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.     

Defining critical habitat for plant species with poor occurrence knowledge and identification of critical habitat networks

We applied spatial distribution and reserve selection modeling to identify critical habitat network for 50 critically endangered plant species of Uzbekistan. We created maps of relative habitat suitability, converted them into maps of species critical habitat, and the latter served as input to the spatial conservation prioritization program Zonation. Although all studied species were extremely rare, the extent of their predicted critical habitat ranged from 2.6 to 15,508 km² and did not correlate with the number of occurrence records. It appears that the extent of the threatened species predicted suitable area is an indicator of whether the species rarity is inherent due to vary narrow ecological niche or caused solely by anthropogenic activity. This has important conservation implications. Imperiled species from the first category are less amenable (if at all) to such conservation actions as trans- or relocation (i.e. there is no alternative to protecting the last remaining populations). Species from the second group can potentially grow in many more locations than they currently occupy, and therefore, for these species, translocation can be the most appropriate strategy when their last remaining locations are degraded or can not be protected for whatever reason. Based on results of nature reserve design that utilized SDM-predicted maps for 50 imperiled species, we recommend adding new areas to the existing network of protected areas to cover critical habitats of highly threatened plant species. The highest priority for adding have the territories harboring critical habitat of disproportionally high number of imperiled species, and we found that they all are concentrated in the eastern part of Uzbekistan.

     

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.     

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.     

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.     

An integrated method to create habitat suitability models for fragmented landscapes

Given the pervasive influence of human induced habitat fragmentation in ecological processes, landscape models are a welcome advance. The development of GIS software has allowed a greater use of these models and of analyses of the relationship between species and habitat variables. Habitat suitability models are thus theoretical concepts that can be used for planning in fragmented landscapes and habitat conservation. The most commonly used models are based on single species and on the assignment of suitability values for some environmental variables. Generally the cartographic basis for modeling suitability are thematic maps produced by a Boolean logic. In this paper we propose a model based on a set of focal species and on maps produced by a fuzzy classification method. Focal species, selected by an expert-based approach, provide a practical way of extending the scope of habitat suitability models to the conservation of biodiversity at landscape scale. The utilisation of a classification method that applies a continuity criterion may allow more consideration of the connectivity of an area because it allows a better detection of ecological gradients within a landscape. We applied this methodology to the Tuscany region focusing on terrestrial mammals. Performing a fuzzy classification we produced five land cover maps and through image processing operations we obtained a suitability model which applies a continuity criterion. The resulting suitability fuzzy model seems better for the study of connectivity and fragmentation, especially in areas with high spatial complexity.     

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.     

Monitoring habitat dynamics for rare and endangered species using satellite images and niche-based models

The potential distribution of critically rare or endangered species is necessary to assess species conservation status and guide recovery plans. Habitat models based on remotely sensed geospatial data are increasingly used to predict the suitability of sites for rare and endangered species, but in rapidly changing landscapes, habitat evaluations must reflect temporal as well as spatial variation of environmental suitability in order to properly inform management. We used field measurements of species occurrence, a 22-yr time series of satellite images, and the Maximum Entropy modeling approach (Maxent) to monitor spatio-temporal variation in habitat suitability of an endangered butterfly that uses riparian wetlands modified by beaver activity. We modeled the niche of the St. Francis' satyr Neonympha mitchellii francisci in an environment of remotely sensed metrics and projected the niche model over space and time to evaluate habitat dynamics and target sites for reintroduction efforts. Suitable habitat for the subspecies is currently distributed across the study area; however, most of the suitable area is unoccupied, and patches of the most suitable habitat have shifted over time in response to beaver activity and subsequent wetland succession, suggesting a negative interaction between dispersal limitation and landscape dynamics. Landcover changes complicate the recovery of critically threatened species such as N. m. francisci , but habitat monitoring over time can improve recovery plans, offer adaptive management strategies, and provide more exact criteria for species status assignment. Spatio-temporal extensions of the niche/habitat concept are made possible by long-term archives of remotely sensed data, and will likely prove most useful in rapidly changing landscapes.     

Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available Geographic Information Systems data and logistic regression analysis with an information theoretic approach. Across spatial scales, there was very little support for models with structural habitat features, such as tree canopy cover and conifer diameter. Model-averaged 95% confidence intervals for regression coefficients and associated odds ratios indicated that the occurrence of Siskiyou Mountains salamanders was positively associated with rocky soils and Pacific madrone (Abutus menziesii) and negatively associated with elevation and white fir (Abies concolor); these associations were consistent across 3 spatial scales. The occurrence of this species also was positively associated with hardwood density at the medium spatial scale. Odds ratios projected that a 10% decrease in white fir abundance would increase the odds of salamander occurrence 3.02–4.47 times, depending on spatial scale. We selected the model with rocky soils, white fir, and Oregon white oak (Quercus garryana) as the best model across 3 spatial scales and created habitat suitability maps for Siskiyou Mountains salamanders by projecting habitat suitability scores across the landscape. Our habitat suitability models and maps are applicable to selection of priority conservation areas for Siskiyou Mountains salamanders, and our approach can be easily adapted to conservation of other rare species in any geographical location.     

Modelling the distribution of a threatened habitat: the California sage scrub

Aim Using predictive species distribution and ecological niche modelling our objectives are: (1) to identify important climatic drivers of distribution at regional scales of a locally complex and dynamic system – California sage scrub; (2) to map suitable sage scrub habitat in California; and (3) to distinguish between bioclimatic niches of floristic groups within sage scrub to assess the conservation significance of analysing such species groups. Location Coastal mediterranean‐type shrublands of southern and central California. Methods Using point localities from georeferenced herbarium records, we modelled the potential distribution and bioclimatic envelopes of 14 characteristic sage scrub species and three floristic groups (south‐coastal, coastal–interior disjunct and broadly distributed species) based upon current climate conditions. Maxent was used to map climatically suitable habitat, while principal components analysis followed by canonical discriminant analysis were used to distinguish between floristic groups and visualize species and group distributions in multivariate ecological space. Results Geographical distribution patterns of individual species were mirrored in the habitat suitability maps of floristic groups, notably the disjunct distribution of the coastal–interior species. Overlap in the distributions of floristic groups was evident in both geographical and multivariate niche space; however, discriminant analysis confirmed the separability of floristic groups based on bioclimatic variables. Higher performance of floristic group models compared with sage scrub as a whole suggests that groups have differing climate requirements for habitat suitability at regional scales and that breaking sage scrub into floristic groups improves the discrimination between climatically suitable and unsuitable habitat. Main conclusions The finding that presence‐only data and climatic variables can produce useful information on habitat suitability of California sage scrub species and floristic groups at a regional scale has important implications for ongoing efforts of habitat restoration for sage scrub. In addition, modelling at a group level provides important information about the differences in climatic niches within California sage scrub. Finally, the high performance of our floristic group models highlights the potential a community‐level modelling approach holds for investigating plant distribution patterns.     

气候变化对黄土高原及邻近地区稀有种枯蝉分布的潜在影响(英文)

【目的】未来数十年的气候变化预计会是造成很多物种生境丧失的一个重要因素。对适应能力相对脆弱的地方性物种,预测气候变化对其生境的影响将对生物多样性保护具有重要意义。【方法】本文基于最大熵模型,对珍稀蝉科中国特有种枯蝉Subpsaltria yangi在当前和未来气候条件下的生境适宜度进行了评估。【结果】结果表明,枯蝉主要局限分布于黄土高原及邻近地区。预计至2050年,即使在温和的气候变化情景下,枯蝉的生境面积也会明显减少。影响枯蝉栖息地分布的关键因素为年平均气温、最冷月的最低气温、最冷季的平均气温和最潮湿月份的降水量。枯蝉现存种群栖息地应当受到保护,甘肃天水和陕西延安地区应作为枯蝉分布的核心区予以保护,以应对气候变化对其生境带来的影响。【结论】本研究获得的枯蝉适宜生境分布图可以为该稀有物种的新种群发现、现生种群分布地土地规划管理以及有效的自然保护区设立提供重要信息。     

Incorporating bioclimatic and biogeographic data in the construction of species distribution models in order to prioritize searches for new populations of threatened flora

The aim of this study was to analyse the usefulness of incorporating bioclimatic and biogeographic data into digital species prediction and modelling tools in order to identify potential habitats of rare or endangered flora taxa. Species distribution models (SDMs) were obtained using the Maximum entropy algorithm. Habitat suitability maps were based on sites of known occurrence of studied species. The study showed that highly reliable habitat prediction models can be obtained through the inclusion of bioclimatic and biogeographic maps when modelling these species. The resultant SDMs are able to fit the search area more closely to the characteristics of the species, excluding the percentage of highly suitable areas that are located far from the known distribution of the taxon, where the probability of finding the plant is low. Therefore, it is possible to overcome one of the most commonly encountered problems in the construction of rare or threatened flora taxa SDMs, derived from the low number of initial citations. The resulting SDMs and the vegetation map enable prioritization of the search for new populations and optimization of the economic and human resources used in the collection of field data.     

Using species distribution models to predict new occurrences for rare plants

Aim  To evaluate a suite of species distribution models for their utility as predictors of suitable habitat and as tools for new population discovery of six rare plant species that have both narrow geographical ranges and specialized habitat requirements.
Location  The Rattlesnake Creek Terrane (RCT) of the Shasta-Trinity National Forest in the northern California Coast Range of the United States.
Methods  We used occurrence records from 25 years of US Forest Service botanical surveys, environmental and remotely sensed climate data to model the distributions of the target species across the RCT. The models included generalized linear models (GLM), artificial neural networks (ANN), random forests (RF) and maximum entropy (ME). From the results we generated predictive maps that were used to identify areas of high probability occurrence. We made field visits to the top-ranked sites to search for new populations of the target species.
Results  Random forests gave the best results according to area under the curve and Kappa statistics, although ME was in close agreement. While GLM and ANN also gave good results, they were less restrictive and more varied than RF and ME. Cross-model correlations were the highest for species with the most records and declined with record numbers. Model assessment using a separate dataset confirmed that RF provided the best predictions of appropriate habitat. Use of RF output to prioritize search areas resulted in the discovery of 16 new populations of the target species.
Main conclusions  Species distribution models, such as RF and ME, which use presence data and information about the background matrix where species do not occur, may be an effective tool for new population discovery of rare plant species, but there does appear to be a lower threshold in the number of occurrences required to build a good model.     

Biogeography of Cephalopods in the Southern Ocean Using Habitat Suitability Prediction Models

Our understanding of how environmental change in the Southern Ocean will affect marine diversity, habitats and distribution remain limited. The habitats and distributions of Southern Ocean cephalopods are generally poorly understood, and yet such knowledge is necessary for research and conservation management purposes, as well as for assessing the potential impacts of environmental change. We used net-catch data to develop habitat suitability models for 15 of the most common cephalopods in the Southern Ocean. Using modeled habitat suitability, we assessed favorable areas for each species and examined the relationships between species distribution and environmental parameters. The results compared favorably with the known ecology of these species and with spatial patterns from diet studies of squid predators. The individual habitat suitability models were overlaid to generate a “hotspot” index of species richness, which showed higher numbers of squid species associated with various fronts of the Antarctic circumpolar current. Finally, we reviewed the overall distribution of these species and their importance in the diet of Southern Ocean predators. There is a need for further studies to explore the potential impacts of future climate change on Southern Ocean squid.     

Are Species Coexistence Areas a Good Option for Conservation Management? Applications from Fine Scale Modelling in Two Steppe Birds

Biotic interactions and land uses have been proposed as factors that determine the distribution of the species at local scale. The presence of heterospecifics may modify the habitat selection pattern of the individuals and this may have important implications for the design of effective conservation strategies. However, conservation proposals are often focused on a single flagship or umbrella species taken as representative of an entire assemblage requirements. Our aim is to identify and evaluate the role of coexistence areas at local scale as conservation tools, by using distribution data of two endangered birds, the Little Bustard and the Great Bustard. Presence-only based suitability models for each species were built with MaxEnt using variables of substrate type and topography. Probability maps of habitat suitability for each species were combined to generate a map in which coexistence and exclusive use areas were delimitated. Probabilities of suitable habitat for each species inside coexistence and exclusive areas were compared. As expected, habitat requirements of Little and Great Bustards differed. Coexistence areas presented lower probabilities of habitat suitability than exclusive use ones. We conclude that differences in species'' habitat preferences can hinder the efficiency of protected areas with multi-species conservation purposes. Our results highlight the importance of taking into account the role of biotic interactions when designing conservation measurements.     

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.     

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.     

Translocations,conservation, and climate change: use of restoration sites as protorefuges and protorefugia

High levels of human activity have affected the quality and usability of the natural landscape, leading to habitat degradation, loss of connectivity between sites, and reduced chances of long‐term survival for individual species. In line with conservation policy, ecological restoration practitioners try to improve degraded sites by means of reestablishing species lost from these sites, thereby returning ecological functionality and maintaining biological diversity. It may appear difficult to integrate the long‐term potential impacts of climate change within restoration strategies. However, more refined climate projections and species distribution models provide us with better understanding of likely scenarios, enabling us to consider future proofing as an integral part of the design of restoration sites, aiding plant conservation. We believe that it is possible to go one step further with a closer integration of restoration and conservation objectives. We introduce the novel concepts of “protorefuges” and “protorefugia”—restoration sites that threatened species can be translocated to, where the restoration design can be specifically adapted to help reduce the decline of threatened species at the leading and trailing edges (respectively) of bioclimatic envelope shifts. This is particularly relevant for nuclear decommissioning sites, which may be free from human activity for decades to centuries.     

Land use changes affect distributional patterns of desert birds in the Baja California peninsula, Mexico

Reliable plans for desert bird conservation will depend on accurate prediction of habitat change effects on their distribution and abundance patterns. Predictive models can help highlight relationships between human‐related and other environmental variables and the presence of desert bird species. Presence/absence of 30 desert bird species of Baja California peninsula was modelled on the basis of explanatory variables taken from the field, maps, and digital imagery. Generalized linear models were fit to each bird species using both variables representing human activity and other environmental factors as predictors that might influence distribution. Probability of species presence was used as a habitat suitability index to evaluate the effect of human activity when the model contained a significant human activity variable. No differences were found in bird species richness between natural sites and those transformed by agriculture or urbanization. Of 59 bird species recorded in surveys, 34% were positively or negatively associated with human‐transformed habitats. Fourteen species seem to benefit from transformation of natural vegetation by agriculture or urbanization, while six were negatively affected. Sensitivity analyses of final models indicated all were robust. Results suggest that the occurrence of a large percentage of bird species inhabiting scrub habitats is sensitive to human habitat transformation. This finding has important conservation implications at regional scale as fragmentation and conversion of desert ecosystems into agricultural and urban areas affect the distribution of species that are highly selective for scrub habitat. Land use and anthropogenic activities seem to change ecological patterns at large spatial scales, but other factors could drive species richness distribution too (i.e. individual species response, species–energy relationships). The spatial modelling approach at regional scale used in this study can be useful for designing natural resource management plans in the Sonoran desert scrub.     

Thyme and isolation for the Sinai baton blue butterfly (<Emphasis Type="Italic">Pseudophilotes sinaicus</Emphasis>)

The distribution of the narrowly endemic butterfly Pseudophilotes sinaicus (Lycaenidae) was studied. Potential habitat within its range was first located and then the quality of that habitat assessed. Degree of shelter, diversity of plant species, and resource area of an individual food plant (Thymus decussatus) all affected habitat quality and together were used to develop an index of habitat suitability applicable to each site. The butterfly's distribution was then studied within the identified network of suitable habitat patches: isolated patches with a small resource area were least likely to contain butterflies. Population size in a patch (as opposed merely to patch occupancy) was affected by resource area and the quality of habitat within that patch. Metapopulation processes and variation in habitat quality therefore appear to combine to describe the distribution of patches occupied by P. sinaicus and their population sizes. This finding provides insights into some of the processes operating on an endemic species throughout its geographical range and has important implications for the conservation of this rare butterfly.