Estimate Habitat Suitability Research Articles

The potential for species distribution models to distinguish source populations from sinks.

While species distribution models (SDM) are frequently used to predict species occurrences to help inform conservation management, there is limited evidence evaluating whether habitat suitability can reliably predict intrinsic growth rates or distinguish source populations from sinks. Filling this knowledge gap is critical for conservation science, as applications of SDMs for management purposes ultimately depend on these typically unobserved population or metapopulation dynamics. Using linear regression, we associated previously published population level estimates of intrinsic growth and abundance derived from a Bayesian analysis of mark-recapture data for 17 bird species found in the contiguous United States with SDM habitat suitability estimates fitted here to opportunistic data for these same species. We then used the area under the ROC curve (AUC) to measure how well SDMs can distinguish populations categorized as sources and sinks. We built SDMs using two different approaches, boosted regression trees (BRT) and generalized linear models (GLM), and compared their source/sink predictive performance. Each SDM was built with presence points obtained from eBird (a web-available database) and 10 environmental variables previously selected to model intrinsic growth rates and abundance for these species. We show that SDMs built with opportunistic data are poor predictors of species demography in general; both BRT and GLM explained very little spatial variation of intrinsic growth rate and population abundance (median R2 across 17 species was close to 0.1 for both SDM methods). SDMs, however, estimated higher suitability for source populations as compared to sinks. Out of 13 species which had both source and sink populations, both BRT and GLM had AUC values greater than 0.7 for 7 species when discriminating between sources and sinks. Habitat suitability have the potential to be a useful measure to indicate a population's ability to sustain itself as a source population; however more research on a diverse set of taxa is essential to fully explore this potential. This interpretation of habitat suitability can be particularly useful for conservation practice, and identification of explicit cases of when and how SDMs fail to match population demography can be informative for advancing ecological theory.

Uncertainty in consensus predictions of plant species' vulnerability to climate change

AbstractAimVariation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection.LocationCalifornia Floristic Province (California, US portion).MethodsWe modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species‐level habitat change to species' attributes.ResultsAssuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts.Main ConclusionsOur results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end‐of‐century time periods and within species' currently occupied habitats (no dispersal).

Spatial distribution models for the four commercial tuna in the sea of maritime continent using multi-sensor remote sensing and maximum entropy

The dynamic of marine environmental parameters affects the distribution of commercial tuna in the sea of the maritime continent. Hence, the objectives of this study are to develop spatial distribution models for the four main tuna species in the Maritime continent's sea with reasonable accuracy, identify their correlation with marine environmental parameters, and investigate areas of interaction between those tuna species. The study develops the distribution models for albacore (Thunnus alalunga), bigeye (Thunnus obesus), yellowfin (Thunnus albacares), and skipjack (Katsuwonus pelamis) tuna species, utilizing multi-sensor satellite remote sensing and maximum entropy. The results show models have good performance, focusing on environmental factors such as sea surface temperature (SST), chlorophyll-a (CHL), and sea surface height anomalies (SSHA), combined with eddy kinetic energy (EKE). Seasonal variations in potential tuna habitats are revealed, emphasizing the influence of those marine environmental conditions. From December to May, the four commercial tuna species were distributed in conditions characterized by SST of 26–31.5 °C, CHL levels of 0–3 mg/l, SSHA of −0.3 to 0.2 m, and EKE of 0–1 m2/s2, while from June to November, they experienced SST of 23–31 °C, CHL levels of 0–4 mg/l, SSHA of −0.5 to 0.3 m, and EKE of 0–1.1 m2/s2. The spatial persistence of the four tuna species emerged mainly around the south sea of Java, with skipjack being the most common species found in the sea of the maritime continent. With sufficient and evenly distributed tuna presence records, the results indicate the potential for extrapolation beyond the training data to estimate habitat suitability for the four commercial tuna distributions. The results also suggest potential competition between tuna species sharing ecological niches and highlight possible overlapping areas where different tuna species interact with the same fishing gear.

Greater Glasgow pond amphibian surveys 2022

In 2019, Clyde Amphibian and Reptile Group (CARG) decided to organise a spring 2020 common frogspawn (Rana temporaria) survey of the Greater Glasgow area, Scotland. The COVID-19 lockdown postponed this project until 2022. The 2022 survey area was spread across four council districts: Glasgow City, South Lanarkshire, Renfrewshire and East Renfrewshire. The primary aim of the surveys was to collect records of amphibian breeding throughout the Greater Glasgow Area, with secondary aims of: (1) revisiting the ponds to see if the ponds supported the spawn through to tadpole and froglet stages; (2) assessing the condition of the ponds for amphibians; (3) identifying areas for habitat enhancement work; and (4) collecting data on breeding common toads (Bufo bufo) and newts (Lissotriton, Ichthyosaura and Triturus spp.). A total of 45 volunteers participated in the surveys. Surveys were completed between March and May 2022, with a primary focus between March and April in order to capture frog spawning data. Surveyors were asked to record amphibian population data, and habitat data in order to estimate Habitat Suitability Indices. In total 162 ponds were surveyed, with evidence of breeding common frogs found in 66.1% of ponds with 11,478 frogspawn clumps counted on the first set of surveys. Only 12.2% of ponds were found to contain common toads, and small newts (Lissotriton spp.) were identified in only 7.4% of ponds. In relation to the quality of breeding habitat, 24.5% of ponds were assessed as drying out annually, which significantly reduces the suitability of these ponds for breeding. This figure is predicted to increase with anthropogenic climate change reducing the number of breeding ponds available to amphibians in the absence of intervention. Furthermore, the majority of the ponds surveyed were assessed as offering poor or below average suitability for great crested newts (Triturus cristatus) and nearly half of the ponds surveyed were found to have poor or bad water quality, which can increase stress levels for larval amphibians and may adversely affect mortality levels. However, as the analysis of water quality was subjective, these findings should be treated with caution.

Empirical estimation of habitat suitability for rare plant restoration in an era of ongoing climatic shifts

Accurate estimates of current and future habitat suitability are needed for species that may require assistance in tracking a shifting climate. Standard species distribution models (SDMs) based on occurrence data are the most common approach for evaluating climatic suitability, but these may suffer from inaccuracies stemming from disequilibrium dynamics and/or an inability to identify suitable climate regions that have no analogues within the current range. An alternative approach is to test performance with experimental introductions, and model suitability from the empirical results. We used this method with the Haleakalā silversword (Argyroxiphium sandwicense subsp. macrocephalum), using a network of out-plant plots across the top of Haleakalā volcano, Hawaiʻi. Over a ~ 5-year period, survival varied strongly across this network and was effectively explained by a simple model including mean rainfall and air temperature. We then applied this model to estimate current climatic suitability for restoration or translocation activities, to define trends in suitability over the past three decades, and to project future suitability through 2051. This empirical approach indicated that much of the current range has low suitability for long-term successful restoration, but also identified areas of high climatic suitability in a region where plants do not currently occur. These patterns contrast strongly with projections obtained with a standard SDM, which predicted continued suitability throughout the current range. Under continued climatic shifts, these results caution against the common SDM presumption of equilibrium between species’ distributions and their environment, even for long-established native species.

Modelling elephant corridors over two decades reveals opportunities for conserving connectivity across a large protected area network.

Protected area (PA) connectivity is pivotal for the persistence of wide-ranging wildlife species, but is challenged by habitat loss and fragmentation. We analyzed habitat suitability and connectivity for the African elephant (Loxodonta africana) across PAs in south-western Tanzania in 2000, 2010, and 2019. We quantified land-use changes through remote sensing data; estimated habitat suitability through aerial survey data, remotely sensed variables and ensemble species distribution models; modelled least-cost corridors; identified the relative importance of each corridor for the connectivity of the PA network and potential bottlenecks over time through circuit theory; and validated corridors through local ecological knowledge and ground wildlife surveys. From 2000 to 2019, cropland increased from 7% to 13% in the region, with an average expansion of 634 km2 per year. Distance from cropland influenced elephant distribution models the most. Despite cropland expansion, the locations of the modelled elephant corridors (n = 10) remained similar throughout the survey period. Based on local ecological knowledge, nine of the modelled corridors were active, whereas one modelled corridor had been inactive since the 1970s. Based on circuit theory, we prioritize three corridors for PA connectivity. Key indicators of corridor quality varied over time, whereas elephant movement through some corridors appears to have become costlier over time. Our results suggest that, over the past two decades, functional connectivity across the surveyed landscape has largely persisted. Beyond providing crucial information for spatial prioritization of conservation actions, our approach highlights the importance of modeling functional connectivity over time and verifying corridor models with ground-truthed data.

Ensemble species distribution modeling of Culex tarsalis (Diptera: Culicidae) in the continental United States.

West Nile virus (WNV) is the primary mosquito-borne disease in the United States and has had case reports every year since its introduction in 1999. As such, it is critical that we characterize the distribution of WNV vectors. Estimates of Culex tarsalis Coquillett species distribution, a major WNV vector, are scarce. We used ensemble distribution modeling to estimate habitat suitability for this species across the contiguous United States by consolidating presence data from four publicly available mosquito trapping data servers. The central plains region and much of the western US were estimated to have high habitat suitability. We identified multiple metrics of temperature and precipitation to be important in predicting the occurrence of Cx. tarsalis in a given geographic area. Furthermore, we observed habitat suitability for Cx. tarsalis to be significantly higher in areas with a high incidence of West Nile neuroinvasive disease compared to areas with low WN disease incidence, suggesting that Cx. tarsalis is present in regions with a high incidence of disease.

Combining community science and MaxEnt modeling to estimate Wild Turkey ( Meleagris gallopavo ) winter abundance and distribution

Understanding the distribution and abundance of species is a fundamental aspect of conservation biology. Species distribution models aim to predict distributions based on species observations and ecologically relevant information. To understand the contemporary distribution of Wild Turkeys (<em>Meleagris gallopavo</em>) in Ontario, we curated and collated Wild Turkey flock observations from eBird and iNaturalist submitted during winter 2018. We combined these with environmental predictors to build distribution models using MaxEnt and evaluated model fit using 10-fold cross validation. We also estimated total population size for this species under different modeling scenarios. The potential presence of unknown spatial bias in community science datasets is a complex problem often requiring context-specific statistical solutions. Data cleaning, sometimes referred to as thinning, filtering, or culling, is often proposed to manage this bias. As such, we tested the effect of data cleaning on model outputs and on subsequent analyses. We evaluated all models using area under the curve (AUC). We found building density to be the most important environmental variable followed by winter severity. We validated our habitat suitability estimates using fine-scale GPS data and found that data cleaning had no effect on habitat suitability estimates inside available Wild Turkey habitat or inside core-use areas, except at one site in 2012 (t = -2.2, P = 0.04, df = 14). Use of community collected data offers a cost-efficient and collaborative method to obtain data for species distribution modeling and management. We discuss implications for Wild Turkey management and present potential contemporary distribution maps for this species.

Reduced complexity models for regional aquatic habitat suitability assessment

AbstractGeneralizable methods that identify suitable aquatic habitat across large river basins and regions are needed to inform resource management. Habitat suitability models intersect environmental variables to predict species occurrence, but are often data intensive and thus are typically developed at small spatial scales. This study estimated mean monthly aquatic habitat suitability throughout Utah (USA) for Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) and Bluehead Sucker (Catostomus discobolus) with publicly available, geospatial datasets. We evaluated 15 habitat suitability models using unique combinations of percent of mean annual discharge, velocity, gradient, and stream temperature. Environmental variables were validated with observed conditions and species presence observations to verify habitat suitability estimates. Stream temperature, gradient, and discharge best predicted Bonneville Cutthroat Trout presence, and gradient and discharge best predicted Bluehead Sucker presence. Simple aquatic habitat suitability models outperformed models that used only streamflow to estimate habitat for both species, and are useful for conservation planning and water resources decision‐making. This modeling approach could enable resource managers to prioritize stream restoration across vast regions within their management domain, and is potentially compatible with water management modeling to improve ecological objectives in management models.

Comparing Methods for Estimating Habitat Suitability

Habitat suitability (HS) describes the ability of the habitat to support living organisms. There are several approaches to estimate habitat suitability. These approaches are specific to a species or habitat or estimate general HS broadly across multiple species or habitats. The objectives of the study were to compare the approaches for estimating HS and to provide guidelines for choosing an appropriate HS method for conservation. Three HS estimation methods were used. Method 1 scores the suitability based on the naturality of the habitat. Method 2 uses the average of HS values found in the literature. Method 3 uses the species richness as an indicator for HS. The methods were applied to a case study in the Choctawhatchee River Watershed. GIS applications were used to model the suitability of the watershed. The advantages and disadvantages of the HS methods were then summarized. The multiple HS maps created using the three methods display the suitability of the watershed. The highest suitability occurred in the southern parts of the region. Finally, a decision support tool was developed to help determine which approach to select based on the available data and research goals.

Quantifying the risk of plastic ingestion by ichthyofauna in the Balearic Islands (western Mediterranean Sea).

This study investigates the risk plastic debris ingestion poses to coastal marine taxa in the Balearic Islands in the western Mediterranean Sea. Here, we use species observations and environmental data to model habitat maps for 42 species of fish. For each species, we then match estimates of habitat suitability against the spatial distribution of plastic debris to quantify plastic exposure, which we further combine with species-wise ingestion rates to map the risk of plastic ingestion. The results indicate that the risk of plastic ingestion is particularly high in the north-west and south-east regions and the risks varied strongly between species, with those at higher trophic levels being the most vulnerable overall. Extending this work to other coastal regions within the Mediterranean Sea and beyond will allow managers and policymakers to target the most appropriate areas and types of interventions for mitigating plastic pollution on coastal diversity in the marine environment.

A novel unsupervised method for assessing mesoscale river habitat structure and suitability from 2D hydraulic models in gravel‐bed rivers

AbstractApplication of mesoscale habitat models in gravel‐bed rivers is increasingly common for a variety of purposes, from ecological flow design, impact assessment and conservation programmes. Integration with 2D hydraulic modelling offers the potential for broader applicability of mesoscale habitat models, extending applications to larger streams and nonwadable flow conditions, when on‐the‐ground and in‐stream surveys are challenging or even prohibitive. In this work, a novel fully unsupervised procedure that allows the segmentation of the river channel area at a given flow condition at a scale that is consistent with the mesoscale is presented. Further, it defines an objective methodology to choose segmentation parameters and thus an optimal segmentation, based on intrinsic spatial properties of the resulting regions. Segmentation parameters are objectively selected by minimising a Global Score, which is based on three metrics representing intrasegment homogeneity, intersegment heterogeneity and an optimal range of segment numbers based on an empirically defined mesoscale. Applications of the model are tested on two reaches of the multithread Mareta and meandering Aurino Rivers in South Tyrol (NE, Italy). Model outcomes are compared with ground mesohabitat surveys, and habitat suitability is then assessed for three fish species (marble trout, grayling and European bullhead). A high level of agreement is found when comparing model‐ and survey‐based habitat suitability estimates, with an overall value of . The proposed approach shows potential for application of the mesohabitat concept for large gravel‐bed rivers and nonwadable flow conditions. By allowing habitat estimates at flow ranges that could not be surveyed in‐stream, the approach facilitates applicability of mesoscale habitat models to nonwadable conditions and large streams. The workflow is river‐independent and fully unsupervised, as it does not require calibration or subjective choices of segmentation parameters.Significance statementQuantifying suitable habitat for riverine fauna is increasingly used for ecological flows assessment, with the use of mesoscale habitat modelling approaches becoming more common in the past few decades. Existing mesoscale habitat modelling approaches often rely on field surveys, which, however, become prohibitive at nonwadable flow conditions and in large streams. Here we develop and test against field data a fully unsupervised approach able to extract mesohabitats and their hydraulic characteristics from the outputs of 2D hydraulic models. Compared with existing approaches, our approach allows an automated segmentation of the wetted reach into mesoscale units through the implementation of an unsupervised optimality step in which optimal segmentation parameters are defined, and a final mesohabitat mosaic is selected. The methodology makes it easier to expand the applicability of mesoscale habitat modelling to a broader range of river sizes and conditions.

Glacial vicariance and oceanic circulation shape population structure of the coastal legume Derris trifoliata in the Indo-West Pacific.

The phylogeography of coastal plant species is shaped by contemporary and historical biogeographic processes. In this study, we aim to decipher the phylogeography of Derris trifoliata, a woody legume of relatively recent origin and wide distribution, in coastal areas in the Indo-West Pacific (IWP) region. Genetic diversity and population structure were assessed by analyzing six nuclear and three chloroplast DNA sequences from 30 populations across the species' range. Phylogeography was inferred by estimating gene flow, divergence time, historical population size changes, and historical habitat suitability using paleoclimatic niche modeling. High genetic diversity was observed at the species level. The populations of three oceanic regions included in this study (i.e., Indian Ocean, South China Sea, and Pacific Ocean) formed distinct clades and likely diverged during the late Pleistocene. Potential barriers to gene flow were identified, including the Sunda and Sahul shelves, geographic distance, and current patterns of oceanic circulation. Analysis of changes in population size supported the bottleneck model, which was strengthened by estimates of habitat suitability across paleoclimatic conditions. The once widespread distribution of D. trifoliata was fragmented by changes in climatic suitability and biogeographic barriers that arose following sea-level changes during the Pleistocene. In addition, contemporary patterns of oceanic circulation and geographic distance between populations appear to maintain genetic differentiation across its distribution in the IWP.

Scale-dependent assumptions influence habitat suitability estimates for the American lobster (Homarus americanus): Implications for a changing Gulf of Maine

Bioclimate envelope models were evaluated for possible spatial nonstationarity for American lobster (Homarus americanus) in the Gulf of Maine (GOM). Five environmental variables were considered, including bottom water temperature, bottom water salinity, distance offshore, sediment grain size, and latitude. Three models accounting for varying degrees of spatial nonstationarity were developed and evaluated. Spatial scales developed in these models were determined by the patterns of the GOM coastal currents and the associated affects these currents have on the GOM oceanography. This study suggests that incorporating spatial nonstationarity into habitat suitability modeling may lead to improved models. Forecast plots for the 2028−2055 period revealed that traditional modeling techniques applied at coarse spatial scales estimated higher suitability of habitat for juvenile lobsters than models at smaller spatial scales. For adult lobsters, coarse spatial model yielded higher suitability in both coastal waters in western GOM and farther offshore waters in eastern GOM, and generally estimated lower suitability in coastal eastern GOM waters and some offshore western GOM waters, compared to finer-scale spatial models. These results demonstrate how HSI estimates would vary based on the choice of spatial scales and its consequences. This information could benefit future stakeholders to prepare and adapt at more localized scales for changes that may occur in a region that is susceptible to climate change.

Habitat suitability map of Ixodes ricinus tick in France using multi-criteria analysis.

The tick Ixodes ricinus is widely distributed across Europe and is responsible for the transmission of several pathogens to humans and animals. In this study, we used a knowledge-based method to map variations in habitat suitability for I. ricinus ticks throughout continental France and Corsica. The multi-criteria decision analysis (MCDA) integrated four major biotic and abiotic factors known to influence tick populations: climate, land cover, altitude and the density of wild ungulates. For each factor, habitat suitability index (HSI) values were attributed to different locations based on knowledge regarding its impact on tick populations. For the MCDA, two methods of factor combination were tested, additive and multiplicative, both which were evaluated at the spatial scales of departments and local municipalities. The resulting habitat suitability maps (resolution=100x100 m) revealed that conditions are suitable for I. ricinus over most of France and Corsica. Particularly suitable habitats were located in central, north-eastern and south-western France, while less-suitable habitats were found in the Mediterranean and mountainous regions. To validate the approach, the HSI scores were compared to field data of I. ricinus nymph abundance. Regardless of scale, the correlation between abundance indicator and HSI score was stronger for the additive than for the multiplicative approach. Overall, this study demonstrates the value of MCDA for estimating habitat suitability maps for I. ricinus abundance, which could be especially useful in highlighting areas of the tick's distribution where preventive measures should be prioritised.

HyDiaD: A hybrid species distribution model combining dispersal, multi-habitat suitability, and population dynamics for diadromous species under climate change scenarios

Diadromous species are particularly vulnerable to climate change because they utilize both marine and freshwater habitat to complete their life cycles. Dispersal plays an important role in restraining the distribution of plant and animal species, and is a key mechanism to allow diadromous species to adapt to changes in habitat suitability, but it is often not included in species distribution models that explore population trends under climate scenarios. The objective of this study was to develop a model to estimate potential shifts in diadromous populations in the Atlantic area of Europe under two climate change scenarios and multiple global climate models. To address the question of range-shift responses, a hybrid approach for diadromous species distribution (HyDiaD) was developed that incorporated two components: i) statistical static models of habitat suitability describing the influence of environmental factors on species occurrence, and ii) biological processes relevant for the distribution of the species, such as population demography and dispersal dynamics. Hybrid models were developed using a novel approach that incorporated both population and between-catchment dispersal dynamics specific to each species. Occupancy data for diadromous species in a subset of Atlantic Area catchments were first validated by regional experts, and boosted regression trees were applied to estimate habitat suitability within each catchment based on historical physical and climatic environmental predictors from the continental and marine domains. Habitat suitability was then used in a population dynamics model that incorporated between-catchment dispersal and local population growth. Results for different-sized catchments were compared using time series of spawner density and saturation rate, which estimated how much of the available habitat was being utilized. Many of the species-specific values used in HyDiaD were estimated through a survey of diadromous species experts, and group consensus was reached by calculating weighted averages. The HyDiaD model was applied to two shad species (Alosa alosa and A. fallax) to explore population trends projected annually from 1951 to 2100. Projected trends indicated that under XXIst century climate scenarios, habitat suitability is expected to increase for A. fallax, but decrease for A. alosa. Projected trends also indicated an increase in the rate of annual variability for A. alosa, particularly in the southern part of its range. Future studies can utilize the HyDiaD model to explore distribution trends for other diadromous species under climate change scenarios.

Major Expansion of Marine Forests in a Warmer Arctic

Accelerating warming and associated loss of sea ice are expected to promote the expansion of coastal marine forests (macrophytes) along the massive Arctic coastlines. Yet, this region has received much less attention compared to other global oceans. The available future projections of Arctic macrophytes are still limited to few species and regions, and mostly focused at lower latitude ranges, thus precluding well-informed IPCC impact assessments, conservation and management. Here we aim to quantify potential distributional changes of Arctic intertidal and subtidal brown macroalgae and eelgrass by the year 2100, relative to present. We estimate habitat suitability by means of species distribution modeling, considering changes in seawater temperature, salinity, nutrients and sea ice cover under two greenhouse gas emission scenarios, one consistent with the Paris Agreement (RCP 2.6) and the other representing limited mitigation strategies (RCP 8.5). As data on substrate conditions do not exist, the models were restricted to the depth range supporting Arctic macrophytes (down to 5 m for eelgrass and 30 m for brown macroalgae). Models projected major expansions of Arctic macrophytes between 69,940 and 123,360 km2, depending on the climate scenario, with polar distribution limits shifting northwards by up to 1.5 latitude degrees at 21.81 km per decade. Such expansions in response to changing climate will likely elicit major changes in biodiversity and ecosystem functions in the future Arctic. Expansions are, however, less intense than those already realized over the past century, indicating an overall slowing down despite accelerated warming as habitats become increasingly occupied.

Copepod habitat suitability estimates vary among oxygen metrics in Chesapeake Bay

AbstractSeasonal deoxygenation in coastal and estuarine systems leads to decreased available habitat for many planktonic organisms. However, the volume of available habitat can be defined in different ways, depending on the oxygen metrics employed. Here, we used monitoring data for water quality to estimate the seasonal and inter-annual variability in habitat for the copepod Acartia tonsa in Chesapeake Bay, defined using three different oxygen metrics: a concentration-based (2 mg l−1) definition of hypoxia, and two partial pressure-based definitions corresponding to limiting oxygen demand (Pcrit), and the minimum requirement for respiration (Pleth). We examined spatial and temporal trends in the oxygen habitat, and compared habitat estimates to zooplankton abundance and distribution and in relation to hydrologically wet, average, and dry years. Pcrit predicted the largest volume of unsuitable deoxygenated habitat over space and time, and dry conditions were associated with a decreased extent of deoxygenated habitat compared to average and wet conditions. No clear relationship between copepod abundance and habitat availability was observed, but the position of peak abundance of A. tonsa correlated to the extent of deoxygenated habitat using Pcrit. Species-specific metrics to describe oxygen habitat may be more useful in understanding the non-lethal impacts of deoxygenation.

Distribution Modelling and Habitat Requirements of Micronycteris sanborni (Phyllostomidae) across the South America Dry Diagonal

Micronycteris sanborni is an insectivorous bat known from dry phytogeographic domains in South America, although its distribution range is not yet well known. Here, we modelled the distribution of this species based on seven bioclimatic and vegetation predictors associated with its occurrence, using 26 sites where the species was recorded in the Caatinga (16), Cerrado (7), Chiquitano Dry Forest (2) and Pantanal (1). We used four different algorithms to build an ensemble distribution model, to estimate habitat suitability throughout its geographic occurrence and the area of habitat available inside protected areas. Our models showed excellent performance and highlighted the main importance of four environmental variables (other mixed trees, deciduous broadleaf trees, evergreen broadleaf trees, and precipitation of driest quarter), which accounted for more than 80% of the species presence probability. The distribution model indicated the potential occurrence of M. sanborni consistently across the dry diagonal of South America, but adequate habitat areas covered mainly the Caatinga and the northeast of Cerrado rather than the southwest, where suitable habitats were scattered and discontinuous. Less than 10% of the total habitat predicted for M. sanborni corresponded to protected areas. Our results support that M. sanborni mostly depends on woody and less dry environments across the South America dry diagonal, which raises concerns about its vulnerability due to high deforestation in the southwest and because severe dryness is forecast for the coming decades in the Brazilian northeast.

Accounting for geographic variation in species-habitat associations during habitat suitability modeling.

Range-wide species conservation efforts are facilitated by spatially explicit estimates of habitat suitability. However, species-environment relationships often vary geographically and models assuming geographically constant relationships may result in misleading inferences. We present the first range-wide habitat suitability model (HSM) for the federally threatened eastern indigo snake (Drymarchon couperi) as a case study illustrating an approach to account for known latitudinal variation in habitat associations. Specifically, we modeled habitat suitability using interactive relationships between minimum winter temperature and several a priori environmental covariates and compared our results to those from models assuming geographically constant relationships. We found that multi-scale models including interactive effects with winter temperature outperformed single-scale models and models not including interactive effects with winter temperature. Our top-ranked model had suitable range-wide predictive performance and identified numerous large (i.e., ≥1000 ha) potential habitat patches throughout the indigo snake range. Predictive performance was greatest in southern Georgia and northern Florida likely reflecting more restrictive indigo snake habitat associations in these regions. This study illustrates how modeling interactive effects between temperature and environmental covariates can improve the performance of HSMs across geographically varying environmental gradients.