Estimate Habitat Suitability Research Articles

Niche models do not predict experimental demography but both suggest dispersal limitation across the northern range limit of the scarlet monkeyflower (Erythranthe cardinalis)

AbstractAimGeographical ranges largely reflect the projection of species’ environmental niches onto the landscape, but dispersal limitation can cause ranges to fall short of niche limits. Understanding the prevalence of niche and dispersal limitation is a fundamental problem in ecology and biogeography, and it is relevant in predicting climate‐driven range shifts. Dispersal limitation could also cause widely used ecological niche models (ENM), which relate records of occurrence to environmental predictors, to underestimate properties of the ecological niche. Using a combination of experimental transplants and ENM, we tested for (a) dispersal and niche limitation across a species’ range boundary and (b) associations between ENM predictions and population performance.LocationOregon, USA.TaxonScarlet monkeyflower (Erythranthe cardinalis).MethodsWe created experimental populations within and beyond the northern range edge and used integral projection models (IPM) to infer potential population growth trajectories. We also built two classes of ecological niche models (ENM), one using climatic predictors and the other using fine‐scale stream habitat variables, to estimate habitat suitability across the northern range edge. Finally, we tested whether higher ENM suitability scores predict greater demographic performance.ResultsConsistent with dispersal limitation, experimental populations beyond the range were projected to persist or spread in three of four sites (compared to two of four sites within the range) and stream habitat ENM projected abundant suitable stream microhabitat within the species’ thermal envelope beyond the range edge. In contrast, climatic ENM suggested decreasing habitat suitability and availability at the northern range edge. Unexpectedly, higher climatic ENM scores were associated with negative population growth rates, while higher stream habitat ENM scores were unrelated to population growth.Main conclusionsThe northern range edge falls short of the species niche limit and is instead limited by dispersal into suitable habitat. Dispersal limitation caused correlative niche models to underestimate the climatic niche and to poorly predict demographic performance in a short‐term field study. These results highlight key challenges to applying predictions from correlative ENM to understanding range and niche limits.

Corrigendum

Journal of Applied EcologyVolume 55, Issue 5 p. 2528-2528 CORRIGENDUMFree Access Corrigendum This article corrects the following: Foxes are now widespread in Tasmania: DNA detection defines the distribution of this rare but invasive carnivore Volume 55Issue 3Journal of Applied Ecology pages: 1564-1564 First Published online: May 15, 2017 Foxes are now widespread in Tasmania: DNA detection defines the distribution of this rare but invasive carnivore Stephen D. Sarre, Anna J. MacDonald, Candida Barclay, Glen R. Saunders, David S. L. Ramsey, Paul Lukacs, Volume 50Issue 2Journal of Applied Ecology pages: 459-468 First Published online: December 4, 2012 Editorial Notice Volume 55Issue 5Journal of Applied Ecology pages: 2527-2527 First Published online: August 12, 2018 First published: 12 August 2018 https://doi.org/10.1111/1365-2664.13245AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Sensitivity analysis of the fox habitat suitability model in Sarre et al. (2013) to omission of the Glen Esk (Cleveland) fox carcass. Stephen D. Sarre, Anna J. MacDonald, Candida Barclay, Glen R. Saunders, David S. L. Ramsey We fitted a fox habitat suitability model to the 65 locations of physical evidence of foxes using the maximum likelihood method of Royle, Chandler, Yackulic, and Nichols (2012) using the “maxlike” package in r. All the specific methodological details of the maximum likelihood method, data and predictor variables used in the modelling are given in Sarre, MacDonald, Barclay, Saunders, and Ramsey (2013). The initial model fitted here used the same set of predictor variables as was selected in the final model given in Table 1 of Sarre et al. (2013). We then refitted this model to the dataset but with the Glen Esk fox carcass removed (i.e. n = 64 locations). We then compared the predictions of the original and refitted model by comparing the differences (discrepancy) in the estimated habitat suitability for each of the 1-km2 habitat pixels covering Tasmania (i.e. n = 66,456 cells). The maximum discrepancy (difference) for any pixel in the predictions between the original model and the refitted model with the Glen Esk carcass removed was 0.12. However, the average discrepancy was 0.001 and the median discrepancy was 0. Examination of the cumulative distribution of the discrepancies revealed that 99.9% of the discrepancies were less than 0.043. Given the trivial nature of these discrepancies, the estimate of habitat suitability of foxes from the data with the omitted carcass is essentially unchanged from that given in Sarre et al. (2013). REFERENCES Royle, J. A., Chandler, R. B., Yackulic, C., & Nichols, J. D. (2012). Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions. Methods in Ecology and Evolution, 3, 545– 554. https://doi.org/10.1111/j.2041-210X.2011.00182.x Sarre, S. D., MacDonald, A. J., Barclay, C., Saunders, G. R., & Ramsey, D. S. L. (2013). Foxes are now widespread in Tasmania: DNA detection defines the distribution of this rare but invasive carnivore. Journal of Applied Ecology, 50, 459– 468. https://doi.org/10.1111/1365-2664.12011 Volume55, Issue5September 2018Pages 2528-2528 ReferencesRelatedInformation

Integrated spatially-explicit models predict pervasive risks to recolonizing wolves in Scandinavia from human-driven mortality

Human-driven wildlife mortality is caused by both indirect causes and direct persecution due to conflicts of interests. The wolf, a predator frequently at risk from human-wildlife conflict, is returning to areas where it was historically extirpated in Scandinavia (Sweden and Norway). The wolf is expanding via a management strategy that allows wolves to reproduce exclusively in a wolf breeding range (WBR) in the south-central region. We modelled wolf territory occurrence in the WBR and all of Scandinavia, accounting for biotic and anthropogenic variables, and we also modelled the occurrence of human-driven mortality (traffic collisions, culling and illegal killing). We integrated territory distribution and mortality models in a two-dimensional model estimating habitat suitability and mortality risk for wolves. Forest was the main variable driving territory occurrence, and mortality was a consequence of variables associated with traffic infrastructure, human population, prey densities, and wolf management levels. Only <0.1% of the WBR was not characterized by these risks. Our results confirm that human-related conflicts resulting in wolf mortality occur wherever the species is present, which leads to actions to control the population expansion. Considering the adaptability of wolves and the presence of potential suitable habitat in Scandinavia, their survival and expansion will be dependent on changes in public attitudes about illegal killing, and a review of policies and management actions. Our framework can be used to assist management of human-wildlife conflicts of recolonizing wolves elsewhere, or of other species at high risk from human-induced mortality.

Island biogeography and ecological modeling of the amblypygid Phrynus marginemaculatus in the Florida Keys archipelago.

AimThe biogeography of terrestrial organisms across the Florida Keys archipelago is poorly understood. We used population genetics and spatioecological modeling of the Amblypygi Phrynus marginemaculatus to understand the genetic structure and metapopulation dynamics of Keys populations that are otherwise isolated by human development and ocean.LocationThe Florida Keys archipelago and mainland Florida.MethodsWe sequenced a 1,238 bp fragment of mtDNA for 103 individuals of P. marginemaculatus from 13 sites in the Florida Keys and South Florida, binned into four regions. We used population genetic analyses to understand the population structure of the species throughout its US range. Furthermore, we used ecological modeling with climate, habitat, and human development data to develop habitat suitability estimates for the species.ResultsWe found clear genetic structure between localities. The Lower Keys, in particular, support populations separate from those in other regions studied. Ecological modeling and genetic analyses showed the highest habitat suitability and genetic isolation in the Lower Keys, but urban development across the species range has resulted in the loss of most historical habitat.Main conclusionsA mainland‐metapopulation model best fits P. marginemaculatus gene flow patterns in the Florida Keys and mainland. Ocean currents likely play a role in metapopulation dynamics and gene flow for terrestrial Keys species like P. marginemaculatus, and genetic patterns also matched patterns consistent with geologic history. Suitable habitat, however, is limited and under threat of human destruction. The few remaining pockets of the most suitable habitat tend to occur in parks and protected areas. We argue that conservation efforts for this species and others in the terrestrial Florida Keys would benefit from a deeper understanding of the population genetic structure and ecology of the archipelago.

Home Range Size and Resource Use of Breeding and Non-breeding White Storks Along a Land Use Gradient

Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.

How conspecific primates use their habitats: Surviving in an anthropogenically-disturbed forest in Central Kalimantan, Indonesia

Kalimantan (Indonesian Borneo) is a biodiversity hotspot at risk because of severe forest loss, degradation and burning events. Habitat loss and anthropogenic altering of forest structures pose a threat to forest-dependent taxa, including multiple endemic primate species. Conservation management schemes may be enhanced by evaluating how forest-dependent primates use their habitat for fulfilling life-history requirements, the role of natural forest structures thereon, and any corresponding impacts from anthropogenic disturbance and modification of forests. We investigated how forest-structure variables and landscape scale anthropogenic disturbance factors influenced the life-history behaviours (sleeping, ranging and feeding) of two endemic and sympatric primate species, Presbytis rubicunda (red langur) and Hylobates albibarbis (Bornean agile gibbon), in Sabangau tropical peat-swamp forest, Central Kalimantan. We aimed to identify key factors that influence habitat suitability for both species, and determine the influence of similar factors when selecting habitat for various activities such as sleeping, feeding and ranging. GPS locational data for each behaviour were analysed in conjunction with forest-structure parameters present (derived from LiDAR, ALOS-PALSAR), landscape-scale habitat related factors, and proximity to landscape-scale disturbance factors including burned areas. A Maximum Entropy (MaxEnt) algorithm was employed for estimating habitat suitability for the different activities of each species based on the afore-mentioned variables. By using a combination of forest sub-class, structure and disturbance variables within the MaxEnt framework, distribution maps of suitable langur and gibbon sleeping, ranging and feeding habitats were produced. Langurs and gibbons had limited overlaps in terms of feeding, ranging and sleeping habitats. In all cases, landscape-scale variables including those related to landscape scale anthropogenic disturbance had the highest percentage contribution for explaining habitat suitability in comparison to forest-structure variables such as canopy heights (derived using LiDAR data). Additionally, variables influencing habitat selection varied between species; while langur feeding, ranging and sleeping were all influenced by distance from burned forests, gibbon sleeping habitat selection was influenced by distance from the forest edge, and ranging and feeding habitat selection was most affected by distance from burned areas. The insights gained from this study may help inform conservation management of these species and guide forest management strategies accordingly to ensure habitat structure is maintained to facilitate activities by sympatric primate species.

Incorporating biophysical ecology into high‐resolution restoration targets: insect pollinator habitat suitability models

Species distribution models can be informative of the biodiversity impacts of changing environments at global, national, and regional scales, but are often constrained in their resolution to extents not relevant to individual, intensive ecological management programs. We constructed a high‐resolution topoclimatic model of spring and summer temperatures across a 152 km2 restoration area on the Swan Coastal Plain, Western Australia, and used it to project energetic expenditure and habitat suitability estimates for four major hymenopteran pollinators. For all species, the most heavily modified landscapes were the least suitable, but only for one species, Zapsilothynnus nigripes, was there evidence that the upper thermal tolerance threshold was exceeded broadly. However, at the higher environmental temperatures that we modeled, some species would need to forage up to 10 times their own body mass every hour to meet their energetic requirements. It seems unlikely that the nutritional requirements of most insect pollinators operating at these higher metabolic rates could be met in an impoverished restoration ecosystem, although resource availability remains to be quantified in these habitats. Hence, to increase the likelihood of restoration success by restoring insect pollination networks, nutritional resources may need to be increased during restoration. Accounting for the way that thermoenergetic requirements shape ecological interactions better positions management trajectories aimed at restoring and maintaining key insect pollinators in “novel” ecosystems.

Parameterization of an optical model to refine seagrass habitat requirements in an urbanized coastline

Accurate simulation of the underwater light climate is a requirement to understanding and predicting the ecological benefits from initiatives to manage land-derived inputs of nutrients and suspended solids to the coast. The goal of this work was to derive an empirical light model to be used in the water quality module of a coupled physical-biogeochemical model, developed to estimate habitat suitability for seagrasses in a metropolitan region (Adelaide, South Australia) affected by wastewater and stormwater discharges. Paired measurements of water quality and the vertical attenuation coefficient (Kd) obtained at six fixed sites between summer and winter were used in a multiple regression analysis to optimize local specific attenuation coefficients for coloured dissolved organic matter (CDOM) (2.623 cm m−1, measured as absorption at 254 nm), chlorophyll a (0.071 m2 mg−1), suspended solids (SS) < 63 μm (0.032 m2 g−1) and >63 μm (0.001 m2 g−1). The fitted relation explained 65% of the variability in Kd, with a standard error of 0.10 m-1. This error is small considering a mean Kd value of 0.35 m-1, varying between 0.12 and 0.89 m-1. Fine SS contributed on average 6 times more light attenuation (34%) than coarse SS (6%). CDOM was the second largest contributor to Kd (36%). The contribution of chlorophyll a to Kd (13%) was only marginally higher than the background imparted by seawater (12%). In shallow waters (3–5 m), Kd values were >0.4 m-1 and heavily influenced by sediment resuspension. In deeper waters (12–15 m), Kd values decreased and were dominated by CDOM. The light climate in the north of the study region was also heavily influenced by CDOM inputs, not only from point sources but also from mangroves and seagrass beds. This analysis suggests the control of fine SS as the most powerful management option to deter further nearshore seagrass losses in the region, and promote seagrass restoration.

Insights into the ecology, genetics and distribution of Lucanus elaphus Fabricius (Coleoptera: Lucanidae), North America's giant stag beetle

Abstract Little is known about the biology or conservation status of Lucanus elaphus Fabricius in North America despite well‐documented declines of a related species, Lucanus cervus (L.), in Europe. This study provides information critical to developing conservation plans for L. elaphus including the species’ larval substrate requirements, genetic data and range‐wide estimates of habitat suitability. In Mississippi floodplain forests, larval L. elaphus were recovered from a wide range of log sizes and rot types and were either found tunnelling within the wood or feeding beneath logs at the soil–wood interface. The species appears to require 1–2 years to complete development, exhibits a 1:1 sex ratio and is parasitised by Zelia vertebrata (Say) (Diptera: Tachinidae). Flight intercept traps placed at three heights at both the edge and interior of hardwood‐dominated forests in Georgia yielded six adult male L. elaphus, all of which were captured in traps placed at 15 m on the forest edge. Because L. elaphus larvae are morphologically indistinguishable from related species, DNA sequence data from the mitochondrial cytochrome oxidase I gene were generated to facilitate molecular identification. Genetic data revealed modest intra‐specific variation, with up to 1.3% sequence divergence among haplotypes sampled from the same forest. Based on assembled occurrence records, ecological niche models suggest that environmental conditions are suitable for L. elaphus across much of the southeastern United States, provided that adequate lowland forest cover and dead wood substrates are available.

Physical calculations of resistance to water loss improve predictions of species range models

AbstractSpecies ranges are constrained by the physiological tolerances of organisms to climatic conditions. By incorporating physiological constraints, species distribution models can identify how biotic and abiotic factors constrain a species' geographic range. Rates of water loss influence species distributions, but characterizing water loss for an individual requires complex calculations. Skin resistance to water loss (ri) is considered to be the most informative metric of water loss rates because it controls for experimental biases. However, calculating ri requires biophysical equations to solve for the resistance of the air that surrounds an organism, termed the boundary layer resistance (rb). Here, we compared theoretical and empirical methods for measuring skin resistance to water loss of a Plethodon salamander collected from nature. For the empirical methods, we measured rb of agar replicas at five body sizes, two temperatures, three vapor pressure deficits, and six flow rates using a flow‐through system. We also calculated rb using biophysical equations under the same experimental conditions. We then determined the ecological implications of incorporating skin and boundary layer resistance into a species range model that estimated potential activity time and energy balance throughout the geographic range of the study species. We found that empirical methods for calculating rb resulted in negative values of ri, whereas biophysical calculations produced meaningful values of ri. The species range model determined that ignoring realistic boundary layer and skin resistances reduced average estimates of energy balance by as much as 64% and potential activity time by 88% throughout the spatial extent of the model. We conclude that the use of agar replicas is an inadequate technique to characterize skin resistance to water loss, and incorporating boundary layer and skin resistances to water loss improves estimates of activity and energetics for mechanistic species distribution models. More importantly, our study suggests that incorporating the physical processes underlying rates of water loss could improve estimates of habitat suitability for many animals.

Plant Distribution Data Show Broader Climatic Limits than Expert-Based Climatic Tolerance Estimates.

BackgroundAlthough increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance.MethodsWe compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the ‘plant characteristics’ information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF) and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (ΔCN), and tested whether ΔCN was influenced by growth form or range size.ResultsClimate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001). The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ΔCN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ΔCN while grasses and trees had larger ΔCN for minimum precipitation.ConclusionOur results show that distribution data are consistently broader than USDA PLANTS experts’ knowledge and likely provide more robust estimates of climatic tolerance, especially for widespread forbs and grasses. These findings suggest that widely available expert-based climatic tolerance estimates underrepresent species’ fundamental niche and likely fail to capture the realized niche.

Predicting habitat suitability and geographic distribution of anchovy (Engraulis ringens) due to climate change in the coastal areas off Chile

The effects of climate change on ocean conditions will have impacts on fish stocks, primarily through physiological and behavioural effects, such as changes in growth, reproduction, mortality and distribution. Habitat and distribution predictions for marine fishery species under climate change scenarios are important for understanding the overall impacts of such global changes on the human society and on the ecosystem. In this study, we examine the impacts of climate change on anchovy fisheries off Chile using predicted changes in global models according to the National Centre for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) and IPCC high future CO2 emission scenario A2, habitat suitability index (HSI) models and satellite-based sea surface temperature (SST) and chlorophyll-a (Chl-a) estimates from high-resolution regional models for the simulation period 2015–2065. Predictions of SST from global climate models were regionalised using the Delta statistical downscaling technique. Predictions of chlorophyll-a were developed using historical Chl-a and SST (2003–2013) satellite data and applying a harmonic model. The results show an increase in SST of up to 2.5°C by 2055 in the north and central-south area for an A2 scenario. The habitat suitability index model was developed using historical (2001–2011) monthly fisheries and environmental data. The catch per unit effort (CPUE) was used as an abundance index in developing the HSI models and was calculated as the total catch (ton) by hold capacity (m3) in a 10′×10′ fishing grid square of anchovy, integrated over one month of fishing activity. The environmental data included the distance to coast (DC), thermal (SST) and food availability (Chl-a) conditions. The HSI modelling consists of estimating SI curves based on available evidence regarding the optimum range of environmental conditions for anchovy and estimating an integrated HSI using the Arithmetic Mean Model (AMM) method. The results of this work show that the model has produced robust estimates of habitat suitability and geographic distribution off Chile and has been especially effective in capturing the spatial and temporal variability of CPUE.Using IDRISI geographical information system (GIS), these HSI models simulated monthly changes in the habitat suitability (i.e., relative abundance) and distribution of anchovy off Chile forced by changes in the regionalised SST and Chl-a as projected by the NCAR model under the A2 emission scenario. The simulations predicted a moderate negative change of 17% and 13% for the north and central-south areas, respectively, in the habitat suitability (i.e., potential relative abundance) of anchovy by 2055.

Indicative response of Oxysternon festivum Linné (Coleoptera: Scarabaidae) to vegetation condition in the basin of the Orinoco river, Venezuela

A good indicator species should be easy to sample, identify and measure, and be informative about its ecological context. We analysed data from a nation-wide dung beetle survey in Venezuela in order to assess the indicative response of Oxysternon festivum (Coleoptera: Scarabaeinae) to vegetation and climatic condition in the Orinoco river basin. Our approach consisted of two steps: estimating habitat suitability (HS) from historical records and mean environmental conditions, and analysing four different properties measured during a nationwide survey (occurrence, total abundance, individual body size, and total biomass), in relationship with HS and current environmental covariates measured from remote sensors. O. festivum population status could not be completely explained by historical or current conditions alone, but rather by combinations of both. It was strongly associated with forest vegetation, but abundance, biomass and body size increased under harsher (hotter and drier) climatic conditions. Thus, O. festivum seems to be sensitive to changes in vegetation cover, but tolerant to certain levels of perturbance, where it probably replaces other, more sensitive species. Fully understanding the role of O. festivum requires the analysis of its relationships to other species. We strongly recommend the development of similar protocols for the analysis of other potential ecological indicator species, drawing information from historical and contemporary sources and exploiting the available statistical tools to reveal complex patterns. Given the high diversity of dung beetles, and the growing interest in this group, several candidates will probably be found in most tropical countries.

Spatially combining wood production and recreation with biodiversity conservation

Pine plantations established on former heathland are common throughout Western Europe and North America. Such areas can continue to support high biodiversity values of the former heathlands in the more open areas, while simultaneously delivering ecosystem services such as wood production and recreation in the forested areas. Spatially optimizing wood harvest and recreation without threatening the biodiversity values, however, is challenging. Demand for woody biomass is increasing but other pressures on biodiversity including climate change, habitat fragmentation and air pollution are intensifying too. Strategies to spatially optimize different ecosystem services with biodiversity conservation are still underexplored in the research literature. Here we explore optimization scenarios for advancing ecosystem stewardship in a pine plantation in Belgium. Point observations of seven key indicator species were used to estimate habitat suitability using generalized linear models. Based on the habitat suitability and species’ characteristics, the spatially-explicit conservation value of different forested and open patches was determined with the help of a spatially-explicit conservation planning tool. Recreational pressure was quantified by interviewing forest managers and with automated trail counters. The impact of wood production and recreation on the conservation of the indicator species was evaluated. We found trade-offs between biodiversity conservation and both wood production and recreation, but were able to present a final scenario that combines biodiversity conservation with a restricted impact on both services. This case study illustrates that innovative forest management planning can achieve better integration of the delivery of different forest ecosystem services such as wood production and recreation with biodiversity conservation.

Landsat ETM+ and SRTM Data Provide Near Real-Time Monitoring of Chimpanzee (Pan troglodytes) Habitats in Africa

All four chimpanzee sub-species populations are declining due to multiple factors including human-caused habitat loss. Effective conservation efforts are therefore needed to ensure their long-term survival. Habitat suitability models serve as useful tools for conservation planning by depicting relative environmental suitability in geographic space over time. Previous studies mapping chimpanzee habitat suitability have been limited to small regions or coarse spatial and temporal resolutions. Here, we used Random Forests regression to downscale a coarse resolution habitat suitability calibration dataset to estimate habitat suitability over the entire chimpanzee range at 30-m resolution. Our model predicted habitat suitability well with an r2 of 0.82 (±0.002) based on 50-fold cross validation where 75% of the data was used for model calibration and 25% for model testing; however, there was considerable variation in the predictive capability among the four sub-species modeled individually. We tested the influence of several variables derived from Landsat Enhanced Thematic Mapper Plus (ETM+) that included metrics of forest canopy and structure for four three-year time periods between 2000 and 2012. Elevation, Landsat ETM+ band 5 and Landsat derived canopy cover were the strongest predictors; highly suitable areas were associated with dense tree canopy cover for all but the Nigeria-Cameroon and Central Chimpanzee sub-species. Because the models were sensitive to such temporally based predictors, our results are the first to highlight the value of integrating continuously updated variables derived from satellite remote sensing into temporally dynamic habitat suitability models to support near real-time monitoring of habitat status and decision support systems.

Response to agriculture by a woodland species depends on cover type and behavioural state: insights from resident and dispersing Iberian lynx

Summary Conservation biology faces the challenge of ensuring species persistence in increasingly modified landscapes. Agriculture covers a large proportion of the Earth's surface, but the degree to which crop production is compatible with species use of the landscape is still uncertain, particularly for woodland carnivores with large territories. Here, we focus on the Iberian lynx Lynx pardinus, an emblematic endangered species that has coexisted for centuries with human‐modified Mediterranean mosaics, as a case study to unravel habitat and dispersal preferences in heterogeneous landscapes. We estimated species resource selection from ≈40 000 telemetry locations for 48 GPS‐collared individuals covering all the current Iberian lynx range, including more fragmented areas where the species was reintroduced from 2009. We differentiated GPS locations within home ranges (to estimate habitat suitability) and those corresponding to dispersal or exploratory movements (to estimate landscape permeability). We built mixed conditional logistic regression models with 12 land cover classes, terrain slope and roads as predictors. We found that lynx response to agriculture largely depends on the crop type and on the presence of natural vegetation remnants. Lynx largely avoided intensive cultivation areas such as irrigated arable lands when establishing home ranges, but frequently selected permanent crops (olive groves) and/or heterogeneous agricultural lands, which were used with smaller differences to the most preferred shrubland or forest covers than reported in previous studies. Such differences further narrowed down when lynx moved outside home ranges, with some agricultural covers being as permeable as shrublands for lynx dispersal. The species dispersal plasticity was also evidenced by a much weaker avoidance of roads and steep terrain when dispersing than when selecting territories. Synthesis and applications. We conclude that (i) the widespread consideration of all agricultural lands within a single (and usually regarded as unsuitable) class for the study and management of woodland or forest species is not supported and that (ii) the ability of woodland species to use fragmented and heterogeneous agricultural landscapes may have been underestimated, which may mislead conservation measures due to a priori assumptions that do not relate to the actual species responses to heterogeneous land covers. We suggest that Iberian lynx conservation and reintroduction may be successful in a wider set of more heterogeneous areas than previously thought, including mainly well‐conserved Mediterranean woodlands but also some extensive agricultural lands with permanent crops and natural vegetation remnants.

Acceleration Data Reveal Highly Individually Structured Energetic Landscapes in Free-Ranging Fishers (Pekania pennanti).

Investigating animal energy expenditure across space and time may provide more detailed insight into how animals interact with their environment. This insight should improve our understanding of how changes in the environment affect animal energy budgets and is particularly relevant for animals living near or within human altered environments where habitat change can occur rapidly. We modeled fisher (Pekania pennanti) energy expenditure within their home ranges and investigated the potential environmental and spatial drivers of the predicted spatial patterns. As a proxy for energy expenditure we used overall dynamic body acceleration (ODBA) that we quantified from tri-axial accelerometer data during the active phases of 12 individuals. We used a generalized additive model (GAM) to investigate the spatial distribution of ODBA by associating the acceleration data to the animals' GPS-recorded locations. We related the spatial patterns of ODBA to the utilization distributions and habitat suitability estimates across individuals. The ODBA of fishers appears highly structured in space and was related to individual utilization distribution and habitat suitability estimates. However, we were not able to predict ODBA using the environmental data we selected. Our results suggest an unexpected complexity in the space use of animals that was only captured partially by re-location data-based concepts of home range and habitat suitability. We suggest future studies recognize the limits of ODBA that arise from the fact that acceleration is often collected at much finer spatio-temporal scales than the environmental data and that ODBA lacks a behavioral correspondence. Overcoming these limits would improve the interpretation of energy expenditure in relation to the environment.

Accounting for the indirect area effect in stacked species distribution models to map species richness in a montane biodiversity hotspot

AbstractAimUnderstanding how species richness is distributed is a critical prerequisite to implement efficient conservation strategies in biodiversity hotspots. Stacked species distribution models (S‐SDMs) provide new opportunities to map species richness, but the accuracy of this method may decline with elevation. Here, we test whether variation in model accuracy arises from increasingly unpredictable environments or the decreasing availability of area with increasing elevation, which might affect the regional pool of species and, as a result, the local species richness (the indirect area effect).LocationThe New Caledonian biodiversity hotspot (south‐west Pacific Ocean).MethodsAn individual MAXENT model was built for 562 tree species by combining eight 100‐m resolution environmental variables with c. 10,000 occurrence records. For each species, a map was produced at a one‐hectare scale indicating the estimated habitat suitability. All models were then summed, and the resulting estimates were compared with richness measured in 11 independent one‐hectare inventories. To account for the indirect area effect, S‐SDM estimates were adjusted through the Arrhenius' equation linking the number of species hosted by a habitat with its surface area.ResultsThe S‐SDM predictions ranged from 95 to 251 species (mean = 153) while field inventories were lower, ranging from 39 to 131 species (mean = 90). Overall, the S‐SDM increasingly overestimated richness as elevation increased. Taking into account the indirect area effect de‐correlated residuals from elevation and induced a significant correlation between modelled and measured species richness.ConclusionThe decreasing accuracy of the S‐SDM with elevation was explained by the decreasing availability of habitat influencing regional diversity found in each elevational band. Despite remaining difficulties to predict species richness when addressing the indirect area effect, our findings represent a significant step forward towards improved S‐SDM designing.

Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

Species distribution models (SDMs) are extensively used to project habitat suitability of species in stream ecological studies. Owing to complex sources of uncertainty, such models may yield projections with varying degrees of uncertainty. To better understand projected spatial distributions and the variability between habitat suitability projections, this study uses five SDMs that are based on the outputs of a two-dimensional hydraulic model to project the suitability of habitats and to evaluate the degree of variability originating from both differing model types and the split-sample procedure. The habitat suitability index (HSI) of each species is based on two stream flow variables, including current velocity (V), water depth (D), as well as the heterogeneity of these flow conditions as quantified by the information entropy of V and D. The six SDM approaches used to project fish abundance, as represented by HSI, included two stochastic models: the generalized linear model (GLM) and the generalized additive model (GAM); as well as three machine learning models: the support vector machine (SVM), random forest (RF) and the artificial neural network (ANN), and an ensemble model (where the latter is the average of the preceding five models). The target species Sicyopterus japonicas was found to prefer habitats with high current velocities. The relationship between mesohabitat diversity and fish abundance was indicated by the trends in information entropy and weighted usable area (WUA) over the study area. This study proposes a method for quantifying habitat suitability, and for assessing the uncertainties in HSI and WUA that are introduced by the various SDMs and samples. This study also demonstrated both the merits of the ensemble modeling approach and the necessity of addressing model uncertainty.

Habitat suitability for chiru (Pantholops hodgsonii): Implications for conservation management across the Tibetan region of Chang Tang

Understanding how population density relates to habitat underlies basic ecological theory and is pertinent to conservation issues. Chiru (Pantholops hodgsonii) are an endangered steppe-dwelling ungulate endemic to the Tibetan plateau. To prepare effective conservation and management strategies for this species, we require detailed knowledge of the relationship between group size and habitat conditions. We surveyed the Chang Tang region of Tibet and used data collected along vehicular line transects to record the presence and group size of chiru. Using ecological niche factor analysis, we inferred the ecological requirements of chiru in relation to a large number of topographic, vegetation, and anthropogenic variables. We used these analyses to estimate habitat suitability models and describe their optimum range. Areas favored by chiru had moderate grazing by domestic animals, gentle slopes, and villages present only at lower altitudes. Chiru showed a high level of specialization regarding the presence of villages and gentle slopes, and were negatively associated with areas of those easily accessed by people. We suggest new management measures for the long-term conservation of chiru. Specifically, we focus on the rehabilitation of natural plains for grazing by chiru, recognizing that conservation of large groups may require special efforts. For smaller groups and solitary chiru, the large tracts of unsuitable or marginal areas may expose them to different threats that could pose greater challenges for conservation management. © 2015 The Wildlife Society.