Habitat Suitability Models Research Articles

The Gulf toadfish goes south: assessing the potential habitat suitability of Opsanus beta in response to climate change

Climate change can directly influence invasive species range, and may reflect in greater habitat suitability, consequently increasing losses in native biodiversity. Habitat suitability modelling can help identify priority areas for conservation and rapid response for invasive taxa. This study aimed to model the habitat suitability of Opsanus beta, an invasive fish species, in South America under current and future climate change scenarios. Three modelling techniques, Generalized Linear Model (GLM), Maximum Entropy Algorithm (Maxent), and Random Forest (RF), were applied, and their results were compared and then put together in an Ensemble model to visualize habitat suitability. We found that the current habitat suitability of O. beta in South America is relatively low, with its occurrences mostly related to coastal port areas, suggesting that the species was introduced from ballast water. The increase in mean temperature at mean depth and temperature range were the most relevant variables influencing the species habitat suitability. The gradual increase in habitat suitability for the 2100 climate change scenarios, particularly in more severe climate change scenarios, such as the RCP 8.5, was also observed. The study highlights the critical need to use habitat suitability models to mitigate the impact of future climate change scenarios on invasive species. The findings call for preventive measures to be taken in time to prepare areas that may become the target of dispersal and establishment of O. beta.

Prioritization of spatial protection of Šumava National Park, Czechia: comparing reality and the model

ABSTRACT Natural processes and biodiversity are under pressure, especially in the human-dominated region of Central Europe. Therefore, an effective approach is needed for the conservation of the last fragments of valuable habitats. Šumava National Park is one of the biggest relatively natural forested areas within the cultural landscapes of Czechia and Central Europe. It has been protected since 1991 as a National Park, but management has been changed several times; thus, we would like to create a map with nature protection prioritization based on objective procedures and data to help manage the National Park with regard to its goals. We used occurrence data for 50 selected key fauna and flora species and made habitat suitability models; furthermore, data derived from the habitat mapping layer describing the quality of habitats were prepared. These data were inputs for prioritization ZONATION software resulting in a prioritization map, which could be compared with the current zonation of the National Park.

Characterization and development of 14 microsatellite markers for mountain stewartia (Stewartia ovata): an uncommon, Appalachian-endemic member of the tea family

ABSTRACT Mountain stewartia [Stewartia ovata (Cav.) Weatherby] is a rare, endemic understory tree native to the southeastern U.S.A. While found only in microsites across southeastern Appalachia, the species distribution spans from northern Alabama and Georgia to southern Kentucky and Virginia. However, most occurrences have been recorded in Tennessee. While recent distribution surveys and habitat suitability modeling conducted for this species have improved our understanding of the environmental parameters that constitute its fundamental niche, the ecological profile of S. ovata remains poorly understood. Consequently, its rarity has raised concerns as to the long-term resilience of this species in the wild. Faced with these challenges, the assessment of existing genetic diversity in S. ovata through genetically informative molecular resources is critical to understanding the adaptive potential and ecological resilience of the species. Microsatellites are cost-efficient molecular tools capable of addressing these concerns by elucidating trends in population structure, population demography, and inbreeding. To increase the available genetic resources for S. ovata, we screened 105 microsatellite loci for their suitability to assess these population features using capillary gel electrophoresis. The utility of these markers was evaluated by assessing polymorphism information content (PIC) and population statistics, which yielded 14 highly polymorphic microsatellite markers. These markers displayed an average PIC of 0.695 (PIC range of 0.538–0.851), which supports their ability to capture fine-scale genetic diversity within the species. We also report a low average observed heterozygosity of 0.375 (versus an expected heterozygosity of 0.645) among screened loci, which reinforces the need for broader genetic diversity assessments within this species.

Modeling habitat suitability for endemic Grizzled leaf monkey (Presbytis comata) using geospatial machine learning approach

Global biodiversity, which plays a significant role in maintaining the sustainability of Earth's ecosystems, is threatened by increasingly destructive and uncontrolled human activities. Indonesia's Grizzled leaf monkey or Javan Surili (Presbytis comata) is an endemic primate whose population continues to decline. As the high potential for reducing animal habitats on Java has implications for endemic Surili primates, it is necessary to study the characteristics of suitable habitats that can be used as the basis for strategic policies. This study aimed to develop a habitat suitability index (HSI) for Surili with a study of forest areas in Java Island, Indonesia, using a multi-machine learning approach. The novelty of this study is the integration of three machine learning methods, random forest (RF), support vector machines (SVM), and maximum entropy (MaxEnt), and the use of four parameters, climate, topography, ecology, and anthropogenic factors. This is expected to increase the accuracy of assessing the suitability of the developed Surili habitat. Of the 116 Surili encounter points in the region, 7 (6%) were in the suitable HSI class, 38 (33%) in the high HSI class, 49 (42%) in the moderate HSI class, and 22 (19%) in the low and unsuitable HSI classes. Meanwhile, of the 13 release points, 12 (92%) were dominated by areas with high-to-suitable HSI classes. Based on the receiver operating characteristic curve value, the integrated multi machine learning algorithms value was 0.8578. This study could help formulate potential strategic policies in the restoration program that has been pursued to conserve Surili species in Indonesia.

Spatial Distribution and Genetic Diversity of Turbot (Scophthalmus maximus, Linnaeus, 1758) in Bulgarian Black Sea Waters Relative to Fishing Pressure and Their Abiotic Environment

The present study examined the genetic diversity and spatial distribution of turbot (Scophthalmus maximus), an economically important species on the Bulgarian Black Sea coast. Maximum entropy (MaxEnt) modeling software Version 3.4.4. was utilized to develop a habitat suitability model for S. maximus in the Bulgarian Black Sea region. Data collected via demersal and pelagic surveys and genetic sampling from 2017 to 2021 were utilized to link species occurrence localities with selected abiotic factors. Our findings showed that the species’ habitat preferences are strongly influenced by temperature and dissolved oxygen, and projections based on simplified climatic scenarios indicated potential distribution shifts and a substantial reduction in reproduction habitats in the northern region. The assessment of genetic diversity was based on mtDNA COIII sequencing; MtDNA revealed a low level of polymorphism in all analyzed populations. The extensive fishing pressure may have increased the likelihood of genetic and population bottlenecks and a consequent decline in genetic diversity in the Shabla, Nesebar, and Tsarevo populations. The Tajima’s D values for the latter indicated that turbot underwent a bottleneck followed by rapid population expansion. Our findings are essential for the conservation and effective management of S. maximus stocks in the region.

Predicting the Potential Invasion Hotspots of Chromolaena odorata under Current and Future Climate Change Scenarios in Heterogeneous Ecological Landscapes of Mizoram, India

Recent trends in globalization, human mobility surge and global trade aggravated the expansion of alien species introduction leading to invasion by alien plants compounded by climate change. The ability to predict the spread of invasive species within the context of climate change holds significance for accurately identifying vulnerable regions and formulating strategies to contain their wide proliferation and invasion. Anthropogenic activities and recent climate change scenarios increased the risk of Chromolaena odorata invasion and habitat expansion in Mizoram. To forecast its current distribution and habitat suitability amidst climatic alterations in Mizoram, a MaxEnt-driven habitat suitability model was deployed using the default parameters. The resultant model exhibited that the current spatial range of C. odorata occupies 15.37% of geographical areas deemed suitable for varying degrees of invasion. Projections for 2050 and 2070 anticipated an expansion of suitable habitats up to 34.37% of the geographical area of Mizoram, specifically under RCP 2.6 in 2070 in comparison with its present distribution. Currently, the distributional range of C. odorata in Mizoram spans from lower (450 m) to mid elevational ranges up to 1700 meters, with limited presence at higher altitudes. However, the habitat suitability model extrapolates that climate changes will elevate the invasion risk posed by C. odorata across Mizoram, particularly in the North-Western and Central regions. The projection of further territorial expansion and an upward shift in altitudinal range in the future underscores the urgency of instating robust management measures to pre-empt the impact of C. odorata invasion. This study recommends the imperative nature of effective C. odorata management, particularly during the initial stages of invasion.

USE it: Uniformly sampling pseudo‐absences within the environmental space for applications in habitat suitability models

Abstract Habitat suitability models infer the geographical distribution of species using occurrence data and environmental variables. While data on species presence are increasingly accessible, the difficulty of confirming real absences in the field often forces researchers to generate them in silico. To this aim, pseudo‐absences are commonly sampled randomly across the study area (i.e. the geographical space). However, this introduces sample location bias (i.e. the sampling is unbalanced towards the most frequent habitats occurring within the geographical space) and favours class overlap (i.e. overlap between environmental conditions associated with species presences and pseudo‐absences) in the training dataset. To mitigate this, we propose an alternative methodology (i.e. the uniform approach) that systematically samples pseudo‐absences within a portion of the environmental space delimited by a kernel‐based filter, which seeks to minimise the number of false absences included in the training dataset. We simulated 50 virtual species and modelled their distribution using training datasets assembled with the presence points of the virtual species and pseudo‐absences collected using the uniform approach and other approaches that randomly sample pseudo‐absences within the geographical space. We compared the predictive performance of habitat suitability models and evaluated the extent of sample location bias and class overlap associated with the different sampling strategies. Results indicated that the uniform approach: (i) effectively reduces sample location bias and class overlap; (ii) provides comparable predictive performance to sampling strategies carried out in the geographical space; and (iii) ensures gathering pseudo‐absences adequately representing the environmental conditions available across the study area. We developed a set of R functions in an accompanying R package called USE to disseminate the uniform approach.

Interactive roles of temperature and food availability in predicting habitat suitability for marine invertebrates

Natural variability in habitat characteristics, including their interactions, can affect marine invertebrate development. Controlled laboratory experiments seek to assess responses to such variability. For marine invertebrates, responses to temperature are typically assessed but a continuous gradient of all temperatures that a species may encounter is not frequently used. For planktonic larvae of marine invertebrates, biotic factors such as food availability receive less attention due to difficulty in simulating planktonic biotic interactions in a controlled laboratory setting. Here, a laboratory experiment was used to quantify larval development (growth, pelagic larval duration and survival) of the Atlantic surfclam, Spisula solidissima, in response to a continuous range of temperatures and food (phytoplankton) concentrations, allowing quantification of thermal and food availability niches. A second experiment was conducted to quantify the thermal and food availability niches for recruit (post-settlement) surfclams. These experiments were uniquely designed to inform future climate change-based forecasting and habitat suitability modeling. Larval growth and survival increased with increased food availability, while pelagic larval duration decreased with increased food availability. Larval survival decreased with increased temperature, growth peaked near 22 °C and pelagic larval duration was lowest near 22 °C. For recruits, survival and growth increased with both temperature and food availability, but growth decreased at temperatures >22 °C. Broadly, results suggest potential food limitation for continental shelf bivalve larvae and demonstrate that natural variation in food availability may affect thermal tolerances. Results also suggest that throughout the range of the surfclam, high food and moderate temperature areas such as New York Bight and Georges Bank are ideal for larvae and early recruits, whereas low food and high temperature areas, including continental shelf waters in the southern Middle Atlantic Bight, are suboptimal for early life stages of surfclams. This framework may be used for habitat suitability modeling, from an energetic perspective, for other marine invertebrate taxa.

The contributions of flower strips to wild bee conservation in agricultural landscapes can be predicted using pollinator habitat suitability models

Abstract Sowing flower strips along field edges is a widely adopted method for conserving pollinating insects in agricultural landscapes. To maximize the effect of flower strips given limited resources, we need spatially explicit tools that can prioritize their placement, and for identifying plant species to include in seed mixtures. We sampled bees and plant species as well as their interactions in a semi‐controlled field experiment with roadside/field edge pairs with/without a sown flower strip at 31 sites in Norway and used a regional spatial model of solitary bee species richness to test if the effect of flower strips on bee species richness was predictable from the modelled solitary bee species richness. We found that sites with flower strips were more bee species rich compared to sites without flower strips and that this effect was greatest in areas that the regional solitary bee species richness model had identified to be particularly important for bees. Spatial models revealed that even within small landscapes there were pronounced differences between field edges in the predicted effect of sowing flower strips. Of the plant species that attracted the most bee species, the majority mainly attracted bumblebees and only few species also attracted solitary bees. Considering both the taxonomic diversity of bees and the species richness of bees attracted by plants we suggest that seed mixes containing Hieracium spp. such as Hieracium umbellatum, Pilosella officinarum, Taraxacum spp., Trifolium repens, Lotus corniculatus, Stellaria graminea and Achillea millefolium would provide resources for diverse bee communities in our region. Spatial prediction models of bee diversity can be used to identify locations where flower strips are likely to have the largest effect and can thereby provide managers with an important tool for prioritizing how funding for agri‐environmental schemes such as flower strips should be allocated. Such flower strips should contain plant species that are attractive to both solitary and bumblebees, and do not need to be particularly plant species rich as long as the selected plants complement each other.

Present and future suitable habitat for the black-tailed prairie dog ecosystem

The black-tailed prairie dog (BTPD) ecosystem is an important component of North America's Central Grasslands, which are highly imperiled. Here, we develop a habitat suitability model (HSM) for the BTPD ecosystem across their historical geographic range within the United States to support conservation planning in the region. We used an ensemble HSM approach and spatial analysis combining ecological and climatic variables to quantify suitability of habitat for the black-tailed prairie dog ecosystem, both under today's current climate and projected into the future. We identified 20.8 million hectares of suitable grassland habitat for the black-tailed prairie dog ecosystem, indicating that large areas of quality habitat remain across the western half of their historic range. We also identified a significant northward expansion of their geographic range with future climate change scenarios, with a concomitant decline in habitat suitability across the southern Central Grasslands. Our results show that there is substantial conservation potential for the BTPD ecosystem, given the large amount of remaining available habitat, especially across the western portion of their historical range. Currently, however, we estimate that only ca. 782,521 hectares (3.8 %) of this habitat are occupied by BTPDs. The recovery of the black-tailed prairie dog ecosystem is a complex, multidimensional, socio-ecological challenge. The maps we generated in this analysis provide the basis to carry out spatial analyses that also consider the social, political, and threat landscapes and to incorporate such findings into other large-scale, multi-species conservation planning efforts being developed for the Central Grasslands of North America.

Beyond protected areas: The importance of mixed-use landscapes for the conservation of Sumatran elephants (Elephas maximus sumatranus).

Elephants were once widely distributed across the Indonesian island of Sumatra but now exist in small, isolated populations. Using the best data available on elephant occurrence, we aimed to (a) predict potential habitat suitability for elephants (Elephas maximus sumatranus) across the island of Sumatra and (b) model landscape connectivity among the extant elephant populations. We used direct sightings and indirect observations of elephant signs, as well as six remotely sensed proxies of surface ruggedness, vegetation productivity and structure, and human land use and disturbance, to model habitat suitability in a Google Earth Engine (GEE) environment. We validated the habitat suitability prediction using 10-fold spatial block cross validation and by calculating the area under the precision-recall curve (AUC-PR), sensitivity, and specificity for each model iteration. We also used a geolocation dataset collected from global positioning system (GPS) collars fitted on elephants as an independent validation dataset. Models showed good predictive performance with a mean AUC-PR of 0.73, sensitivity of 0.76, and specificity of 0.68. Greater than 83% of the independent GPS collar geolocations were located in predicted suitable habitat. We found human modification, surface ruggedness, and normalized difference vegetation index to be the most important variables for predicting suitable elephant habitat. Thirty-two percent, or 135,646 km2, of Sumatra's land area was predicted to be suitable habitat, with 43 patches of suitable habitat located across Sumatra. Areas with high connectivity were concentrated in the Riau and North Sumatra provinces. Though our analysis highlights the need to improve the quality of data collected on Sumatran elephants, more suitable habitat remains on Sumatra than is used by known populations. Targeted habitat conservation, especially of the suitable habitat in and around the Lamno, Balai Raja, Tesso Tenggara, Tesso Utara, Bukit Tigapuluh, Seblat, Padang Sugihan, and Bukit Barisan Selatan ranges, may improve the long-term viability of this critically endangered species.

Drought-induced changes in hydrological and phenological interactions modulate waterbird habitats dynamics

Floodplain wetlands are essential for the survival and reproduction of waterbirds, but droughts can negatively impact their food availability and habitat conditions, leading to a decline in waterbird abundance and diversity. To better understand the impact of hydrological and phenological variables on floodplain waterbird habitats during drought conditions, we employed hydrological modeling and remote sensing techniques to calculate fine-scale environmental variables. We constructed habitat suitability models using nine years of field surveys of waterbirds and identified the impact of the interaction effects between hydrological and phenological variables on waterbirds under drought and non-drought conditions. The results showed that hydrological and phenological variables can provide useful information for quantifying the habitat suitability of waterbirds. Drought-induced early water recession negatively impacted the quality of waterbird habitats, reducing their habitat suitability. Sedge eaters exhibited the most significant reduction of 34.47% in the total area of the lake, followed by seed eaters, fish eaters and invertebrate eaters. Tuber eaters had the largest increasing trend, with a significant increase area of 7.44% in total area. Our findings suggest that various feeding guilds exhibit distinct interactions in response to drought, which can be strengthened or weakened by alterations resulting from drought. For sedge eaters, seed eaters, and fish eaters, drought could result in a faster decline in habitat suitability by strengthening the interaction effects between variables. In contrast, for invertebrate eaters and tuber eaters, drought could weaken interaction effects between variables, resulting in a slower decline in habitat quality. The results provide valuable insights into the spatial distribution of overwintering waterbirds and can inform conservation efforts in wetlands.

A fragile future for pink birds: habitat suitability models predict a high impact of climate change on the future distribution of flamingos

ABSTRACT Climate change is one of the most impactful global phenomena, affecting multiple ecosystems, particularly wetlands and water bodies, as well as important species that depend on these areas. Flamingos are unique and distinctive species that live exclusively in these environments and are highly impacted by any changes in their breeding or non-breeding wetlands. To address and measure the direct impact that future climatic changes could have on the distribution of the six extant species of flamingos, I used citizen science data and climatic variables to construct habitat suitability models. These models were used to predict the future gain or loss of climatic suitability areas in the short, medium, and long term, under four different Shared Socioeconomic Pathways and eight Global Circulation Models. The results predicted that five out of the six species of flamingos will experience continued loss of habitat over the next few decades in all scenarios. Dramatic changes in distribution are expected for all species. The data also indicate a higher impact of climate change on more habitat restrictive species and on wetlands along the borders of their distributions. Finally, the research highlights the importance of combined efforts from public communities, scientists, and policymakers to create mitigation and conservation plans that could avoid the intensification of climate change effects on wetlands and prevent the future reduction of flamingo populations.

Multi-objective optimization for timber harvest management incorporating wildlife habitat goals

ContextThe forestry industry provides important goods, services and economic benefits, but timber harvest can adversely impact ecosystem services, including wildlife habitat. Timber harvest planning can integrate wildlife habitat quality through multi-objective optimization for timber harvest and wildlife habitat suitability.ObjectivesOur objective was to develop a method to find optimal solutions for timber harvest and wildlife habitat suitability individually and concurrently, then apply the method to Roosevelt elk (Cervus elaphus roosevelti) on Afognak Island, Alaska.MethodsWe developed three seasonal habitat suitability models using elk locations and landscape variables including historical timber harvest on Afognak Island, Alaska. We used threshold-accepting optimization over a 50-year planning horizon to maximize timber harvest yield and habitat suitability in each season, then used multi-objective goal-deviation optimization to simultaneously maximize timber harvest volume and seasonal habitat suitability.ResultsThe optimal solution for timber yield decreased seasonal average habitat suitability by 5.7%. Elk habitat suitability and corresponding optimal solutions varied seasonally; elk generally selected open landcovers and early- to mid-successional timber stands over late-successional and mature stands. Therefore, in the optimal solutions, stands were harvested before they reached maximum volume and few stands were harvested in early planning periods, resulting in a seasonal average loss of 17.5% yield. Multi-objective optimization decreased seasonal average suitability by 3.9% and yield by 1.4% compared to single-objective optimization.ConclusionsOur multi-objective optimization approach that incorporates data-driven habitat suitability models using open-source software can enable managers to achieve desired quantity and quality of wildlife habitat while providing for resource extraction.

Implications for the conservation of deep-water corals in the face of multiple stressors: A case study from the New Zealand region

The waters around New Zealand are a global hotspot of biodiversity for deep-water corals; approximately one sixth of the known deep-water coral species of the world have been recorded in the region. Deep-water corals are vulnerable to climate-related stressors and from the damaging effects of commercial fisheries. Current protection measures do not account for the vulnerability of deep-water corals to future climatic conditions, which are predicted to alter the distribution of suitable habitat for them. Using recently developed habitat suitability models for 12 taxa of deep-water corals fitted to current and future seafloor environmental conditions (under different future climatic conditions: SSP2 – 4.5 and SSP3 – 7.0) we explore possible levels of spatial protection using the decision-support tool Zonation. Specifically, we assess the impact of bottom trawling on predictions of current distributions of deep-water corals, and then assess the effectiveness of possible protection for deep-water corals, while accounting for habitat refugia under future climatic conditions. The cumulative impact of bottom trawling was predicted to impact all taxa, but particularly the reef-forming corals. Core areas of suitable habitat were predicted to decrease under future climatic conditions for many taxa. We found that designing protection using current day predictions alone, having accounted for the impacts of historic fishing impacts, was unlikely to provide adequate conservation for deep water-corals under future climate change. Accounting for future distributions in spatial planning identified areas which may provide climate refugia whilst still providing efficient protection for current distributions. These gains in conservation value may be particularly important given the predicted reduction in suitable habitat for deep-water corals due to bottom fishing and climate change. Finally, the possible impact that protection measures may have on deep-water fisheries was assessed using a measure of current fishing value (kg km−2 fish) and future fishing value (predicted under future climate change scenarios).

Mapping current and future risk of scorpion sting from a species with low medical concern, Mesobuthus phillipsii (Scorpiones: Buthidae) in Iran.

Scorpion stings are one of the most important health challenges and high priority research topic in public health. In this study, we aimed to model habitat suitability of the Mesobuthus phillipsii (Pocock 1889), a species with low medical concern, under current and future climatic conditions in Iran. We also identified vulnerable populations to scorpion stings in the country. Scorpion sting risk modeling was done using an ensemble approach by considering two species distribution modeling methods: MaxEnt and Random Forest methods. Distribution modeling was performed using the sdm R package. The results showed that due to climate change in 2070, the high-risk areas will increase from 20,839 to 79,212 km2. Habitats with a moderate risk of scorpion stings will also increase from 139,347 to 222,833 km2. Consequently, the number of villages in high-risk areas of scorpion stings will increase from 2,870 to 7,017, while this number will increase from 12,759 to 20,104 in the case of medium-risk villages. The results of this study can be used for scorpion stings management in Iran. This study can be used as an example for similar studies on scorpions with high medical emergency.

High seasonal overlap in habitat suitability in a non-migratory High Arctic ungulate

Understanding drivers of space use and habitat selection is essential for management and conservation, especially under rapid environmental change. Here, we develop summer and winter habitat suitability models for the endemic wild Svalbard reindeer (Rangifer tarandus platyrhynchus). The High Arctic Svalbard tundra is currently subject to the fastest temperature increases on Earth, and reindeer spatial responses to associated environmental change are strongly restricted due to landscape barriers (including 60% glacial coverage) and lack of sea ice as movement corridors. We used an extensive dataset of GPS-collared adult females (2009–2018; N = 268 individual-years) to model seasonal habitat selection as a function of remotely sensed environmental variables , and subsequently built habitat suitability models using an ensemble modelling framework. As expected, we found that reindeer preferred productive habitats, described by the normalized difference vegetation index (NDVI) and plant biomass (derived from a vegetation map), in both seasons. This was further supported by selection for bird cliff areas, rich in forage, improving habitat suitability especially in winter. Contrary to our expectations, the terrain variables had similar, impact on habitat suitability in the two seasons, except for use of higher elevations in winter, likely related to improved forage access due to less snow. Suitable habitat patches covered only a small proportion of the landscape and were highly clustered in both seasons. About 13.0% of the total land area was suitable in both seasons, while summer-only and winter-only areas contributed a marginal addition of around 4.7% and 1.5%, respectively. This suggests, that unlike many continental and migratory Rangifer populations, even small geographic areas may encompass suffiscient suitable habitat. These first archipelago-wide habitat suitability models provide seasonal baseline maps relevant for the management and conservation of Svalbard reindeer, particularly under rapid environmental alterations from climate change.

Utilizing herbarium specimens to assist with the listing of rare plants

Funding for rare plant conservation is limited. In addition, many aspects of the biology and ecology of rare plants are unknown. Therefore, low-cost data generation approaches to fill these gaps should be pursued. Herbarium specimens can be used as a low-cost alternative to learn about the basic biology and ecology of rare plant species. The information provided on herbarium labels has dramatically increased in recent decades to include precise locality (i.e., latitude/longitude), exact dates, habitat, associated species, and substrate. In addition, herbarium specimens are being digitized and the resulting images and data are available via clearinghouses such as GBIF and SEINet. Already, herbarium specimens of rare plants have been used to develop habitat suitability models, predict range shifts, and assess changes in flower phenology due to climate change. Herbarium specimens can also provide a wealth of information about the reproductive biology and biotic interactions of rare plants. In this paper, we will demonstrate how this information can be accessed and present a practical application for using this information to populate an important federal listing document in the USA, Species Status Assessments (SSA). We will provide examples from the literature, as well as case studies from our own research, to demonstrate how this information can be collected from herbarium specimens and how and where to incorporate this information into SSAs. More generally, data gleaned from herbarium specimens can become part of a conservationist’s tool kit to further our knowledge of past, present, and future trends for rare plants. Additional knowledge of a species’ biology and ecology allows land managers and conservationists to make more informed decisions and allows for greater protection of listed species.

Projected distribution of the westernmost subpopulation of Assamese macaques (Macaca assamensis pelops) under climate change: conservation implications of a threatened population

Anthropogenic climate change can have a negative impact on the distribution of habitat specialist species with narrow distributional ranges. Among the many areas around the world affected by climate change, the Himalayan region in particular is experiencing marked effects of global warming on its climatic patterns and life forms. This study assessed the current distribution of Assamese macaques (Macaca assamensis) in western Nepal, and projected their likely distribution (via habitat suitability modeling) for the years 2050 and 2070 under the two most plausible greenhouse gas emission scenarios (RCP4.5 and RCP6.0). We recorded a total of 159 Assamese macaques belonging to 10 groups (nine of them residing outside of protected area networks) between 684m and 2550m asl in western Nepal. Climatic niche modeling predicted that 37.03% (25,114 km2) of the total area of western Nepal (67,813 km2) represented suitable habitat of the species, the majority of which ranged between 1000 m and 2000 m asl. Future projections of the current climatic niche of the Assamese macaques revealed a consistent decrease in the suitable habitat for 2050 and 2070 in both of the greenhouse emission scenarios tested. With the RCP6.0 scenario, almost 57% of the current highly suitable habitat would be lost by 2070 with remaining suitable habitat shifted towards higher elevations. The loss of habitat directly affects the species survival and the range shift towards higher elevation exposes them to new areas for conflict with humans. Therefore, the Assamese macaque population in western Nepal requires a high conservation priority with the establishment of new protected areas.

Creating a distribution model of three crayfish species of the genus Faxonius (Decapoda, Cambaridae) in Michigan streams using publicly accessible data

Abstract This research seeks to create a predictive model of habitat suitability for use in determining waterbodies vulnerable to introduced species within the state of Michigan. Three members of the genus Faxonius (Decapoda, Cambaridae) were selected as test taxa for the model due to several species’ propensity for significantly altering the ecosystems they inhabit in Michigan and elsewhere. Michigan State University and the Michigan Department of Natural Resources (MDNR) conducted extensive field surveys of crayfish species assemblages across 461 stream sites from 2014-2016. This project compares these field data to data from publicly available national datasets with the purpose of revealing ecosystems that are vulnerable to population expansion. We identify patterns in Faxonius habitat at local (100 acres) and landscape (1000 acres) scales by associating crayfish occurrences throughout Michigan with variables characterizing landscape conditions thought to be important factors affecting their spread, growth, and survival. An Artificial Neural Network (ANN) model using variables from Soil Survey Geographic Database (SSURGO) and National Land Cover Database (NLCD) successfully identified stream sites and watersheds in Michigan vulnerable to range expansion by Faxonius rusticus (Girard, 1852), Faxonius propinquus (Girard, 1852), and/or Faxonius virilis (Hagen, 1870). We found several habitat variables that influence our predictions. The most important variable describing F. rusticus presence was local (100-acre) scale Open Water land cover class, whereas for F. propinquus, the high-intensity developed land cover class at the local scale was the most important, while it was the shrubland land cover class at the local scale for F. virilis. This research demonstrates a powerful method to identify locations using remote sensing data that can be prioritized for conservation efforts that are threatened by invasive crayfish species.