Developed Species Distribution Models Research Articles

Environmental filtering mediates desert ant community assembly at two spatial scales.

Understanding the mechanisms that maintain species coexistence and determine patterns of community assembly are fundamental goals of ecology. Quantifying the relationship between species traits and stress gradients is a necessary step to disentangle assembly processes and to be able to predict the outcome of environmental change. We examined the hypothesis that desert ant communities are assembled by niche-based processes i.e., environmental filtering and limiting similarity. First, we used population-level morphological trait measurements to study the functional structure of ant communities along a dryland environmental stress gradient. Second, we developed species distribution models for each species to quantify large-scale climatic niche overlap between species. Body, femur, antennal scape, and head lengths were correlated with environmental gradients. Regionally, the ant community was significantly and functionally overdispersed in terms of morphological traits which suggests the importance of competition to ant community structure. Ant community assembly was also strongly influenced by environmental factors as the degree of functional trait divergence, but not phylogenetic divergence, decreased with increasing environmental stress. Thus, environmental stress likely mediates limiting similarity in these desert ecosystems. Species with lower climatic niche overlap were more dissimilar in morphological traits. This suggests that environmental filtering on ant functional traits is important at the scale of species distributions in addition to regional scales. This study shows that environmental and biotic filtering (i.e., niche-based assembly mechanisms) are jointly and non-independently structuring the ant community.

A climate-induced tree species bottleneck for forest management in Europe.

Large pulses of tree mortality have ushered in a major reorganization of Europe's forest ecosystems. To initiate a robust next generation of trees, the species that are planted today need to be climatically suitable throughout the entire twenty-first century. Here we developed species distribution models for 69 European tree species based on occurrence data from 238,080 plot locations to investigate the option space for current forest management in Europe. We show that the average pool of tree species continuously suitable throughout the century is smaller than that under current and end-of-century climate conditions, creating a tree species bottleneck for current management. If the need for continuous climate suitability throughout the lifespan of a tree planted today is considered, climate change shrinks the tree species pool available to management by between 33% and 49% of its current values (40% and 54% of potential end-of-century values), under moderate (Representative Concentration Pathway 2.6) and severe (Representative Concentration Pathway 8.5) climate change, respectively. This bottleneck could have strong negative impacts on timber production, carbon storage and biodiversity conservation, as only 3.18, 3.53 and 2.56 species of high potential for providing these functions remain suitable throughout the century on average per square kilometre in Europe. Our results indicate that the option space for silviculture is narrowing substantially because of climate change and that an important adaptation strategy in forestry-creating mixed forests-might be curtailed by widespread losses of climatically suitable tree species.

Risk of climate change to sweet potato cultivation in the American continent

ABSTRACT Sweet potato, Ipomoea potatoes L., is an essential crop for food security in various countries. However, the effects of climate change could reduce or increase the yield and profitability of this crop, especially for small farmers. Thus, we developed species distribution models for the current and six climate change scenarios based on environmental variables, species occurrence, and global climate change model. Also, we identified the most relevant environmental variables for cultivation. Future scenarios showed gradual shifts in suitable areas for cultivation. Losses in suitable areas were more relevant than gains at the low concentration of greenhouse gas emissions (RCP 2.6). This trend is maintained in the worst scenario of a high concentration of greenhouse gas emissions (RCP 8.5) with more significant losses of suitable areas. The temperature and precipitation of warmest and wettest quarters, temperature seasonality, and isothermality are the most critical variables for sweet potato cultivation. The cultivation is expected to expand the suitable areas in some regions and retract in others due to climate change. Knowledge about climate change effects in cultivated areas is essential for developing management plans that could mitigate the adverse effects of climate change.

Cold temperatures drive the latitudinal range limits and inhibit overwintering survival of the redbanded stink bug (Hemiptera: Pentatomidae).

For non-native insects that are economically damaging, understanding the drivers of range expansions and contractions is important for forecasting pest pressure. The invasion of the redbanded stink bug, Piezodorus guildinii (Westwood) (Hemiptera: Pentatomidae), reached Louisiana, United States, in 2000, after which the northern range limits of this species have fluctuated annually. Low winter temperatures have been implicated as a major driver of this pattern, but the importance of cold temperatures-or other abiotic factors-for the persistence of this pest over large geographic scales are incompletely understood. We coupled occurrence data of P. guildinii with climatic data to investigate trends in P. guildinii presence in relation to winter temperatures and develop species distribution models, forecasting habitat suitability based on current and future climatic scenarios. Our results show that (i) some P. guildinii persisted in locations where ambient temperatures reached -12°C, (ii) overwintering temperatures drive P. guildinii range dynamics, and (iii) with intermediate projections of climatic warming, northward expansion by P. guildinii in North America is likely to be minimal. While the northern extent of P. guildinii's range may now be largely realized in North America, our results suggest that increased frequency of mild winters could reduce interannual fluctuations of P. guildinii and enable it to become a more consistent economic concern for soybean growers throughout the Midsouth region of the United States.

Mapping queen snapper (Etelis oculatus) suitable habitat in Puerto Rico using ensemble species distribution modeling.

Queen snapper (Etelis oculatus) is of interest from an ecological and management perspective as it is the second most landed finfish species (by total pounds) as determined by Puerto Rico commercial landings (2010-2019). As fishing activities progressively expand into deeper waters, it is critical to gather data on deep-sea fish populations to identify essential fish habitats (EFH). In the U.S. Caribbean, the critically data-deficient nature of this species has made this challenging. We investigated the use of ensemble species distribution modeling (ESDM) to predict queen snapper distribution along the coast of Puerto Rico. Using occurrence data and terrain attributes derived from bathymetric datasets at different resolutions, we developed species distribution models unique to each sampling region (west, northeast, and southeast Puerto Rico) using seven different algorithms. Then, we developed ESDM models to analyze fish distribution using the highest-performing algorithms for each region. Model performance was evaluated for each ensemble model, with all depicting 'excellent' predictive capability (AUC > 0.8). Additionally, all ensemble models depicted 'substantial agreement' (Kappa > 0.7). We then used the models in combination with existing knowledge of the species' range to produce binary maps of potential queen snapper distributions. Variable importance differed across spatial resolutions of 30 m (west region) and 8 m (northeast and southeast region); however, bathymetry was consistently one of the best predictors of queen snapper suitable habitat. Positive detections showed strong regional patterns localized around large bathymetric features, such as seamounts and ridges. Despite the data-deficient condition of queen snapper population dynamics, these models will help facilitate the analysis of their spatial distribution and habitat preferences at different spatial scales. Our results therefore provide a first step in designing long-term monitoring programs targeting queen snapper, and determining EFH and the general distribution of this species in Puerto Rico.

Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Over the course of a few decades, climate change has caused a rapid and alarming reshaping of species habitats, resulting in mass extinction, particularly among sensitive species. In order to investigate the effects of climate change on species distribution and assess habitat suitability, researchers have developed species distribution models (SDMs) that estimate present and future species distribution. In West Asia, thyme species such as T. fedtschenkoi, T. pubescens, and T. transcaucasicus are rich in thymol and carvacrol, and are commonly used as herbal tea, spice, flavoring agents, and medicinal plants. This study aims to model the distribution of these Thymus species in Iran using the MaxEnt model under two representative concentration pathways (RCP 4.5 and RCP 8.5) for the years 2050 and 2070. The objective is to identify the crucial bioclimatic (n = 5), edaphic (n = 1), and topographic (n = 3) variables that influence their distribution and predict how their distribution might change under various climate scenarios. The findings reveal that the most significant variable affecting T. fedtschenkoi and T. pubescens is altitude, while soil organic carbon content is the primary factor influencing the distribution of T. transcaucasicus. The MaxEnt modeling demonstrates excellent performance, as indicated by all the area under the curve (AUC) values exceeding 0.9. Based on the projections, it is expected that these three thyme species will experience negative area changes in the coming years. These results can serve as a valuable tool for developing adaptive management strategies aimed at enhancing protection and sustainable utilization in the context of global climate change. Special attention should be given to conserving T. fedtschenkoi, T. pubescens, and T. transcaucasicus due to their significant habitat loss in the future.

Potential Range Map Dataset of Indian Birds

Conservation management heavily relies on accurate species distribution data. However, distributional information for most species is limited to distributional range maps, which could not have enough resolution to take conservation action and know current distribution status. In many cases, distribution maps are difficult to access in proper data formats for analysis and conservation planning of species. In this study, we addressed this issue by developing Species Distribution Models (SDMs) that integrate species presence data from various citizen science initiatives. This allowed us to systematically construct current distribution maps for 1091 bird species across India. To create these SDMs, we used MaxEnt 3.4.4 (Maximum Entropy) as the base for species distribution modelling and combined it with multiple citizen science datasets containing information on species occurrence and 29 environmental variables. Using this method, we were able to estimate species distribution maps at both a national scale and a high spatial resolution of 1 km2. Thus, the results of our study provide species current species distribution maps for 968 bird species found in India. These maps significantly improve our knowledge of the geographic distribution of about 75% of India’s bird species and are essential for addressing spatial knowledge gaps for conservation issues. Additionally, by superimposing the distribution maps of different species, we can locate hotspots for bird diversity and align conservation action.

Predicting climate change impacts on critical fisheries species in Fijian marine systems and its implications for protected area spatial planning

AbstractAimSpatially explicit protections of coastal habitats determined on the current distribution of species and ecosystems risk becoming obsolete in 100 years if the movement of species ranges outpaces management action. Hence, a critical step of conservation is predicting the efficacy of management actions in future. We aimed to determine how foundational, habitat‐building species will respond to climate change in Fiji.LocationThe Republic of Fiji.MethodsWe develop species distribution models (SDMs) using MaxEnt, General Additive Models and Boosted Regression Trees and publicly available data from the Global Biodiversity Information Facility to predict changes in distribution of suitable habitat for mangrove forests, coral habitat, seagrass meadows and critical fisheries invertebrates under several IPCC climate change scenarios in 2070 or 2100. We then overlay predicted distribution models onto existing Fijian protected area network to assess whether today's conservation measures will afford protection to tomorrow's distributions.ResultsWe found that mangrove suitability is projected to decrease along the Coral Coast and increase northward towards the Yasawa Islands due to precipitation changes. The response of seagrass meadows was predicted to be inconsistent and dependent on the climate scenario. Meanwhile, suitability for coral reefs was not predicted to decline significantly overall. The mangrove crab Scylla serrata, an important resource for fisherwomen in Fiji, is projected to increase in habitat suitability while economically important sea cucumber species will have highly variable responses to climate change.Main conclusionsSpecies distribution models are a critical tool for conservation managers, as linking spatial distribution data with future climate change scenarios can aid in the creation and resiliency of protected area programmes. New protected area designations should consider the future distribution of species to maximize benefits to those taxa.

Long-term effect of forest harvesting on boreal species assemblages under climate change

Logging is the main human disturbance impacting biodiversity in forest ecosystems. However, the impact of forest harvesting on biodiversity is modulated by abiotic conditions through complex relationships that remain poorly documented. Therefore, the interplay between forest management and climate change can no longer be ignored. Our aim was to study the expected long-term variations in the assemblage of bird and beetle communities following modifications in forest management under different climate change scenarios. We developed species distribution models to predict the occurrence of 88 species of birds and beetles in eastern Canadian boreal forests over the next century. We simulated three climate scenarios (baseline, RCP4.5 and RCP8.5) under which we varied the level of harvesting. We also analyzed the regional assemblage dissimilarity by decomposing it into balanced variations in species occupancy and occupancy gradient. We predict that forest harvesting will alter the diversity by increasing assemblage dissimilarity under all the studied climate scenarios, mainly due to species turnover. Species turnover intensity was greater for ground-dwelling beetles, probably because they have lower dispersal capacity than flying beetles or birds. A good dispersal capacity allows species to travel more easily between ecosystems across the landscape when they search for suitable habitats after a disturbance. Regionally, an overall increase in the probability of occupancy is projected for bird species, whereas a decrease is predicted for beetles, a variation that could reflect differences in ecological traits between taxa. Our results further predict a decrease in the number of species that increase their occupancy after harvest under the most severe climatic scenario for both taxa. We anticipate that under severe climate change, increasing forest disturbance will be detrimental to beetles associated with old forests but also with young forests after disturbances.

Balancing Rare Species Conservation with Extractive Industries

The Colorado Plateau has abundant oil, gas, and alternative energy potential. This energy potential is scattered among a patchwork of land ownership, with private, tribal, and public lands being actively developed for energy extraction. Elements of biodiversity (e.g., listed and sensitive plant and animal species) are distributed among all land tenures, yet the laws protecting them can vary as a function of land tenure. It is imperative to understand the spatial distributions of threatened endangered, and sensitive species in relation to land tenure to preserve habitat and conserve species populations in areas undergoing energy development. We developed species distribution models and spatial conservation optimization frameworks to explore the interactions among land ownership, existing and potential energy extraction, and biodiversity. Four management scenarios were tested to quantify how different approaches to energy extraction may impact rare plant distributions. Results show that incorporating risk and land tenure in spatially optimized frameworks it is possible to facilitate the long-term viability of rare plant species. The scenarios developed here represent a different attitude towards the value of rare plants and the risk of energy development. Results gives insight into the financial consequences of rare species protection and quantifies the biodiversity costs of energy development across landscapes.

Developing species distribution models for critically endangered species using participatory data: The European sturgeon marine habitat suitability

Increasing knowledge on distribution and habitat selection of coastal fish species is essential for the management of marine environments, and can be provided through the use of Species Distribution Models (SDM). Opportunistic and participatory data, such as recreational or commercial bycatch data, can provide precious information at large scale and low cost to estimate fish spatial distributions, but are subject to biases (e.g. lack of absence data, non-random sampling scheme). The European sturgeon (Acipenser sturio) is a critically endangered diadromous fish and its marine habitat preferences are unknown. The goal of this study was to investigate key variables driving A. sturio distribution and predict its current distribution in inshore waters along the European Atlantic coast. We developed two correlative SDM in A. sturio marine habitats based on incidental observations (2012–2021) and two different sets of environmental predictors. In both attempts, six methods which differ according to the biases they aim to reduce (i.e. oversampled areas or environmental conditions, dependence between calibration and validation datasets) and the input dataset used (i.e. random pseudo-absences or target-group pseudo-absences) were applied at various stages of the model building and evaluation process. By comparing potentially biased and bias-corrected predictions, we found similar satisfactory level of evaluation and spatial patterns of habitat suitability. Marine areas predicted as the most suitable were distributed along the French Atlantic coast, the Seine and Somme bays, and at a lesser extent around the Rhine delta and in some coastal areas of the Cantabrian Sea (Northern Spain). We found a strong influence of the bathymetry, temperature, and salinity as well as an influence of the bottom current velocity and of the distance to the source population in explaining A. sturio marine distribution, while the nature of the substrate was not retained by the models. Results of this study could pave the way toward more integrated conservation measures for this critically endangered fish.

Hindcast-validated species distribution models reveal future vulnerabilities of mangroves and salt marsh species.

Rapid climate change is threatening biodiversity via habitat loss, range shifts, increases in invasive species, novel species interactions, and other unforeseen changes. Coastal and estuarine species are especially vulnerable to the impacts of climate change due to sea level rise and may be severely impacted in the next several decades. Species distribution modeling can project the potential future distributions of species under scenarios of climate change using bioclimatic data and georeferenced occurrence data. However, models projecting suitable habitat into the future are impossible to ground truth. One solution is to develop species distribution models for the present and project them to periods in the recent past where distributions are known to test model performance before making projections into the future. Here, we develop models using abiotic environmental variables to quantify the current suitable habitat available to eight Neotropical coastal species: four mangrove species and four salt marsh species. Using a novel model validation approach that leverages newly available monthly climatic data from 1960 to 2018, we project these niche models into two time periods in the recent past (i.e., within the past half century) when either mangrove or salt marsh dominance was documented via other data sources. Models were hindcast‐validated and then used to project the suitable habitat of all species at four time periods in the future under a model of climate change. For all future time periods, the projected suitable habitat of mangrove species decreased, and suitable habitat declined more severely in salt marsh species.

A gap analysis of reconnaissance surveys assessing the impact of the 2019–20 wildfires on vertebrates in Australia

Large-scale disturbance events are forecast to increase in severity and frequency due to climate change. On-ground surveys are crucial for assessing the immediate impact of disturbances on biodiversity and for informing management responses. However, there are few examples where quantitative tools have guided post-disturbance survey design. In this study, we integrated species distribution modelling and spatial prioritisation to identify taxonomic and spatial gaps in surveys for 92 priority vertebrates 6 months after the 2019–20 wildfires in Australia. We predicted the pre-fire distribution of priority species, mapped locations of post-wildfire surveys that were already underway, and integrated this information with remotely-sensed fire severity maps in the tool, Zonation, to prioritise locations for new surveys across three fire severity classes (unburnt, low severity, high severity). Our results suggest that 6 months after the wildfires, surveys by government agencies had targeted 17 of 20 mammals (85%); 11 of 17 birds (65%); 10 of 17 frogs (59%); 10 of 23 reptiles (43%) and 5 of 17 fish (29%). We developed species distribution models for 63 of these species after collating 120,118 occurrence records from 6 data repositories. By predicting their distribution before the wildfires, we most efficiently identified gaps in survey effort while ensuring representation across species and fire severity classes. Our analysis provided an important ‘stocktake’ of the response effort to the 2019–20 wildfires in Australia and helped inform the allocation of government-funded wildfire recovery programs. Although we focus on wildfire, our approach could assess gaps in survey effort following any large-scale disturbance.

Endemism, projected climate change, and identifying species of critical concern in the Scrub Mint clade (Lamiaceae)

AbstractRecent studies have revealed that narrow endemics, particularly those native to the North American Coastal Plain, are experiencing range contractions due to human development and anthropogenic‐driven climate warming. We model how the projected distributions of a group of scrub‐adapted plant species with similar evolutionary histories change in response to warming climates. The Scrub Mint clade (Lamiaceae) (SMC), which comprises 24 species in Dicerandra, Conradina, Stachydeoma, Piloblephis, and Clinopodium, including federally or state‐listed threatened and endangered species, occurs in the scrub and sandhill biomes of the North American Coastal Plain. Georeferenced occurrence points were used to develop species distribution models (SDMs) to assess both present and predicted future ranges of all SMC species under future climate change. Future SDMs show that suitable environments for 67% of the SMC species would cover reduced geographical areas than at present. This loss of habitat is most pronounced in species of the Florida peninsula but is also prevalent in species found farther north. We use SDMs to identify the most at‐risk species and geographic areas. Narrowly endemic species were more susceptible to habitat loss than those species with wider ranges. Using a large dataset and modeling habitat suitability at this regional scale, we demonstrate that scrub‐adapted species are highly vulnerable to habitat reduction as a result of climate change.

Ecological interactions mediate projected loss of kelp biomass under climate change

AbstractAimClimate change has precipitated loss of kelp in temperate regions globally, with further losses projected in response to ocean warming. Projected climate‐driven changes to kelp are commonly derived from responses to sea surface temperature and neglect the effects of important ecological interactions, such as herbivory. Here, we use a stacked species distribution model to project impacts of future climate scenarios on kelp distribution and biomass incorporating the effects of key ecological interactions.LocationThe eastern Australian coastline (28.0–37.5°S).MethodsA stacked species distribution model, incorporating ecological interactions with urchins, was used to project future effects of climate change on kelp. This model incorporated key drivers of kelp occurrence and cover (habitat availability, light and in situ temperatures) that are rarely considered when projecting the effects of climate change on kelp.ResultsConsistent with previous research, we find range contractions of kelp (~275 km) at lower latitudes (<32°S), due to ocean warming under RCP 8.5 (~3.4°C) by 2100. However, in contrast to previous studies, we find range contractions will not occur under RCP 2.6 (~0.8°C), and only moderate contractions are projected (~55 km) under RCP 6.0 (~2.3°C). Instead, vertical migration of kelp, from shallow areas to cooler deep water refugia, is likely under future change. Interestingly, range contractions at lower latitudes are projected to be offset by increased kelp biomass at higher latitudes (32–37.5°S) resulting from reductions in urchin herbivory. Consequently, a net gain in kelp biomass is projected for mainland eastern Australia by 2100 under RCPs 2.6 and 6.0 (up to 29.4%), while relatively small net losses are projected under RCP 8.5 (−3.5%).Main conclusionsConsidering key ecological interactions when developing species distribution models can significantly change projections of habitat loss and must be integrated into assessments to accurately evaluate future change and enable evidence‐based management.

Limited Range-Filling Among Endemic Forest Herbs of Eastern North America and Its Implications for Conservation With Climate Change

Biodiversity hotspots host a high diversity of narrowly distributed endemic species, which are increasingly threatened by climate change. In eastern North America, the highest concentration of plant diversity and endemism occurs in the Southern Appalachian Mountains (SAM). It has been hypothesized that this region served as a refugium during Pleistocene glacial cycles and that postglacial migration northward was dispersal limited. We tested this hypothesis using species distribution models for eight forest herb species. We also quantified the extent to which the geography of suitable habitat shifted away from the current range with climate change. We developed species distribution models for four forest herb species endemic to the SAM and four that co-occur in the same SAM habitats but have broader ranges. For widespread species, we built models using (1) all occurrences and (2) only those that overlap the SAM hotspot in order to evaluate the extent of Hutchinsonian shortfalls and the potential for models to predict suitable habitat beyond the SAM. We evaluated the extent to which predicted climatically suitable areas are projected to shift away from their current ranges under future climate change. We detected unoccupied but suitable habitat in regions up to 1,100 km north of the endemic species’ ranges. Endemic ranges are disjunct from suitable northern areas due to a ∼100–150 km gap of unsuitable habitat. Under future climate change, models predicted severe reductions in suitable habitat within current endemic ranges. For non-endemic species, we found similar overall patterns and gap of unsuitability in the same geographic location. Our results suggest a history of dispersal limitation following the last glacial maximum along with an environmental barrier to northward migration. Conservation of endemic species would likely require intervention and assisted migration to suitable habitat in northern New England and Canada.

Changes in the Habitat Preference of Crested Ibis (Nipponia nippon) during a Period of Rapid Population Increase.

Simple SummaryIn 1981, the crested ibis (Nipponia nippon) was a critically endangered bird with only two pairs left in the world. Now, numbers have increased, and it has been reintroduced to many places in China, Japan, and Korea. In the breeding season, the crested ibis has high food needs (fish, freshwater invertebrate, etc.) to feed nestlings, and it prefers areas with rice paddies and waterbodies near to trees for nesting. We compared nest site preference from 1981 to 2019, and found that nest sites moved closer to houses of local farmers. In the 1980s, crested ibises only lived in remote mountain areas, where the farmers were too poor to afford pesticide and fertilizer, and consequently rice paddies contained substantial fish populations. In the meantime, the massive use of pesticides in more populated areas had caused the collapse of fish populations. A pesticide ban was enforced from 1981 on, when the crested ibis was rediscovered, and the freshwater biodiversity gradually recovered. The crested ibis returned to lower and more populated areas containing their ancestral habitats with large areas of wetlands.The number of breeding pairs of crested ibis (Nipponia nippon) in Hanzhong, China has recovered remarkably from 2 to 511 from 1981 to 2019. Although the crested ibis has been closely monitored, the habitat preference of the bird has not been well studied despite the extensive increase in abundance. We used nest site data from the past 39 years and 30 environmental variables to develop species distribution models for each year. We applied random forest to select important environmental variables, and used logistic regressions to quantify the changes in habitat preferences in 39 years, taking into account the effects of interaction and quadratic terms. We found that six variables had strong impacts on nest site selection. The interaction term of rice paddies and waterbodies, and the quadratic term of precipitation of the wettest quarter of the year were the most important correlates of nest presence. Human impact at nest sites changed from low to high as birds increased their use of ancestral habitats with abundant rice paddies. We concluded that during the population recovery, the crested ibises retained their dependence on wetlands, yet moved from remote areas to populated rural regions where food resources had recovered due to the ban of pesticide use.

Revealing floristic variation and map uncertainties for different plant groups in western Amazonia

AbstractQuestionsUnderstanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad‐scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia.LocationMiddle Juruá river region, Amazonas State, Brazil.MethodsWe mapped four plant groups by applying machine learning to scale up locally observed community composition and using environmental and remotely sensed variables as predictors, which were obtained as GIS layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national‐level vegetation classification.ResultsThe overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high.ConclusionOur maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science‐based conservation and land‐use planning.

Predicting koala (Phascolarctos cinereus) distribution from incidental sighting data in South-East Queensland, Australia

Species distribution maps are important tools for wildlife conservation planning and management. To model koala distributions, usually, a spatially representative sample of koala populations is collected through systematic field surveys. Details of koala sightings collected by members of the public could potentially be used to develop species distribution models if appropriate analytical approaches are applied to address the inherent biases in such datasets. We developed a stepwise approach for applying bias correction techniques to estimate and map koala distributions. Using a Boosted regression tree approach, we modelled indirectly the search effort made by observers to identify or sight koalas. Land lot density (58%) and human population density (19%) had the strongest positive impact on the indirect search effort, while the distances to roads were negatively associated with the indirect search effort. To estimate the koala distribution across South-East Queensland, we then developed models describing koala habitat (environmental model), access to koala habitat (accessibility model) and the search effort (search effort model), with the latter including the indirect search effort covariate. Finally, we corrected the estimates derived from these models (bias-corrected search effort and accessibility model). Three independent statistical modelling approaches (Lasso penalty Poisson regression, Down-weighted Poisson regression, and Maximum entropy) were used to compare the five koala distribution models. Based on assessments of areas under curves, the predictive accuracy of models improved when area accessibility and search effort were included. Overall, the spatial extent of koala distributions increased in the prediction maps when models were corrected for accessibility and indirect search effort (except for Down-weighted Poisson regression).

Targeting conifer removal to create an even playing field for birds in the Great Basin

The encroachment of pinyon-juniper woodlands into sagebrush habitat in the Great Basin Ecoregion of the western USA, represents a potential source of habitat degradation for sagebrush-associated wildlife species. To restore sagebrush habitat, managers are conducting large-scale conifer removal efforts within the Great Basin, particularly within Greater Sage-Grouse (Centrocercus urophasianus) priority areas for conservation. Such large-scale habitat modification efforts may result in unintended ecological trade-offs for wildlife. To investigate these trade-offs, we used community science data to develop species distribution models for two sagebrush and three pinyon-juniper associated bird species of conservation concern in the Great Basin. We evaluated the predictive performance of our models with an independent dataset of presence locations derived from systematic monitoring programs. We then simulated conifer removal across the Great Basin and mapped habitat gains and losses for our study species. Despite differing land cover associations, 31%–51% of suitable habitat for our study species coincided with Greater Sage-Grouse priority areas for conservation. Our conifer removal scenario increased suitable habitat by 6%–17% for sagebrush associates and reduced habitat by 11%–41% for pinyon-juniper associates. We identified areas of the Great Basin where conifer removal expanded habitat for sagebrush associates without concurrent habitat loss for pinyon-juniper associates. Our results provide guidance for conducting vegetation management in the Great Basin while addressing the habitat needs for multiple focal species. Our methods, which use freely available community science data and geospatial layers, can easily be transferred to other species and ecoregions.