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.     

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.     

Evaluating tree wētā (Orthoptera: Anostostomatidae: <Emphasis Type="Italic">Hemideina</Emphasis> species) as bioindicators for New Zealand national biodiversity monitoring

Indicator taxa are increasingly being used to evaluate the natural environment because they provide both quantified and simplified information about complex phenomena and because they result in huge cost savings compared with monitoring entire biotas. In this paper, we examine the suitability of an iconic New Zealand invertebrate, the tree wētā (Orthoptera: Anostostomatidae: Hemideina species), as a bioindicator for invertebrates under a national biodiversity monitoring scheme in New Zealand. Tree wētā are common and widespread in New Zealand, comprising a distinctive component of the native invertebrate fauna, being large-bodied (up to 40 mm in length), relatively long-lived, flightless, and nocturnal. Arboreal tree wētā species are commonly monitored in conservation areas containing scrub or forest, particularly after mammal control, because they can be easily monitored using artificial roosts without harming them and they are readily identified by field workers. We evaluated whether data supported the use of tree wētā as a range of bioindicators for such monitoring and conclude that the arboreal species are good indicators for monitoring the effects of controlling the abundance of insectivorous mammals and that they are likely to be reliable population indicators of taxa sensitive to mammalian predation pressure, especially by rodents. However, it is unlikely that arboreal tree wētā are useful population indicators of habitat change (e.g. degradation and fragmentation) as they commonly survive in exotic vegetation and urban gardens throughout New Zealand. Although poorly studied for indicator value, tree wētā may not be good biodiversity indicators although there are insufficient data to establish this. We recommend further research be undertaken to develop standardised methods for monitoring so that conservation managers and researchers produce results that are consistent and comparable across different locations.     

Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data

While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12 × 11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10 000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species’ presence for both fine and coarse grain habitat suitability and distribution modelling.     

Modeling habitat suitability for chimpanzees (<Emphasis Type="Italic">Pan troglodytes verus</Emphasis>) in the Greater Nimba Landscape,Guinea, West Africa

Tropical forests and the biodiversity within them are rapidly declining in the face of increasing human populations. Resource management and conservation of endangered species requires an understanding of how species perceive and respond to their environments. Species distribution modeling (SDM) is an appropriate tool for identifying conservation areas of concern and importance. In this study, SDM was used to identify areas of suitable chimpanzee (Pan troglodytes verus) habitat within the Greater Nimba Landscape, Guinea, West Africa. This location was ideal for investigating the effects of landscape structure on habitat suitability due to the topographic variation of the landscape and the Critically Endangered status of the Western chimpanzee. Additionally, this is the only mountainous, long-term chimpanzee study site and little is known about the effects of topography on chimpanzee behavior. Suitable habitat was predicted based on the location of direct and indirect signs of chimpanzee presence and the spatial distribution of 12 biophysical variables within the study area. Model performance was assessed by examining the area under the curve. The overall predictive performance of the model was 0.721. The variables most influencing habitat suitability were the normalized difference vegetation index (37.8%), elevation (27.3%), hierarchical slope position (11.5%), surface brightness (6.6%), and distance to rivers (5.4%). The final model highlighted the isolation and fragmentation of chimpanzee habitat within the Greater Nimba Landscape. Understanding the factors influencing chimpanzee habitat suitability, specifically the biophysical variables considered in this study, will greatly contribute to conservation efforts by providing quantitative habitat information and improving survey efficiency.     

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.     

Distribution of medium- to large-sized African mammals based on habitat suitability models

The knowledge of the areas inhabited by a species within its distribution range and the connections among patches are critical pieces of information for successful conservation actions. The internal structure of the extent of occurrence (EO) of a species is almost always unknown, even for “well-known” flagship species. We developed a methodology to infer the area of occupancy (AO) within the EO of a species using the limited available data. We present here the results of a three years project funded by European Union to develop high-resolution models of habitat suitability for 281 medium- to large-sized African mammals across the whole continent. The existing literature was reviewed and all data on the geographic distribution and environmental preferences of the selected species were collected. For each species, these data were then expressed in terms of key variables available as GIS layers at a resolution of 1 km² over the entire African continent. The AO of each species was obtained merging the information on the ecological needs of the species and the values of ecological variables over the region identified as EO. The habitat suitability models were evaluated through direct field work in four countries (Morocco, Cameroon, Uganda, Botswana) chosen as representatives of the environmental and species diversity of Africa. More than 81% of models had positive true skill statistics (TSS) values, indicating models performing better than random. Rigorous modeling procedures supported by ad-hoc field evaluation allowed the production of high-resolution habitat suitability models useful for conservation applications.     

基于MaxEnt模型的北极村国家级自然保护区紫貂栖息地适宜性评价

在人类支配的景观中,生境退化已经导致多个物种种群数量不断减少,分布范围不断缩减。紫貂（Martes zibellina）为国家Ⅰ级重点保护动物,种群数量稀少,开展栖息地适宜性研究工作对制定科学的栖息地保护计划至关重要。于2021年1月-2022年8月在黑龙江省北极村国家级自然保护区采用样线调查法、足迹链跟踪、远红外相机监测综合收集到紫貂和猎物（雪兔）活动点信息。利用最大熵（MaxEnt）栖息地建模分析方法,首次在多个分辨率尺度背景下对紫貂种群的栖息地适宜性进行评价,研究结果表明：（1）利用ArcGIS 10.4重采样后在6个分辨率尺度（30m、60m、120m、240m、480m、960m）进行栖息地建模分析,基于主要栖息地变量因子对模型的贡献率及稳定性影响,并综合考虑研究区域面积,最终选定30m分辨率尺度作为紫貂栖息地最佳分析建模尺度,在30m分辨率尺度栖息地预测模型的曲线下面积（AUC）值为0.881;（2）研究发现猎物资源、植被类型和地形变量是影响紫貂栖息地适宜性的主要变量因子：雪兔出现概率较高、距草地与河流较近、海拔约400-600m、距常绿针叶林1.5km、距落叶针叶林约200m、坡向为50-250°的区域为紫貂的适宜栖息地;（3）栖息地适宜性分析表明,北极村国家级自然保护区紫貂适宜栖息地和次适宜栖息地面积共计23.66km²,约占保护区的17.2%,主要集中在保护区中部,而东部和西北部区域,栖息地破碎化较严重。基于模型结果与野外调查,提出了三条建议：（1）应严格控制人为活动,避免因人类干扰造成不适宜栖息地面积的持续扩大;（2）建立生态廊道促进保护区西部与中部紫貂种群进行个体交流,降低紫貂种群局部区域灭绝概率;（3）对东部地区破碎化的栖息地进行修复,扩大东部适宜栖息地面积,使破碎化的栖息地连接为整体。为分布于我国最北端的紫貂种群恢复创造条件,这对于构建该地区相对稳定的生物多样性保护空间格局有着重要意义。     

Predicting global habitat suitability for stony corals on seamounts

Aim Globally, species distribution patterns in the deep sea are poorly resolved, with spatial coverage being sparse for most taxa and true absence data missing. Increasing human impacts on deep‐sea ecosystems mean that reaching a better understanding of such patterns is becoming more urgent. Cold‐water stony corals (Order Scleractinia) form structurally complex habitats (dense thickets or reefs) that can support a diversity of other associated fauna. Despite their widely accepted ecological importance, records of scleractinian corals on seamounts are patchy and simply not available for most of the global ocean. The objective of this paper is to model the global distribution of suitable habitat for stony corals on seamounts. Location Seamounts worldwide. Methods We compiled a database containing all accessible records of scleractinian corals on seamounts. Two modelling approaches developed for presence‐only data were used to predict global habitat suitability for seamount scleractinians: maximum entropy modelling (Maxent) and environmental niche factor analysis (ENFA). We generated habitat‐suitability maps and used a cross‐validation process with a threshold‐independent metric to evaluate the performance of the models. Results Both models performed well in cross‐validation, although the Maxent method consistently outperformed ENFA. Highly suitable habitat for seamount stony corals was predicted to occur at most modelled depths in the North Atlantic, and in a circumglobal strip in the Southern Hemisphere between 20° and 50° S and shallower than around 1500 m. Seamount summits in most other regions appeared much less likely to provide suitable habitat, except for small near‐surface patches. The patterns of habitat suitability largely reflect current biogeographical knowledge. Environmental variables positively associated with high predicted habitat suitability included the aragonite saturation state, and oxygen saturation and concentration. By contrast, low levels of dissolved inorganic carbon, nitrate, phosphate and silicate were associated with high predicted suitability. High correlation among variables made assessing individual drivers difficult. Main conclusions Our models predict environmental conditions likely to play a role in determining large‐scale scleractinian coral distributions on seamounts, and provide a baseline scenario on a global scale. These results present a first‐order hypothesis that can be tested by further sampling. Given the high vulnerability of cold‐water corals to human impacts, such predictions are crucial tools in developing worldwide conservation and management strategies for seamount ecosystems.     

From topography to hydrology—The modifiable area unit problem impacts freshwater species distribution models

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors—a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90‐m digital‐elevation model by using the GRASS‐GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km². We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land‐use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1–93.2 and 0.61–0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can have consistently high evaluation scores while mapped predictions differ significantly and are highly contingent on the underlying subcatchment size. We encourage building freshwater SDMs across multiple catchment sizes, to assess model variability and uncertainties in model outcomes emerging from the MAUP.     

Diet selectivity in a terrestrial forest invertebrate,the Auckland tree wētā, across three habitat zones

Insects are important but overlooked components of forest ecosystems in New Zealand. For many insect species, information on foraging patterns and trophic relationships is lacking. We examined diet composition and selectivity in a large‐bodied insect, the Auckland tree wētā Hemideina thoracica, in three habitat zones in a lowland New Zealand forest. We asked whether H. thoracica selectively forage from available plant food sources, and whether these choices were lipid‐rich compared to nonpreferred available plants. We also identified the proportion of invertebrates in their frass as a proxy for omnivory. From reconnaissance plot sampling, together with fecal fragment analysis, we report that more than 93% of individual tree wētā had eaten invertebrates before capture. Additionally, wētā in the highest elevation hillslope habitat zone consumed significantly fewer species of plants on average than wētā on the low‐elevation terrace habitat. Upper hillslope wētā also had the highest average number of invertebrate fragments in their frass, significantly more than wētā in the low‐elevation terrace habitat zone. Wētā showed high variability in the consumption of fruit and seeds across all habitat zones. Generally, we did not observe diet differences between the sexes (although it appears that male wētā in the mid‐hillslope habitat ate fruits and seeds more voraciously than females), suggesting that the sexes have similar niche breadths and display similar degrees of omnivorous behavior. Extraction of leaf lipids demonstrated a range of lipid content values in available plants, and Ivlev's Electivity Index indicated that plant species which demonstrated high electivity tended to have higher concentrations of lipids in their leaves. Our findings indicate that H. thoracica forage omnivorously and selectively, and hence play multiple roles in native ecosystems and food webs.     

Assessing congruence of opportunistic records and systematic surveys for predicting Hispaniolan mammal species distributions

Comparative assessment of the relative information content of different independent spatial data types is necessary to evaluate whether they provide congruent biogeographic signals for predicting species ranges. Opportunistic occurrence records and systematically collected survey data are available from the Dominican Republic for Hispaniola’s surviving endemic non‐volant mammals, the Hispaniolan solenodon (Solenodon paradoxus) and Hispaniolan hutia (Plagiodontia aedium); opportunistic records (archaeological, historical and recent) exist from across the entire country, and systematic survey data have been collected from seven protected areas. Species distribution models were developed in maxent for solenodons and hutias using both data types, with species habitat suitability and potential country‐level distribution predicted using seven biotic and abiotic environmental variables. Three different models were produced and compared for each species: (a) opportunistic model, with starting model incorporating abiotic‐only predictors; (b) total survey model, with starting model incorporating biotic and abiotic predictors; and (c) reduced survey model, with starting model incorporating abiotic‐only predictors to allow further comparison with the opportunistic model. All models predict suitable environmental conditions for both solenodons and hutias across a broadly congruent, relatively large area of the Dominican Republic, providing a spatial baseline of conservation‐priority landscapes that might support native mammals. Correlation between total and reduced survey models is high for both species, indicating the substantial explanatory power of abiotic variables for predicting Hispaniolan mammal distributions. However, correlation between survey models and opportunistic models is only moderately positive. Species distribution models derived from different data types can provide different predictions about habitat suitability and conservation‐priority landscapes for threatened species, likely reflecting incompleteness and bias in spatial sampling associated with both data types. Models derived using both opportunistic and systematic data must therefore be applied critically and cautiously.     

Unravelling the response of diurnal raptors to land use change in a highly dynamic landscape in northwestern Spain: an approach based on satellite earth observation data

Land use and land cover change (LULCC) is one of the main components of current anthropogenic global change. Unravelling the ecological response of biodiversity to the combined effect of land use change and other stressors is essential for effective conservation. For this purpose, we used co-inertia analysis to combine LULCC analysis of earth observation satellite data-derived maps and raptor data obtained from road censuses conducted in 2001 and 2014 at sampling unit level (10 km² spatial resolution), in northwestern Spain (province of Ourense, c. 7281 km²). In addition, habitat suitability models were also computed using ten widely used single-modelling techniques providing an ensemble of predictions at landscape level (four spatial resolutions: 500-m, 1-km, 2-km and 5-km radius around each sighting) for each year and raptor species to analyse the habitat suitability changes in the whole study area through three niche overlap indices. The models revealed an increase in occurrence and habitat suitability of forest raptor species coupled with a strong decrease in species associated with open habitats, mainly heaths and shrub formations. Open-habitat specialist species were negatively affected by the concomitant effects of intensive forest management and a long-lasting trend of rural abandonment coupled with an unusually high frequency of wildfires. Sustainable forest management and agricultural practices should be encouraged by both public and private sectors, through, e.g. policies related to European funds for rural and regional development (FEDER and FEADER programs) to effectively protect threatened habitats and species, and to comply with current environmental legislation. The combined use of satellite imagery and ground-level biodiversity data proved to be a cost-effective and systematic method for monitoring priority habitats and their species in highly dynamic landscapes.     

Multi-criteria Decision Analysis to Model <Emphasis Type="Italic">Ixodes ricinus</Emphasis> Habitat Suitability

Tick-borne diseases present a major threat to both human and livestock health throughout Europe. The risk of infection is directly related to the presence of its vector. Thereby it is important to know their distribution, which is strongly associated with environmental factors: the presence and availability of a suitable habitat, of a suitable climate and of hosts. The present study models the habitat suitability for Ixodes ricinus in Ireland, where data on tick distribution are scarce. Tick habitat suitability was estimated at a coarse scale (10 km) with a multi-criteria decision analysis (MCDA) method according to four different scenarios (depending on the variables used and on the weights granted to each of them). The western part of Ireland and the Wicklow mountains in the East were estimated to be the most suitable areas for I. ricinus in the island. There was a good level of agreement between results from the MCDA and recorded tick presence. The different scenarios did not affect the spatial outputs substantially. The current study suggests that tick habitat suitability can be mapped accurately at a coarse scale in a data-scarce context using knowledge-based methods. It can serve as a guideline for future countrywide sampling that would help to determine local risk of tick presence and refining knowledge on tick habitat suitability in Ireland.     

Relationships between survival and habitat suitability of semi‐aquatic mammals

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche‐based species distribution models (SDMs) and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi‐aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30‐m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent‐predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability‐fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic SDMs incorporating local abundance and demographic rates are needed.     

Environmental change,shifting distributions,and habitat conservation plans: A case study of the California gnatcatcher

Many species have already experienced distributional shifts due to changing environmental conditions, and analyzing past shifts can help us to understand the influence of environmental stressors on a species as well as to analyze the effectiveness of conservation strategies. We aimed to (1) quantify regional habitat associations of the California gnatcatcher (Polioptila californica ); (2) describe changes in environmental variables and gnatcatcher distributions through time; (3) identify environmental drivers associated with habitat suitability changes; and (4) relate habitat suitability changes through time to habitat conservation plans. Southern California's Western Riverside County (WRC ), an approximately 4,675 km² conservation planning area. We assessed environmental correlates of distributional shifts of the federally threatened California gnatcatcher (hereafter, gnatcatcher) using partitioned Mahalanobis D ² niche modeling for three time periods: 1980–1997, 1998–2003, and 2004–2012, corresponding to distinct periods in habitat conservation planning. Highly suitable gnatcatcher habitat was consistently warmer and drier and occurred at a lower elevation than less suitable habitat and consistently had more CSS , less agriculture, and less chaparral. However, its relationship to development changed among periods, mainly due to the rapid change in this variable. Likewise, other aspects of highly suitable habitat changed among time periods, which became cooler and higher in elevation. The gnatcatcher lost 11.7% and 40.6% of highly suitable habitat within WRC between 1980–1997 to 1998–2003, and 1998–2003 to 2004–2012, respectively. Unprotected landscapes lost relatively more suitable habitat (?64.3%) than protected landscapes (30.5%). Over the past four decades, suitable habitat loss within WRC , especially between the second and third time periods, was associated with temperature‐related factors coupled with landscape development across coastal sage scrub habitat; however, development appears to be driving change more rapidly than climate change. Our study demonstrates the importance of providing protected lands for potential suitable habitat in future scenarios.     

Predicting the in-between: Present and future habitat suitability of an intertidal euryhaline fish

New World mangrove trees are foundation species, and their range is predicted to expand northward with climate change. Foundation species are commonly prioritized for conservation, with the goal of preserving the entire community that depends on them. However, no studies have explicitly investigated whether mangrove-dependent species' ranges will track the northward expansion of New World mangrove forests. We use the mangrove rivulus fish, Kryptolebias marmoratus, to investigate shifts in habitat suitability in response to various climate change scenarios (Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5). Niche models for coastal species focus on traditional climatic variables (e.g., precipitation, temperature) even though coastal habitats also are directly influenced by marine variables (e.g., sea surface salinity). We employ a novel data integration method that combines marine and climatic variables, and that accounts for model selection uncertainty using model averaging to provide robust estimates of habitat suitability. Contrary to expectation, suitability of rivulus habitat is predicted to increase in the south and decrease or remain unchanged in the north across all climate change scenarios. Thus, rivulus might experience range contraction, not expansion. Habitat became more suitable with increased salinity of the saltiest month and precipitation of the driest quarter. In laboratory settings, rivulus have higher survival, reproductive success, and growth rates in low salinities. This discrepancy suggests that some combination of the responses of rivulus and its competitors to environmental change will restrict rivulus to habitats that laboratory experiments consider suboptimal. Our models suggest that focusing conservation decisions on foundation species could overestimate habitat availability and resilience of affiliated communities while simultaneously underestimating species declines and extinction risks.