Use Of Niche Models Research Articles

Analysis of the current risk of Leishmania infantum transmission for domestic dogs in Spain and Portugal and its future projection in climate change scenarios.

Canine leishmaniosis, caused by the protozoan parasite Leishmania infantum, is a cosmopolitan vector-borne zoonosis, transmitted principally by Phlebotomus perniciosus in Spain and Portugal, where it is considered an endemic disease. Ecoinformatics tools such as ecological niche models (ENM) have been successfully tested to model the distribution of the risk of infection of different parasitosis as they take into account environmental variables vital for their survival. The risk map proposed in this study combines the potential distribution of Ph. perniciosus in the Iberian Peninsula and the calculation of the infection rate of the parasite in the vector to model the risk of contracting the disease in a more realistic way. In fact, this weighting strategy improves the predictive power of the resulting model (R2 = 0.42, p = < 0.01) compared to the Ph. perniciosus ENM model alone (R2 = 0.13, p > 0.05). The places with the highest risk of transmission are the southwest and central peninsular area, as well as the Mediterranean coast, the Balearic Islands and the Ebro basin, places where the ideal habitat of Ph. perniciosus and the infection rate is also high. In the case of future projections under climate change scenarios, an increase in the risk of infection by L. infantum can be observed in most of the territory (4.5% in 2040, 71.6% in 2060 and 63% in 2080), mainly in the northern part of the peninsula. The use of ENMs and their weighting with the infection rate in Ph. perniciosus is a useful tool in predicting the risk of infection for L. infantum in dogs for a given area. In this way, a more complete model can be obtained to facilitate prevention and control.

The use of ecological niche models improves biogeographic regionalization of the Balsas Depression, Mexico

AbstractAimBiogeographic regionalization classifies zones in terms of their biotas and contributes to understanding the ecological and historical factors that affect the distribution of species. We use Ecological Niche Modeling (ENM) to complement missing information on species distribution and thus improve the accuracy of biogeographic boundaries.LocationBalsas Depression Floristic Province, Mexico.MethodsBased on parameters documented in herbarium collections and environmental variables, ENM was carried out to determine the most suitable environmental conditions for a species to thrive (i.e., the species' ecological niche). The ENM and spatial analysis were used to obtain the biogeographic regionalization of the seasonally dry tropical forest (SDTF) in the Balsas Depression (BD), Mexico, through spatial analysis. Using the Maxent algorithm, we constructed ecological niche models (ENMs) of 134 flowering plant species distributed preferentially in the SDTF (characteristic species), most of them endemic to the BD. Subsequently, we obtained an incidence matrix based on the information from the 134 ENMs, which was used to analyze the turnover of species in Biodiverse software. The turnover matrix was used for Non‐metric Multidimensional Scaling (NMDS) ordination and clustering analyses. Finally, the environmental predictors most related to species turnover were identified using the relative environmental turnover method.ResultsThe clustering analysis divided the SDTF in the BD into four floristic districts — two located in its western part and two in the eastern region. The NMDS differentiated, in the first component, two districts in the western region and one in the eastern. Seven environmental variables contributed significantly to explaining the turnover of species in these districts; the most significant were the elevation, pH, and precipitation of the coldest quarter.Main ConclusionsThe use of ENM for the regionalization of areas with high species richness allows for a more detailed classification of subregions and the distribution patterns of the species that define their limits. This provides a more solid theoretical basis for the investigation of biogeographic patterns.

Ecological niche modelling guided chemotypic analysis of Ageratum conyzoides L. from varied geography of India

Ageratum conyzoides L., recognized globally as a noxious weed, holds significant value in traditional medicine, particularly in treating cuts, wounds, and tick infestations. This study focuses on identifying specific germplasms of this plant, rich in therapeutically valuable metabolites, across various phytogeographical zones in India. Using the Reverse Phase High-Performance Liquid Chromatography with Photodiode Array Detection (RP-HPLC-PDA) method, we analyzed 110 samples to quantify five key bioactive markers: Precocene-I (PRC-I), Coumarin (CM), Caryophyllene (CAR), Caryophyllene Oxide (CAO), and Humulene (HUM). Our findings revealed distinct geographical variations in these compounds. The highest concentrations of PRC-I (7.86±1.36 %) was found in sample NAC-12, CM (1.50±0.46 %) and HUM (0.0099±0.0004 %) in NAC-104, while CAR (6.33±0.87 %) and CAO (6.23±0.18 %) were predominant in NAC-01 and NAC-02, respectively. Ecological Niche Modelling (ENM) was used to predict the climatic suitability of regions for high yield of these metabolites. The ENM results showed that annual precipitation (Bio 12), precipitation of the coldest quarter (Bio 19) and minimum temperature of coldest month (Bio 6) were the principal climatic factors influencing metabolite content. Geographically, the Indo-Gangetic plain, Indus plain, and Central India were identified as suitable for higher content of PRC-I, CAO, CAR, whereas the North Eastern region favoured high content of CM and HUM. This study underscores the importance of bioactive marker-based assessment in understanding chemotypic diversity and demonstrates the effective use of ENM in predicting optimal habitats for harvesting specific chemotypes. These insights pave the way for location-specific cultivation strategies and targeted procurement of metabolite-rich germplasms, contributing to sustainable sourcing and conservation efforts, as well as to the advancement of herbal product standardization and efficacy.

Can ecological niche models be used to accurately predict the distribution of invasive insects? A case study of Hyphantria cunea in China.

In recent decades, ecological niche models (ENMs) have been widely used to predict suitable habitats for species. However, for invasive organisms, the prediction accuracy is unclear. In this study, we employed the most widely used maximum entropy (MaxEnt) model and ensemble model (EM) Biomod2 and verified the practical effectiveness of the ENM in predicting the distribution areas of invasive insects based on the true occurrence of Hyphantria cunea in China. The results showed that when only limited data of invasive areas were used, the two ENMs could not effectively predict the distribution of suitable habitats of H. cunea, although the use of global data can greatly improve the prediction accuracy of ENMs. When analyzing the same data, Biomod2's prediction accuracy was significantly better than that of MaxEnt. For long-term predictions, the area of suitable habitat predicted by the ENMs was much greater than the occurrence area; for short-term predictions, the accuracy of the predicted area was significantly improved. Under the current conditions, the area of suitable habitat for H. cunea in China is 118 × 104 km2, of which 59.32% is moderately or highly suitable habitat. Future climate change could significantly increase the suitable habitat area of H. cunea in China, and the predicted area of suitable habitats in all climate scenarios exceeded 355 × 104 km2, accounting for 36.98% of the total land area in China. This study demonstrates the use of ENMs to study invasive insects and provides a reference for the management of H. cunea in China.

Modeling the habitat suitability of two exotic freshwater crayfishes in Mesoamerica and the Caribbean:Cherax quadricarinatus(von Martens, 1868) andProcambarus clarkiiGirard, 1852 (Decapoda: Astacidea: Parastacidae, Cambaridae)

AbstractBiological invasions are among the main threats to the diversity of freshwater ecosystems, particularly invasions of freshwater crayfishes, which have negatively impacted native populations and ecosystem functions. Various invasions of freshwater crayfishes have been relatively well documented, allowing the use of Ecological Niche Modeling (ENM) techniques to forecast their potential invasive distribution. Modeling the most environmentally suitable areas for exotic species can provide guidelines to allocate resources, thus contributing to the control and management of invasions. We modelled the potential distribution of Cherax quadricarinatus (von Martens, 1868) and Procambarus clarkiiGirard, 1852 in Mesoamerica and the Caribbean using global occurrence data and ten environmental variables to ensemble a model using nine different algorithms. Our models showed that C. quadricarinatus has a high probability of invasion in tropical lowland areas, with the presence of exotic populations of this species already reported. Our results support that P. clarkii has a higher probability of invasion in some of the mountain ranges and plateaus of the study region, where this species has already established non-native populations. These models visualize the high-risk areas of invasion of these two non-native crayfish species in Mesoamerica and the Caribbean. A regional approach for monitoring and control of the invasive populations is encouraged as well as regulations for trade and aquaculture of freshwater crayfishes.

Predicting the potential impacts of climate change on the endangered endemic annonaceae species in east africa

Globally, endemic species and natural habitats have been significantly impacted by climate change, and further considerable impacts are predicted. Therefore, understanding how endemic species are impacted by climate change can aid in advancing the necessary conservation initiatives. The use of niche modeling is becoming a popular topic in biological conservation to forecast changes in species distributions under various climate change scenarios. This study used the Australian Community Climate and Earth System Simulator version 1 (ACCESS-CM2) general circulation model of coupled model intercomparison project phase 6 (CMIP6) to model the current distribution of suitable habitat for the four threatened Annonaceae species endemic to East Africa (EA), to determine the impact of climate change on their suitable habitat in the years 2050 (average for 2041–2060) and 2070 (average for 2061–2080). Two shared socio-economic pathways (SSPs) SSP370 and SSP585 were used to project the contraction and expansion of suitable habitats for Uvariodendron kirkii, Uvaria kirkii, Uvariodendron dzomboense and Asteranthe asterias endemic to Kenya and Tanzania in EA. The current distribution for all four species is highly influenced by precipitation, temperature, and environmental factors (population, potential evapotranspiration, and aridity index). Although the loss of the original suitable habitat is anticipated to be significant, appropriate habitat expansion and contraction are projections for all species. More than 70% and 40% of the original habitats of Uvariodendron dzombense and Uvariodendron kirkii are predicted to be destroyed by climate change, respectively. Based on our research, we suggest that areas that are expected to shrink owing to climate change be classified as important protection zones for the preservation of Annonaceae species.

Coalescing disparate data sources for the geospatial prediction of mosquito abundance, using Brazil as a motivating case study

One of the barriers to performing geospatial surveillance of mosquito occupancy or infestation anywhere in the world is the paucity of primary entomologic survey data geolocated at a residential property level and matched to important risk factor information (e.g., anthropogenic, environmental, and climate) that enables the spatial risk prediction of mosquito occupancy or infestation. Such data are invaluable pieces of information for academics, policy makers, and public health program managers operating in low-resource settings in Africa, Latin America, and Southeast Asia, where mosquitoes are typically endemic. The reality is that such data remain elusive in these low-resource settings and, where available, high-quality data that include both individual and spatial characteristics to inform the geospatial description and risk patterning of infestation remain rare. There are many online sources of open-source spatial data that are reliable and can be used to address such data paucity in this context. Therefore, the aims of this article are threefold: (1) to highlight where these reliable open-source data can be acquired and how they can be used as risk factors for making spatial predictions for mosquito occupancy in general; (2) to use Brazil as a case study to demonstrate how these datasets can be combined to predict the presence of arboviruses through the use of ecological niche modeling using the maximum entropy algorithm; and (3) to discuss the benefits of using bespoke applications beyond these open-source online data sources, demonstrating for how they can be the new “gold-standard” approach for gathering primary entomologic survey data. The scope of this article was mainly limited to a Brazilian context because it builds on an existing partnership with academics and stakeholders from environmental surveillance agencies in the states of Pernambuco and Paraiba. The analysis presented in this article was also limited to a specific mosquito species, i.e., Aedes aegypti, due to its endemic status in Brazil.

Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases.

Vector-borne diseases (VBDs) pose a major threat to human and animal health, with more than 80% of the global population being at risk of acquiring at least one major VBD. Being profoundly affected by the ongoing climate change and anthropogenic disturbances, modelling approaches become an essential tool to assess and compare multiple scenarios (past, present and future), and further the geographic risk of transmission of VBDs. Ecological niche modelling (ENM) is rapidly becoming the gold-standard method for this task. The purpose of this overview is to provide an insight of the use of ENM to assess the geographic risk of transmission of VBDs. We have summarised some fundamental concepts and common approaches to ENM of VBDS, and then focused with a critical view on a number of crucial issues which are often disregarded when modelling the niches of VBDs. Furthermore, we have briefly presented what we consider the most relevant uses of ENM when dealing with VBDs. Niche modelling of VBDs is far from being simple, and there is still a long way to improve. Therefore, this overview is expected to be a useful benchmark for niche modelling of VBDs in future research.

Ecological niche models applied to post-megafire vegetation restoration in the context of climate change

Climate change and land-use changes are the main drivers altering fire regimes and leading to the occurrence of megafires. Current management policies mainly focus on short-term restoration without considering how climate change might affect regeneration dynamics. We aimed to test the usefulness of ecological niche models (ENMs) to integrate the effects of climate change on tree species distributions into post-fire restoration planning. We also examined different important conceptual and methodological aspects during this novel process. We constructed ENM at fine spatial resolution (25 m) for the four main tree species (Pinus pinaster, Quercus pyrenaica, Q. faginea and Q. ilex) in an area affected by a megafire in Central Spain at two scales (local and regional), two periods (2 and 14 years after the fire) at the local scale, and under two future climate change scenarios. The usefulness of ENMs as support tools in decision-making for post-fire management was confirmed for the first time. As hypothesized, models developed at both scales are different, since they represent different scale dependent drivers of species distribution patterns. However, both provide objective information to be considered by stakeholders in combination with other sources of information. Local models generated with vegetation data 14 years after the fire provided valuable information about local and current vegetation dynamics (i.e., current microecology spatial niche prediction). Regional models are capable of considering a higher proportion of the climatic niche of species to generate reliable climate change forecasts (i.e., future macroclimate spatial niche forecast). The use of precise ENMs provide both an objective interpretation of potential habitat conditions and the opportunity of examining vegetation patches, that can be very valuable in managing restoration of areas affected by megafires under climate change conditions.

Modeling impacts of climate change on the potential distribution of three endemic Aloe species critically endangered in East Africa

Climate change has had a significant impact on natural ecosystems and endemic species around the world and substantial impacts are expected in the future. As a result, knowing how climate change affects endemic species can help in putting forward the necessary conservation efforts. The use of niche modeling to predict changes in species distributions under different climate change scenarios is becoming a hot topic in biological conservation. This study aimed to use the global circulation model (CMIP5) to model the current distribution of suitable habitat for three critically endangered Aloe species endemic to Kenya and Tanzania in order to determine the impact of climate change on their suitable habitat in the years 2050 and 2070. We used two representative concentration pathways scenarios (RCP4.5 and RCP8.5) to project the contraction of suitable habitats for Aloe ballyi Reynolds, A. classenii Reynolds, and A. penduliflora Baker. Precipitation, temperature and environmental variables (Potential evapotranspiration, land cover, soil sedimentary and solar radiation) have had a significant impact on the current distribution of all the three species. Although suitable habitat expansion and contraction are predicted for all the species, loss of original suitable habitat is expected to be extensive. Climate change is expected to devastate >44% and 34% of the original habitats of A. ballyi and A. classenii respectively. Based on our findings, we propose that areas predicted to contract due to climate change should be designated as key protection zones for Aloe species conservation.

Linking ecological niche models and common garden experiments to predict phenotypic differentiation in stressful environments: Assessing the adaptive value of marginal populations in an alpine plant

Environmental variation within a species’ range can create contrasting selective pressures, leading to divergent selection and novel adaptations. The conservation value of populations inhabiting environmentally marginal areas remains in debate and is closely related to the adaptive potential in changing environments. Strong selection caused by stressful conditions may generate novel adaptations, conferring these populations distinct evolutionary potential and high conservation value under climate change. On the other hand, environmentally marginal populations may be genetically depauperate, with little potential for new adaptations to emerge. Here, we explored the use of ecological niche models (ENMs) linked with common garden experiments to predict and test for genetically determined phenotypic differentiation related to contrasting environmental conditions. To do so, we built an ENM for the alpine plant Silene ciliata in central Spain and conducted common garden experiments, assessing flowering phenology changes and differences in leaf cell resistance to extreme temperatures. The suitability patterns and response curves of the ENM led to the predictions that: (1) the environmentally marginal populations experiencing less snowpack and higher minimum temperatures would have delayed flowering to avoid risks of late‐spring frosts and (2) those with higher minimum temperatures and greater potential evapotranspiration would show enhanced cell resistance to high temperatures to deal with physiological stress related to desiccation and heat. The common garden experiments revealed the expected genetically based phenotypic differentiation in flowering phenology. In contrast, they did not show the expected differentiation for cell resistance, but these latter experiments had high variance and hence lower statistical power. The results highlight ENMs as useful tools to identify contrasting putative selective pressures across species ranges. Linking ENMs with common garden experiments provides a theoretically justified and practical way to study adaptive processes, including insights regarding the conservation value of populations inhabiting environmentally marginal areas under ongoing climate change.

Predicting potential distribution and evaluating biotic interactions of threatened species: a case study of Discocactus ferricola (Cactaceae)

Abstract: Information on distribution, number of populations, and biotic interactions are essential for assessing the threat status of species and to establish more effective conservation initiatives. Ecological niche modeling have been successfully applied to identify the potential distribution, even for rare species that have few recorded occurrence points. In this study, we evaluated the potential distribution and additionally generated the first data on the reproductive biology of Discocactus ferricola, due to its degree of threat and the absence of ecological data for that species. The potential distribution map highlighted areas with higher probability of occurrence of D. ferricola on the Residual Plateau of Maciço do Urucum located in Mato Grosso do Sul, Brazil. The occurrence of D. ferricola populations was limited to outcrops of flat ironstone (cangas) distributed in patches across the landscape, increasing the chances of serious threats, such as habitat loss due to mining and species extraction. We also found that D. ferricola is xenogamous. Therefore, in situ conservation actions must prioritize the maintenance of interactions with pollinators by preserving the flora and fauna of rocky outcrops and adjacent forests in areas of greater environmental suitability for D. ferricola. Our study highlights the use of ecological niche modeling and data on biotic interactions to evaluate species potential distribution, to guide new sampling efforts, and to assist conservation and management initiatives.

Caution Is Needed When Using Niche Models to Infer Changes in Species Abundance: The Case of Two Sympatric Raptor Populations.

Simple SummaryThis study focuses on sympatric populations of hen harrier (Circus cyaneus) and Montagu’s harrier (Circus pygargus) breeding in mountain heathlands in the NW Iberian Peninsula. These populations have been affected by habitat loss caused by land-use change. Despite the mounting evidence supporting positive relationships between species abundance and habitat suitability, the capacity of ecological niche models to capture variations in population abundance remains largely unexplored. This study shows that habitat suitability predicted from niche models was significantly correlated with the relative abundance for hen harrier and, to a lesser extent, for Montagu’s harrier. However, the temporal variation in local population abundance was not significantly explained by habitat suitability changes predicted by the niche models. These findings call for caution in the use of niche models to infer changes in population abundance. The positive relationship between species abundance and habitat suitability supports the use of niche models to estimate abundance but does not guarantee the ability of these models to predict temporal variations in species abundance. These findings highlight (1) the need to include other possible biotic or abiotic factors involved in population abundance dynamics into niche models and (2) the need to establish specific monitoring protocols for tracking population dynamics.Despite the mounting evidence supporting positive relationships between species abundance and habitat suitability, the capacity of ecological niche models (ENMs) to capture variations in population abundance remains largely unexplored. This study focuses on sympatric populations of hen harrier (Circus cyaneus) and Montagu’s harrier (Circus pygargus), surveyed in 1997 and 2017 in an upland moor area in northwestern Spain. The ENMs performed very well for both species (with area under the ROC curve and true skill statistic values of up to 0.9 and 0.75). The presence of both species was mainly correlated with heathlands, although the normalized difference water index derived from Landsat images was the most important for hen harrier, indicating a greater preference of this species for wet heaths and peat bogs. The findings showed that ENM-derived habitat suitability was significantly correlated with the species abundance, thus reinforcing the use of ENMs as a proxy for species abundance. However, the temporal variation in species abundance was not significantly explained by changes in habitat suitability predicted by the ENMs, indicating the need for caution when using these types of models to infer changes in population abundance.

Drivers of distributions and niches of North American cold‐adapted amphibians: evaluating both climate and land use

Species distribution estimates are often used to understand the niche of a species; however, these are often based solely on climatic predictors. When the influences of biotic factors are ignored, erroneous inferences about range and niche may be made. We aimed to integrate climate data with a unique set of available land cover and land use data for the six cold-adapted amphibians of North America (Ambystoma macrodactylum, Anaxyrus hemiophrys, Anaxyrus boreas, Pseudacris maculata, Rana sylvatica, Rana luteiventris) to determine the relative importance of climate and non-climate drivers through the use of ecological niche models for present-day range estimates. We compared climate-only, land use-only, and combination models of climate and land use, derived from two different model selection techniques, to determine which was most likely to drive current distributions of cold-adapted amphibian species. Land use layers included land cover type, human population, vegetation type, ecoregion, and the overall human footprint. The most supported models included both climate and land use, with climate and human footprint variables having the highest permutation importance and percent contribution. Models that incorporated climate and land use data performed best as measured with AIC and AUC, although qualitatively most underestimated the northern range edge, implying potential sampling bias or locations of reduced habitat quality for these species in the northern area of the ranges. There were small differences in overall combination models dependent on the method of model selection. The overall effect sizes of landscape factors within the combination models were small except for one landscape feature: human footprint, which incorporated multiple aspects of anthropogenic change on the landscape, including human population density, travel access, and agricultural impact. This aspect of the landscape was just as important as climate, and counter to what we expected, the association was mostly positive, with a negative response only occurring at very high levels. This highlights the importance of moving beyond climate only species range estimates as land cover, specifically human impact, may be driving the patterns of species' ranges.

Distribution of Five Aquatic Plants Native to South America and Invasive Elsewhere under Current Climate

Biological invasions and climate pose two of the most important challenges facing global biodiversity. Certainly, climate change may intensify the impacts of invasion by allowing invasive plants to increase in abundance and further expand their ranges. For example, most aquatic alien plants in temperate climate are of tropical and subtropical origins and the northern limits of their ranges are generally determined by minimum winter temperatures, and they will probably expand their distributions northwards if climate warms. The distribution of five invasive aquatic plants in freshwater systems across continents were investigated. Their global distributions in the current climate were modeled using a recently developed ensemble species distribution model approach, specifically designed to account for dispersal constraints on the distributions of range-expanding species. It was found that the species appear capable of substantial range expansion, and that low winter temperature is the strongest factor limiting their invasion. These findings can be used to identify areas at risk of recently introduction of neophytes, and develop future monitoring programs for aquatic ecosystems, prioritizing control efforts, which enables the effective use of ecological niche models to forecast aquatic invasion in other geographic regions.

Most invasive species largely conserve their climatic niche

The ecological niche is a key concept for elucidating patterns of species distributions and developing strategies for conserving biodiversity. However, recent times are seeing a widespread debate whether species niches are conserved across space and time (niche conservatism hypothesis). Biological invasions represent a unique opportunity to test this hypothesis in a short time frame at the global scale. We synthesized empirical findings for 434 invasive species from 86 studies to assess whether invasive species conserve their climatic niche between native and introduced ranges. Although the niche conservatism hypothesis was rejected in most studies, highly contrasting conclusions for the same species between and within studies suggest that the dichotomous conclusions of these studies were sensitive to techniques, assessment criteria, or author preferences. We performed a consistent quantitative analysis of the dynamics between native and introduced climatic niches reported by previous studies. Our results show there is very limited niche expansion between native and introduced ranges, and introduced niches occupy a position similar to native niches in the environmental space. These findings support the niche conservatism hypothesis overall. In particular, introduced niches were narrower for terrestrial animals, species introduced more recently, or species with more native occurrences. Niche similarity was lower for aquatic species, species introduced only intentionally or more recently, or species with fewer introduced occurrences. Climatic niche conservatism for invasive species not only increases our confidence in transferring ecological niche models to new ranges but also supports the use of niche models for forecasting species responses to changing climates.

Habitat suitability models for the imperiled wood turtle (Glyptemys insculpta) raise concerns for the species’ persistence under future climate change

The use of ecological niche models to predict how future climate change may impact habitat suitability is a critical component of imperiled species management. These models allow for the identification of areas with high future suitability that will support the persistence of the species. We developed an ecological niche model and performed protected areas analysis to assess the current and future distribution of suitable habitat for the globally endangered wood turtle (Glyptemys insculpta) across the northeastern U.S. portion of its range. Our model predicts that by 2070 the suitable habitat for this species will decrease by 29–52%, and the total area of optimal habitat will decrease by 62–86%, depending on emissions scenario. Furthermore, currently only 5% of suitable habitat and 8% of optimal habitat is protected, with the total area of protected suitable and optimal habitat expected to decrease by 16–28% and 31–64%, respectively, by 2070. Our results suggest that long-term wood turtle conservation efforts should be directed towards protecting habitat in higher latitudes of their range, mainly in the states of Maine, Vermont, New Hampshire, and New York where the majority of climate refugia exist. Additionally, management action will be required to facilitate the northward transition of southern populations that are threatened with extinction due to rising temperatures. Along with having important conservation implications for the imperiled wood turtle, our study also serves as an example of how climate change assessments should be used to direct long-term conservation efforts of other imperiled species across the globe.

Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China

Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of the most important threats to global biodiversity in the 21st century and will pose significant challenges to biodiversity conservation in the future. The use of niche modelling to predict changes in the suitable distribution of species under climate change scenarios is becoming a hot topic of biological conservation. In this study, we use data from China’s National Forest Continuous Inventory as well as specimen collection data of Cunninghamia lanceolata (Lamb.) Hook to run optimized Maxent models to predict potential suitable distribution of the species in the present day, 2050s, and 2070s under different climate change scenarios in China. In the modeling process, the most important uncorrelated variables were chosen, and the sample-size-adjusted Akaike information criterion (AICc) was used to select the optimal combination of feature type and regularization multiplier. Variable selection reduced the number of variables used and the complexity of the model, and the use of the AICc reduced overfitting. Variables relating to precipitation were more important than temperature variables in predicting C. lanceolata distribution in the optimal model. The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement. The suitable distribution area is predicted to become more fragmented in the future. Our results reveal the climate conditions required for the suitable distribution of C. lanceolata in China and the likely changes to its distribution pattern in the future, providing a scientific basis for the sustainable management, protection, and restoration of the suitable habitat of this economically important tree species in the context of climate change.

Evaluation of the ecological niche model approach in spatial conservation prioritization.

Ecological niche models (ENMs) are widely used in spatial prioritization for biodiversity conservation (e.g. selecting conservation areas). However, it is unclear whether ENMs are always beneficial for such purposes. We quantified the benefit of using ENMs in conservation prioritization, comparing the numbers of species covered by conservation areas selected on the basis of probabilities estimated by ENMs (ENM approach) and those selected on the basis of raw observation data (raw-data approach), while controlling survey range, survey bias, and target size of conservation area. We evaluated three ENM algorithms (GLM, GAM, and random forests). We used virtual community data generated by simulation for the evaluation. ENM approach was effective when survey bias is strong, survey range is narrow, and target size of conservation area is moderate. The percentage of cases in which the ENM approach outperformed the raw-data approach ranged from 0.0 to 33% (GLM), 31% (GAM), and 75% (random forests) depending on conditions. The number of rare species (< 20 presence records) included in the conservation area based on the ENM approach was less than, or the same as, that of the raw-data approach. The unexpectedly limited cases in which the ENM approach was effective in the present research may depend on the conservation target we used (to cover as many species as possible in conservation area). Our results highlight urgent need for evaluating ENM’s effectiveness under other conservation targets for wise use of ENM in conservation prioritization.

Use of Ecological Niche Models of Plant Species to Optimize Placement of Apiaries

Abstract Apiaries must be located in areas with abundant flora as they are the nutritional base for Apis mellifera. Asteraceae is one of the most diverse plant families in Mexico and several of its species are of interest for beekeepers. The objective of this study was to determine the best sites for the placement of apiaries with the use of ecological niche models (ENM) of some Asteraceae species important for bees in two basins of the state of Michoacán, Mexico. ENM for thirty species were obtained through records of their presence, twenty abiotic variables and one biotic variable, and a map of species richness was made to determine which sites would be environmentally appropriate for apiaries. The models were statistically evaluated using the AUC_Maxent, partial_ROC and the binomial tests and were verified in the field. The first two tests’ models had values of 0.70 to 1 and the binomial test’s models had values of 1. The map showed six suitable areas with the greatest richness of species. The corroboration in the field proved ENM effective by finding twenty-two of the thirty modeled species inside the predicted areas. Our results support that ENM are a good strategy to predict the ideal habitat for species important for beekeeping, and thus determine the best places to establish apiaries in the region.