The Use of Habitat Models in Conservation of Rare and Endangered Leafhopper Species (Hemiptera,Auchenorrhyncha)

For conservation of Auchenorrhyncha species, knowledge of their habitat requirements is essential. However, for most species there is no ‘quantitative’ knowledge that would allow e.g. spatially explicit predictions. Such predictions can be made by habitat models, which quantify the relationship between the environment and the occurrence of species. In two plot-based case studies – the endangered leafhopper Verdanus bensoni in mountainous grasslands and four endangered Auchenorrhyncha in urban brownfields – we used habitat models to quantify the habitat requirements of these five species and to exemplify their use for creating habitat suitability maps. In the first case study, the multivariate model showed that occurrence probabilities of the leafhopper V. bensoni increase with both decreasing nitrogen indicator values and decreasing tree cover. On urban brownfields, successional age was a driving factor for species’ occurrence. Site age largely determines a range of vegetation characteristics, which, in multivariate models, often replaced the variable age. Internal validation showed the robustness of all models. The models allow predictions of habitat quality under different management regimes (e.g. response to fertilization or abandonment for V. bensoni or to different turnover rates on brownfield sites). We discuss the application of habitat models in the conservation of Auchenorrhyncha, especially the use of habitat suitability maps.     

Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

Habitat predictors of genetic diversity for two sympatric wetland‐breeding amphibian species

Population genetic diversity is widely accepted as important to the conservation and management of wildlife. However, habitat features may differentially affect evolutionary processes that facilitate population genetic diversity among sympatric species. We measured genetic diversity for two pond‐breeding amphibian species (Dwarf salamanders, Eurycea quadridigitata; and Southern Leopard frogs, Lithobates sphenocephalus) to understand how habitat characteristics and spatial scale affect genetic diversity across a landscape. Samples were collected from wetlands on a longleaf pine reserve in Georgia. We genotyped microsatellite loci for both species to assess population structures and determine which habitat features were most closely associated with observed heterozygosity and rarefied allelic richness. Both species exhibited significant population genetic structure; however, structure in Southern Leopard frogs was driven primarily by one outlier site. Dwarf salamander allelic richness was greater at sites with less surrounding road area within 0.5 km and more wetland area within 1.0 and 2.5 km, and heterozygosity was greater at sites with more wetland area within 0.5 km. In contrast, neither measure of Southern Leopard frog genetic diversity was associated with any habitat features at any scale we evaluated. Genetic diversity in the Dwarf salamander was strongly associated with land cover variables up to 2.5 km away from breeding wetlands, and/or results suggest that minimizing roads in wetland buffers may be beneficial to the maintenance of population genetic diversity. This study suggests that patterns of genetic differentiation and genetic diversity have associations with different habitat features across different spatial scales for two syntopic pond‐breeding amphibian species.     

Toward community predictions: Multi‐scale modelling of mountain breeding birds' habitat suitability,landscape preferences,and environmental drivers

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including “Bio11” (Mean Temperature of Coldest Quarter), and “Bio 4” (Temperature Seasonality), then in the focal variables including “Forest”, “Orchard”, and “Agriculture area” as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.     

Non‐native salmonids affect amphibian occupancy at multiple spatial scales

Aim The introduction of non‐native species into aquatic environments has been linked with local extinctions and altered distributions of native species. We investigated the effect of non‐native salmonids on the occupancy of two native amphibians, the long‐toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), across three spatial scales: water bodies, small catchments and large catchments. Location Mountain lakes at ≥ 1500 m elevation were surveyed across the northern Rocky Mountains, USA. Methods We surveyed 2267 water bodies for amphibian occupancy (based on evidence of reproduction) and fish presence between 1986 and 2002 and modelled the probability of amphibian occupancy at each spatial scale in relation to habitat availability and quality and fish presence. Results After accounting for habitat features, we estimated that A. macrodactylum was 2.3 times more likely to breed in fishless water bodies than in water bodies with fish. Ambystoma macrodactylum also was more likely to occupy small catchments where none of the water bodies contained fish than in catchments where at least one water body contained fish. However, the probability of salamander occupancy in small catchments was also influenced by habitat availability (i.e. the number of water bodies within a catchment) and suitability of remaining fishless water bodies. We found no relationship between fish presence and salamander occupancy at the large‐catchment scale, probably because of increased habitat availability. In contrast to A. macrodactylum, we found no relationship between fish presence and R. luteiventris occupancy at any scale. Main conclusions Our results suggest that the negative effects of non‐native salmonids can extend beyond the boundaries of individual water bodies and increase A. macrodactylum extinction risk at landscape scales. We suspect that niche overlap between non‐native fish and A. macrodactylum at higher elevations in the northern Rocky Mountains may lead to extinction in catchments with limited suitable habitat.     

Near term climate projections for invasive species distributions

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas.     

Measures of giant panda habitat selection across multiple spatial scales for species conservation

Examining ecological processes across spatial scales is crucial as animals select and use resources at different scales. We carried out field surveys in September 2005, March–September 2006, and April 2007, and used ecological niche factor analysis to determine habitat preferences for the giant panda (Ailuropoda melanoleuca) across 4 spatial scales: daily movement, core range, home range, and seasonal elevational migration. We found that giant pandas prefer conifer forest and mixed forest at higher than average elevation (2,157 m) of study area in the 4 scale models. However, we also observed significant scale differences in habitat selection. The strength of habitat preference increased with scale for the 2 disturbed forests (sparse forest and fragmented forest), and decreased with scale for 0–30° gentle slope and south- and north-facing aspect. Furthermore, habitat suitability patterns were scale-dependent. These findings highlight the need to determine species–environment associations across multiple scales for habitat management and species conservation. © 2012 The Wildlife Society.     

Habitat suitability models to make conservation decisions based on areas of high species richness and endemism

Biodiversity positively relates with the provisioning of ecosystem services and preserving areas with elevated diversity of highly-functional species could help to ensure human well-being. Most studies addressed to make these decisions use maps relying on species occurrences, where sites containing several species are proposed as priority conservation areas. These maps, however, may underestimate species richness because of the incompleteness of occurrence data. To improve this methodology, we propose using habitat suitability models to estimate the potential distribution of species from occurrence data, and later shaping richness maps by overlapping these predicted distribution ranges. We tested this proposal with Mexican oaks because they provide several ecosystem services and habitat suitability models of species were calibrated with MaxEnt. We used linear regressions to compare the outputs of these predictive maps with those of maps based on species occurrences only and, for both mapping methods, we assessed how much surface of sites with elevated richness and endemism of oaks is currently included within nature reserves. Both mapping methods indicated that oak species are concentrated in mountain regions of Mexico, but predictive maps based on habitat suitability models indicated higher oak richness and endemism that maps based on species occurrences only. Our results also indicated that nature reserves cover a small fraction of areas harboring elevated richness and endemism of oaks. These results suggest that estimating richness across extensive geographic regions using habitat suitability models quickly provides accurate information to make conservation decisions for highly-functional species groups.     

Habitat suitability models for the sand lizard Liolaemus wiegmannii based on landscape characteristics in temperate coastal dunes in Argentina

The knowledge of environmental variables associated with the species occurrence allows the recognition of sites which fulfil ecological requirements eventually used for conservation of species. The coastal dunes of Argentina are inhabited by sand lizards. Anthropic activities have severely degraded this ecosystem, affecting the habitat structure at a large scale. In this context, the effects of landscape characteristics on the sand lizard's (Liolaemus wiegmannii, Liolaemidae) presence were analysed to build habitat suitability maps along the coastal dunes of Argentina. A thematic map of study area was obtained from supervised classification of satellite images to identify landscape characteristics. Surveys were conducted during the lizard activity season, and landscape variables were measured in two spatial units. All information collected was compiled into a Geographic Information System. The relationship between the presence of lizards and landscape variables was evaluated by Generalized Linear Models. The predictions of these models were transferred by using Geographic Information System to habitat suitability maps. Almost all individuals (80%) were observed in semi‐fixed dunes. The analysis of landscape metrics in the two spatial extents showed complementary results. The habitat suitability models suggest that: (i) heterogeneous landscapes composed by disaggregated patches of semi‐fixed dunes and low or null percentages of active dunes distant from the coastline are the preferred environments, and (ii) human modifications such as urbanizations and forestation of dunes, have a negative impact on species occurrence. Suitable habitats were almost absent in those sectors of coastal dunes with highest level of urbanization, whereas they were distributed almost continuously in those areas without human disturbances.     

Geographic range determinants of two commercially important marine molluscs

Aim We modelled the spatial abundance patterns of two abalone species (Haliotis rubra Donovan 1808 and H. laevigata Leach 1814) inhabiting inshore rocky reefs to better understand the importance of current sea surface temperature (SST) (among other predictors) and, ultimately, the effect of future climate change, on marine molluscs. Location Southern Australia. Methods We used an ensemble species distribution modelling approach that combined likelihood‐based generalized linear models and boosted regression trees. For each modelling technique, a two‐step procedure was used to predict: (1) the current probability of presence, followed by (2) current abundance conditional on presence. The resulting models were validated using an independent, spatially explicit dataset of abalone abundance patterns in Victoria. Results For both species, the presence of reef was the main driver of abalone occurrence, while SST was the main driver of spatial abundance patterns. Predictive maps at c. 1‐km resolution showed maximal abundance on shallow coastal reefs characterized by mild winter SSTs for both species. Main conclusions Sea surface temperature was a major driver of abundance patterns for both abalone species, and the resulting ensemble models were used to build fine‐resolution predictive range maps (c. 1 km) that incorporate measures of habitat suitability and quality in support of resource management. By integrating this output with structured spatial population models, a more robust understanding of the potential impacts of threatening human processes such as climate change can be established.     

Landscape heterogeneity metrics as indicators of bird diversity: Determining the optimal spatial scales in different landscapes

Species distribution models are often used to study the biodiversity of ecosystems. The modelling process uses a number of parameters to predict others, such as the occurrence of determinate species, population size, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead to changes in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatial scales when it comes to undertaking a GIS analysis.We explored the goodness of fit of several models using the metrics of landscape heterogeneity and altitude as predictors of bird diversity in different landscapes and spatial scales. Two variables were used to describe biodiversity: bird richness and trophic level diversity, both of which were obtained from a breeding bird survey by means of point counts. The relationships between biodiversity and landscape metrics were compared using multiple linear regressions. All of the analyses were repeated for 14 different spatial scales and for cultivated, forest and grassland environments to determine the optimal spatial scale for each landscape typology.Our results revealed that the relationships between species’ richness and landscape heterogeneity using 1:10,000 land cover maps were strongest when working on a spatial scale up to a radius of 125–250 m around the sampled point (circa 4.9–19.6 ha). Furthermore, the correlation between measures of landscape heterogeneity and bird diversity was greater in grasslands than in cultivated or forested areas. The multi-spatial scale approach is useful for (a) assessing the accuracy of surrogates of bird diversity in different landscapes and (b) optimizing spatial model procedures for biodiversity mapping, mainly over extensive areas.     

Spatial ecology and conservation of the microendemic ovenbird Cipo Cinclodes (Cinclodes espinhacensis) from the Brazilian highlands

Birds in the genus Cinclodes are habitat specialists, with most restricted to the highlands of South America. The recently described Cipo Cinclodes (C. espinhacensis) is isolated in the southern Espinhaço Range of Brazil and is considered Endangered in Brazil and Near Threatened by the IUCN, but as a subspecies of Long‐tailed Cinclodes (C. pabsti). We examined the population and spatial ecology of Cipo Cinclodes at two geographic scales to improve our understanding of their basic biology and conservation status. We monitored 30 birds at Serra do Breu and found relatively large home ranges (mean = 9.3 ha), a density of paired adults of 0.09/ha, a male‐skewed adult sex ratio (males/total adults = 0.57) due to territories occupied by unpaired males, and long‐term site fidelity. Cipo Cinclodes used all habitat types available in our study area, including rocky outcrops, grasslands, and riparian areas, but habitat selection analyses revealed the importance of riparian areas for foraging and rocky outcrops for nesting. At the species distribution scale, we compiled known and novel recorded occurrence points and used them to calculate the extent of occurrence (EOO) and the area of occupancy (AOO). We used a Maxent species distribution model to generate a binary map to estimate upper limits for EOO (EOO around the model predicted area) and AOO (comprised by the model predicted area within the EOO). We obtained 41 locations, resulting in an EOO of 890.7 km² (up to 1748.7 km²) and an AOO of 100 km² (up to 327.5 km²). The global population is estimated to be between 880 and 2882 birds, which is concerning because small populations are at risk of extinction due to demographic stochasticity, genetic drift, and the interaction of these factors. As such, our results support the designation of Cipo Cinclodes as Endangered on the Brazilian red list.     

Habitat suitability modelling for species at risk is sensitive to algorithm and scale: A case study of Blanding's turtle,Emydoidea blandingii,in Ontario,Canada

Species distribution modelling (SDM) can help conservation by providing information on the ecological requirements of species at risk. We developed habitat suitability models at multiple spatial scales for a threatened freshwater turtle, Emydoidea blandingii, in Ontario as a case study. We also explored the effect of background data selection and modelling algorithm selection on habitat suitability predictions. We used sighting records, high-resolution land cover data (25 m), and two SDM techniques: boosted regression trees; and maximum entropy modelling. The area under the receiver characteristic operating curve (AUC) for habitat suitability models tested on independent data ranged from 0.878 to 0.912 when using random background and from 0.727 to 0.741 with target-group background. E. blandingii habitat suitability was best predicted by air temperature, wetland area, open water area, road density, and cropland area. Habitat suitability increased with increasing air temperature and wetland area, and decreased with increasing cropland area. Low road density and open water increased habitat suitability, while high levels of either variable decreased habitat suitability. Robust habitat suitability maps for species at risk require using a multi-scale and multi-algorithm approach. If well used, SDM can offer insight on the habitat requirements of species at risk and help guide the development of management plans. Our results suggest that E. blandingii management plans should promote the protection of terrestrial habitat surrounding residential wetlands, halt the building of roads within and adjacent to currently occupied habitat, and identify movement corridors for isolated populations.     

Species‐habitat relationships and ecological correlates of butterfly abundance in a transformed tropical landscape

Tropical butterfly conservation strategies often focus on total and/or common species richness to assess the conservation value of a patch or habitat. However, such a strategy overlooks the unique dynamics of rare species. We evaluated the species‐habitat relationships of 209 common, intermediate, and rare butterfly species (including morphospecies) across four habitat types (mature, degraded, or fragmented forest, and urban parks) and two patch sizes (<400 ha, ≥400 ha) in Singapore. Common species richness was consistent across habitat types. Intermediate species richness declined by more than 50 percent in urban parks (relative to all forest habitats), and rare species richness was reduced by 50 percent in degraded and fragmented forest and by 90 percent in urban parks (relative to mature forest). Large patches had comparable overall richness to small patches, but they supported more rare species and three times as many habitat‐restricted species over a similar area. Importantly, a number of rare species were confined to single small patches. Mixed‐effects regression models were constructed to identify habitat and ecological/life history variables associated with butterfly abundance. These models revealed that species with greater habitat specialization, rare larval host plants, few larval host plant genera, and narrow global geographic ranges were more likely to be rare species. Overall, these results demonstrate that the richness of habitat‐restricted and rare species do not follow the same spatial distribution patterns as common species. Therefore, while conserving mature forests is key, effective butterfly conservation in a transformed landscape should take into account rare and habitat‐restricted species.     

Habitat suitability models for the conservation of thermophilic grasshoppers and bush crickets—simple or complex?

One goal of conservation biology is the assessment of effects of land use change on species distribution. One approach for identifying the factors, which determine habitat suitability for a species are statistical habitat distribution models. These models are quantitative and can be used for predictions in management scenarios. However, they often have one major shortcoming, which is their complexity. This means that they need several, often costly-to-determine parameters for predictions of species occurrence. We first used habitat suitability models to investigate and determine habitat preferences of three different Orthoptera species. Second, we compared the predictive powers of simple habitat suitability models considering only the ‘habitat type’ as predictor with more complex models taking different habitat factors into account. We found that the habitat type is the most reliable and robust factor, which determines the occurrence of the species studied. Thus, analyses of habitat suitability can easily be carried out on the basis of existing vegetation maps for the conservation of the three species under study. Our results can serve as a basis for the estimation of spatio-temporal distribution and survival probabilities of the species studied and might also be valuable for other species living in dry grasslands.     

Development and field validation of a regional,management‐scale habitat model: A koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional‐scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently‐collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2‐km spatial filter and by modeling separately two subregions separated by the 500‐m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground‐truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground‐truth sites. Similarly, a site habitat quality index at ground‐truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site‐based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field‐validated models of similar resolution would assist in guiding management of conservation‐dependent species.     

Patterns of differential introgression in a salamander hybrid zone: inferences from genetic data and ecological niche modelling

Hybrid zones have yielded considerable insight into many evolutionary processes, including speciation and the maintenance of species boundaries. Presented here are analyses from a hybrid zone that occurs among three salamanders –Plethodon jordani, Plethodon metcalfi and Plethodon teyahalee– from the southern Appalachian Mountains. Using a novel statistical approach for analysis of non‐clinal, multispecies hybrid zones, we examined spatial patterns of variation at four markers: single‐nucleotide polymorphisms (SNPs) located in the mtDNA ND2 gene and the nuclear DNA ILF3 gene, and the morphological markers of red cheek pigmentation and white flecks. Concordance of the ILF3 marker and both morphological markers across four transects is observed. In three of the four transects, however, the pattern of mtDNA is discordant from all other markers, with a higher representation of P. metcalfi mtDNA in the northern and lower elevation localities than is expected given the ILF3 marker and morphology. To explore whether climate plays a role in the position of the hybrid zone, we created ecological niche models for P. jordani and P. metcalfi. Modelling results suggest that hybrid zone position is not determined by steep gradients in climatic suitability for either species. Instead, the hybrid zone lies in a climatically homogenous region that is broadly suitable for both P. jordani and P. metcalfi. We discuss various selective (natural selection associated with climate) and behavioural processes (sex‐biased dispersal, asymmetric reproductive isolation) that might explain the discordance in the extent to which mtDNA and nuclear DNA and colour‐pattern traits have moved across this hybrid zone.     

Habitat continuity and stepping‐stone oceanographic distances explain population genetic connectivity of the brown alga Cystoseira amentacea

Effective predictive and management approaches for species occurring in a metapopulation structure require good understanding of interpopulation connectivity. In this study, we ask whether population genetic structure of marine species with fragmented distributions can be predicted by stepping‐stone oceanographic transport and habitat continuity, using as model an ecosystem‐structuring brown alga, Cystoseira amentacea var. stricta. To answer this question, we analysed the genetic structure and estimated the connectivity of populations along discontinuous rocky habitat patches in southern Italy, using microsatellite markers at multiple scales. In addition, we modelled the effect of rocky habitat continuity and ocean circulation on gene flow by simulating Lagrangian particle dispersal based on ocean surface currents allowing multigenerational stepping‐stone dynamics. Populations were highly differentiated, at scales from few metres up to thousands of kilometres. The best possible model fit to explain the genetic results combined current direction, rocky habitat extension and distance along the coast among rocky sites. We conclude that a combination of variable suitable habitat and oceanographic transport is a useful predictor of genetic structure. This relationship provides insight into the mechanisms of dispersal and the role of life‐history traits. Our results highlight the importance of spatially explicit modelling of stepping‐stone dynamics and oceanographic directional transport coupled with habitat suitability, to better describe and predict marine population structure and differentiation. This study also suggests the appropriate spatial scales for the conservation, restoration and management of species that are increasingly affected by habitat modifications.