in restored forests than in remnant forests, and that they tended to be highest in young restored forests. This trend persisted when data from variable sampling periods were pooled, although significant differences occurred more often in wet and cold sampling periods. The trend did not always hold for the animal community at large (consisting of both predator and non-predator species). We conclude that restoration age affects predator diversity and activity levels in restored and remnant floodplain forests, and that predator communities can establish soon after restoration. Our results suggest that restoring natural river processes that promote habitat regeneration may benefit mid- to large-sized terrestrial predators that appear to mostly use early successional habitat.
Tilman's model predicts an asymmetric relationship, with ascending, peak, and descending parts, between plant species diversity and a resource gradient. I evaluated the applicability of Tilman's model to mammals by regressing rodent and carnivore species diversity on estimates of net aboveground primary productivity. Rodent diversity was highest at low productivity levels and declined as productivity increased. Although my data did not confirm the upslope and peak phases of Tilman's model, this may be because I did not sample from areas of extremely low productivity. Published studies from very dry desert habitats indicate that rodent diversity increases rapidly across a narrow gradient of very low productivity and peaks at moderately low levels. This suggests that rodents, which are largely herbivorous, exhibit an asymmetric productivity-diversity curve similar to that predicted by Tilman for plants. The rodent data are also consistent with the intermediate disturbance hypothesis, which predicts diversity as a peaked function of a disturbance gradient. Rainfall predictability, which may function as a disturbance, is inversely related to my plant productivity gradient. The regression curve for carnivores helps to distinguish between these two hypotheses. At a given locality carnivores and rodents should be exposed to about the same disturbance levels and according to the intermediate disturbance model should peak at about the same place. Since carnivores as a whole are about one trophic level above rodents, if plant productivity controls diversity the peak for carnivores should occur at about an order of magnitude of productivity higher than the peak for rodents. My carnivore diversity data exhibit upslope, peak, and downslope phases and are shifted to higher levels of productivity by about one order of magnitude. This provides evidence against the intermediate disturbance hypotheses and corroborates predictions of Tilman's model as applied to mammals.
The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Here, we review insights gained through the application of LiDAR to animal ecology studies, revealing the fundamental importance of structure for animals. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential compared with traditionally measured canopy cover, which produces mixed results. However, different taxonomic groups interact with a variety of 3D canopy traits and some groups with 3D topography. To develop a better understanding of animal dynamics, future studies will benefit from considering 3D habitat effects in a wider variety of ecosystems and with more taxa.