Niche Factor Analysis Research Articles

The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models

ABSTRACT Uncertainty is a common problem in spatial modeling and geographical information systems (GIS). Furthermore, urban gain modeling (UGM) contains various dimensions and components of uncertainties. Data sampling is important in UGM, and may cause the results of the models to contain many uncertainties as well as affects their precision and accuracy. A poorly sampled or biased dataset can lead to inaccurate predictions and decreased performance of the models. This paper aims to present and develop novel strategies for sampling and building training datasets that can enhance the performance of data-driven models. In other words, the present study used maximum entropy (ME) and ecological niche factor analysis (ENFA) models to select pure non-change samples with minimal uncertainty for training datasets in UGM of Isfahan and Tabriz cities in Iran. The urban gain of two time intervals of 1992–2002 and 2002–2012 were used for Tabriz City and two time intervals of 1994–2004 and 2004–2014 for Isfahan City. Nine and 14 urban gain drivers were used in the UGM of Isfahan and Tabriz cities, respectively. After the ME and ENFA models produced a training dataset with change and non-change samples with the lowest uncertainty, three well-known models, namely random forest (RF), artificial neural network (ANN), and support vector machine (SVM) were used for the modeling. Moreover, the ME and ENFA models that were used to investigate the uncertainty of the sampling procedure were used as the one-class prediction models. Compared to extant studies, the proposed ME – based sampling strategy increased the area under the receiver operating characteristic curve (AUROC), figure of merit, producer’s accuracy, and overall accuracy by 5.5%, 5%, 5%, and 3%, respectively, in the validation phase of Isfahan City and by 5%, 6%, 14%, and 17%, respectively, for Tabriz City. For Isfahan, the accuracies of ME (AUROC = 0.649) and ENFA (AUROC = 0.661) one – class models were closer to that of the ANN – ME (AUROC = 0.646), ANN – ENFA (AUROC = 0.619), and RF – ENFA (AUROC = 0.631) models but differed significantly from that of the RF – ME (AUROC = 0.737) model. For Tabriz, the accuracies of ME (AUROC = 0.657) and ENFA (AUROC = 0.688) one – class models were lower than that of the two class RF-ME (AUROC = 0.852), and ANN-ME (AUROC = 0.778) models. The results showed that the ME model was able to identify relatively pure non-change samples and properly remove impure non-change samples from the training dataset. This study discovered that binary models are preferable to one-class models, and showed that an optimal sampling strategy is an essential step in UGM as it can decrease uncertainty. As such, modelers must adopt efficient sampling methods.

Habitat suitability of a peatland landscape for tiger translocation on Kampar Peninsula, Sumatra, Indonesia

The risk of large carnivore mortality from anthropogenic sources is increased in areas where frequent human-carnivore encounters are high. Translocation is a potential tool for reducing these conflicts and re-establishing wild populations. Determining proper translocation sites for tigers is important for securing their future. In this research, we quantitatively evaluated the habitat suitability of a potential tiger translocation area on the Kampar Peninsula, a large peatland landscape in Sumatra. This landscape is essential for the conservation of the local tiger population, but its role as a tiger habitat has rarely been investigated. We conducted this research in a region with mosaicked land-use types covering an area of 7,045.89 km2. We applied species ecological niche factor analysis (ENFA) to model habitat suitability using species presence and ecogeographical variables as the bases. The model predicted that approximately 60% of the study area is tiger-suitable habitat with varying suitability levels. The tiger habitat characteristics in the study region are dissimilar to the global tiger habitat characteristics, and the high specialization value obtained indicates that tigers inhabit very narrow niches. Considering the low density of tigers in peatlands, we estimate that the carrying capacity of the whole Kampar landscape is approximately 13 tigers. Therefore, to conserve a viable tiger population, it is necessary to maintain connectivity between the Kampar peatlands and the Kerumutan landscape situated to the south of the Kampar Peninsula.

Niches of three sympatric montane ground-dwelling squirrels: Relative importance of climate, topography, and landcover.

Species with different ecological niches will likely exhibit distinct responses to a changing environment. Differences in the magnitude of niche specialization may also indicate which species may be more vulnerable to environmental change, as many life-history characteristics are known to affect climate change vulnerability. We characterized the niche space of three sympatric high-elevation ground-dwelling squirrels, yellow-bellied marmot (Marmota flaviventer), Belding's ground squirrel (Urocitellus beldingi), and golden-mantled ground squirrel (Callospermophilus lateralis), in the alpine and upper subalpine regions of the Sierra Nevada in California. We used 5879 observations of individual squirrels, collected from 4 years (2009-2012) of transect survey data, to quantify which ecogeographical variable types (climate, topography, or landcover) were most important in defining the niche of each species. We conducted Ecological Niche Factor Analysis to quantify the niche and generate indices of "marginality" (magnitude of selection) and "specialization" (narrowness of niche space). All three species demonstrated differential use of niche space when compared to the available niche space. Moreover, the relative importance of the variables shaping the niche differed among these species. For example, the presence of meadows was important in defining the niche for U. beldingi and M. flaviventer, but the presence of conifers was important to C. lateralis. Precipitation was important in defining the niche for all three species, positively so for U. beldingi, and negatively for the other two species. The niche breadth of these three species was also positively associated with geographic range size. Mammals in high-elevation mountain systems often are perceived as vulnerable to climate shifts, but our results underscore the importance of also including non-climate-based factors in defining the niche. The overall magnitude of niche selection for all three species was driven by a combination of topographic, climatic, and landcover factors; thus, efforts to forecast areas where these species can persist in the future need to evaluate from more than just a climatic perspective.

Global warming leads to habitat loss and genetic erosion of alpine biodiversity

AbstractAimSpecies living on steep environmental gradients are expected to be especially sensitive to global climate change, but little is known about the factors influencing their responses to contemporary warming. Here, we investigate the influence of climate on the biogeography of three alpine species with overlapping ranges.LocationTe Waipounamu (South Island) Aotearoa–New Zealand.TaxonEndemic alpine adapted Catantopinae grasshoppers.MethodsWe used niche modelling to estimate and project the potential niche of three focal species under past and future climate scenarios. Vulnerability assessments were performed using niche factor analyses. Demographic trends and phylogeographic structure were investigated using samples from 15 mountain tops to generate mitochondrial DNA haplotype networks and population genetic statistics.ResultsNiche models and genetic data suggest suitable habitat for all three alpine species was more widespread and contiguous in the past than today. Demographic analyses indicate in situ survival rather than post‐Pleistocene colonisation of current habitat. Population structuring and genetic divergence suggest that mountain uplift during the Pliocene and environmental barriers during Pleistocene glacial and interglacial stages shaped contemporary population structure of each species. Although geographically overlapping, niche analyses suggest these alpine species are not ecologically identical, each showing distinct responses to environmental change, but all will lose intraspecific diversity through population extinction.Main ConclusionsClimatic, biological and geophysical factors controlled population structuring of three cold‐adapted species during the Pleistocene with a legacy of spatially separate intraspecific lineages. Ecological niche models for each species emphasise distinct combinations of environmental proxies, but all are expected to experience severe habitat reduction during climate warming. Increased global temperatures drive available habitat to higher elevation resulting in population contractions, range shifts, habitat fragmentation, local extinctions and genetic impoverishment. Despite alpine species not being ecologically identical, we predict all mountain biota will lose significant genetic diversity due to global warming.

Assessing The Extent Of Habitat Overlap And Resource Partitioning Between Ibex And Livestock In Khyber valley Pakistan

Ibex and livestock distribution and habitat preferences were assessed using ecological niche factor analysis (ENFA). The study area was divided into 45 grid cells of 500 x 500 m pixels. Ibex and livestock were documented to occupy 30.61% and 26.5% of the study area, respectively, from June to November. Male and female ibex showed significant sexual segregation during this period. From November to May, male ibex occupied 32.6% of the study area and female ibex 34%. Livestock occupied 19% of the study area from June to September and 14.2% from September to May. The ENFA results indicated that both ibex and livestock show selective habitat preferences but are selecting for the same resources. The first two principal components (PCs) explained 49.3% and 17.88% of the variation in the data, respectively. The first PC was related to distance to settlements, distance to rivers, distance to roads, and rangelands. The second PC was related to rangelands and snow covers. The biplot of ENFA differentiated available habitats from habitat used (by ibex/livestock) through shades of grey, where light grey areas correspond to all the available habitat and dark grey area represented the used area (ecological niche of the animal). The ENFA plot indicated that though ibex and livestock have selective approach towards habitat usage, but selecting for the same resources

Forecasting the distribution of Anogeissus le\xefocarpa (DC.)\xa0Guill. & Perr.\xa0by using an ensemble modelling in Niger, West Africa

Populations of Anogeissus leïocarpa (DC.) Guill. & Perr. in Niger have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation in rural households. Understanding how climate makes the species particularly vulnerable to extinction and how range shifts may be driven by climatic change is more urgent than ever. One powerful approach for the assessment of the species distribution is habitat modelling, which is a promising tool for priority setting, conservation decision-making and overall support for species conservation. This study combined environmental variables found at sites where species occurrence has been confirmed and analyzed the results to predict future spreading patterns. High variation inflation factor (VIF) values were found for the series of interpolated climate. The study results demonstrate that soil type, elevation, bio 2 (mean diurnal range (Mean of monthly (max temp − min temp))) and 18 (precipitation of warmest quarter) contribute greatly to the models. The study shows that the species is predicted to have some suitable current suitable area (100,926.1 km2); the South West Niger is the most important region for the protection of the habitat in Niger. The habitat area of Anogeissus leïocarpa (DC.) Guill. & Perr. is projected to increase drastically suitability areas in future climate up to 2.73% (RCP 4.5) and decrease up to 5.99% (RCP 8.5) according to CCSM4 and MIROC 5. Based on the outcome of the models, the climatic conditions could boost and prevent the development of Anogeissus leïocarpa (DC.) Guill. & Perr. and their existence. The models and habitat suitability maps derived here with the approach of ecological niche factor analysis can facilitate the prediction of habitat quality under different conservation and management regimes of Anogeissus leïocarpa (DC.) Guill. & Perr. The findings are invaluable for the implementation of conservation strategies and domestication programmes based on Anogeissus leïocarpa (DC.) Guill. & Perr.

The habitat suitability of Timor friarbird (Philemon inornatus) in Western Timor Island, Indonesia

Abstract. Paga B, Pudyatmoko S, Wijayanti LR, Yuda P, Sulaksono N. 2021. The habitat suitability of Timor friarbird (Philemon inornatus) in Western Timor Island, Indonesia. Biodiversitas 23: 703-713. Timor friarbird is an endemic bird to Timor Island. The population of this bird has been declining due to land cover changes as a result of massive anthropogenic pressures. This study aimed to assess the suitability of Timor friarbird's habitat by using 12 ecogeographical variables. The sources of data included Sentinel 2A satellite imagery and remote sensing-based algorithms. The bird's presence was analyzed by using a combination of line transect with point count methods. Ecological Niche Factor Analysis (ENFA) model was applied to obtain habitat suitability value as well as coefficient of marginality (M) and specialization (S). These results showed that the Timor friarbird needs a habitat with a different value from the average of the entire habitat. High specialization value indicated that the species has a narrow ecological niche. Factors influencing habitat suitability included the distance from roads, the presence of mangroves, primary and secondary dryland forests, rivers, and low-density settlements. About 75% of the study area is classified as unsuitable habitat, and only 22% is suitable with range classes of suitability from marginal to optimal habitat. Areas with less anthropogenic pressure on the land cover will be preferred more by the bird. Improvement of unsuitable habitat and protection of suitable habitat, therefore, will be the most important strategy for Timor friarbird conservation.

Applying remotely sensed habitat descriptors to assist reintroduction programs: A case study in the hazel dormouse

AbstractFor reintroduction programs to succeed, it is vital to identify suitable release sites. This is especially true for low dispersing habitat specialists, which are at particular risk from habitat fragmentation. The habitat specialist Muscardinus avellanarius (hazel dormouse) is part of a large‐scale reintroduction program in the UK. The program began in 1993 and has so far had varying levels of long‐term success across 24 sites. Although the causes of population persistence at reintroduction sites are not well understood, continued habitat suitability is hypothesized to play an important role. Here, we establish broad‐scale habitat descriptors associated with the current distribution of natural hazel dormouse populations in England, using ecological niche factor analysis and remotely sensed, open‐source maps. We also apply generalized linear mixed effects models to long‐term monitoring data for reintroduced hazel dormouse populations, revealing that broad‐scale habitat factors strongly influence the number of animals present in nest boxes. To aid conservation practitioners in future site selection, we illustrate the practical application of habitat suitability mapping to help prioritize the most appropriate woodlands for future hazel dormouse reintroductions, using the county of Cheshire as an example. Although demonstrated here for the hazel dormouse, this approach to reintroduction site selection could be beneficial to a broad range of species.

Spatial distribution and habitat selection of culicoides imicola: The potential vector of bluetongue virus in Tunisia.

The increasing threat of vector-borne diseases (VBDs) represents a great challenge to those who manage public and animal health. Determining the spatial distribution of arthropod vector species is an essential step in studying the risk of transmission of a vector-borne pathogen (VBP) and in estimating risk levels of VBD. Risk maps allow better targeting surveillance and help in designing control measures. We aimed to study the geographical distribution of Culicoides imicola, the main competent vector of Bluetongue virus (BTV) in sheep in Tunisia. Fifty-three records covering the whole distribution range of C.imicola in Tunisia were obtained during a 2-year field entomological survey (August 2017 – January 2018 and August 2018 – January 2019). The ecological niche of C. imicola is described using ecological-niche factor analysis (ENFA) and Mahalanobis distances factor analysis (MADIFA). An environmental suitability map (ESM) was developed by MaxEnt software to map the optimal habitat under the current climate background. The MaxEnt model was highly accurate with a statistically significant area under curve (AUC) value of 0.941. The location of the potential distribution of C. imicola is predicted in specified regions of Tunisia. Our findings can be applied in various ways such as surveillance and control program of BTV in Tunisia.

Models for Studying the Distribution of Ticks and Tick-Borne Diseases in Animals: A Systematic Review and a Meta-Analysis with a Focus on Africa.

Ticks and tick-borne diseases (TTBD) are constraints to the development of livestock and induce potential human health problems. The worldwide distribution of ticks is not homogenous. Some places are ecologically suitable for ticks but they are not introduced in these areas yet. The absence or low density of hosts is a factor affecting the dissemination of the parasite. To understand the process of introduction and spread of TTBD in different areas, and forecast their presence, scientists developed different models (e.g., predictive models and explicative models). This study aimed to identify models developed by researchers to analyze the TTBD distribution and to assess the performance of these various models with a meta-analysis. A literature search was implemented with PRISMA protocol in two online databases (Scopus and PubMed). The selected articles were classified according to country, type of models and the objective of the modeling. Sensitivity, specificity and accuracy available data of these models were used to evaluate their performance using a meta-analysis. One hundred studies were identified in which seven tick genera were modeled, with Ixodes the most frequently modeled. Additionally, 13 genera of tick-borne pathogens were also modeled, with Borrelia the most frequently modeled. Twenty-three different models were identified and the most frequently used are the generalized linear model representing 26.67% and the maximum entropy model representing 24.17%. A focus on TTBD modeling in Africa showed that, respectively, genus Rhipicephalus and Theileria parva were the most modeled. A meta-analysis on the quality of 20 models revealed that maximum entropy, linear discriminant analysis, and the ecological niche factor analysis models had, respectively, the highest sensitivity, specificity, and area under the curve effect size among all the selected models. Modeling TTBD is highly relevant for predicting their distribution and preventing their adverse effect on animal and human health and the economy. Related results of such analyses are useful to build prevention and/or control programs by veterinary and public health authorities.

Climatic ecological suitability and potential distribution of Tricholoma matsutake in western Sichuan Plateau, China based on MaxEnt model.

Based on the distribution data of Tricholoma matsutake obtained from field investigation and literature, the ecological-niche factor analysis (ENFA) and the maximum entropy model (MaxEnt) were used to simulate the distribution law and suitable area of T. matsutake in the western Sichuan Plateau. The prediction was made for the future changes in the suitable area of T. matsutake by analyzing the relationship between climate factors and dynamic distribution. The results showed that the area under curve (AUC) values of both the model training set and validation set were greater than 0.90, indicating that the model prediction results were extremely accurate. The environmental variables affecting the potential distribution of T. matsutake were mainly the lowest temperature in the coldest month, the coldest season precipitation, annual temperature difference and soil type, with accumulative contribution of 90.3%. The niche parameters of suitable distribution areas of T. matsutake were as follows: the lowest temperature in the coldest month was -18.5--5.4 ℃, the coldest season precipitation was less than 15.7 mm, the annual temperature difference was 39.5-45 ℃, and soil type was semi-leached soil, including dry red soil, cinnamon soil, gray cinnamon soil, black soil and grey forest soil. The suitable areas of T. matsutake were distributed in the southwest, south, central and east of the plateau at an altitude range of 1900-3600 m. The highly suita-ble areas were mainly distributed in some towns of Yajiang, Xiangcheng, Kangding, Jiulong, Daocheng, Litang, Batang, Danba, Maerkang, Xiaojin, Jinchuan, Lixian, Maoxian, etc. The moderately and lowly suitable areas were located in some towns of Derong, Daofu, Xinlong, Luhuo, Baiyu, Luding, Rangtang, Wenchuan, Heishui, Jiuzhaigou. The highly suitable areas were discontinuously distributed according to the direction of rivers and mountains. The moderately suitable areas were connected with the highly suitable areas, while the lowly suitable areas were the extension of the highly and moderately suitable areas. Future climate change would be beneficial to the growth of T. matsutake on the western Sichuan Plateau, while the climate-suitable areas would show an overall increasing trend. Suitable areas in the low-altitude Minjiang River Basin would be more affected by climate change than those located in high-altitude areas.

Assessing Habitat Suitability for the Common Pochard, Aythya Ferina (Anseriformes, Anatidae) at different Spatial Scales in Orel’ River Valley, Ukraine

Abstract The habitat suitability for the Common Pochard, a duck species in decline, was studied in the middle reaches of the Orel’ River, Central Ukraine, in 2015–2017. The ducks were counted on their breeding grounds with the use of the ground survey technique. The positions of individual birds were estimated by GPS and plotted on the Google Earth map. The Ecological Niche Factor Analysis (ENFA) was applied to assess the habitat suitability. Sentinel-2 image was used to extract 13 ecogeographical variables and to get two measures of the ecological niche (marginality and specialization). The ENFA procedure was applied twice at landscape and sub-landscape levels to describe the habitat selection across sequential spatial scales. Both the axes of marginality and specialization of the ecological niche of the species proved to be significantly different from the random alternatives. At landscape level, the distribution may be predicted with the use of Aerosol/Coastal, Vegetation and Hydrothermal Composite indices (marginality) and Modified Normalized Difference Water (MNDW) Index along with several vegetation indices (specialization). At sub-landscape level, MNDW played a crucial role. The importance of MNDW is mediated by the preference for the wetlands with the stretches of open water which are used by the ducks to initiate flight safely and to optimize diving possibilities. The ENFA is a reliable tool for the assessment of the habitat suitability and for setting the conservation priorities for the Common Pochard.

Factors affecting the home range of Dinaric-Pindos brown bears

Abstract Studying how animals interact with their environment is fundamental to informing conservation and management efforts, especially when examining large, wide-ranging carnivores in human-dominated landscapes. We hypothesized that the home ranges of bears are configured to exploit supplemental food (corn) and avoid people. In 2004–2016, we tracked 10 brown bears from the Dinaric-Pindos population using GPS telemetry, then used Brownian bridge movement models to estimate their home ranges. We related seasonal home range size to circadian period and density of supplemental feeding sites using generalized linear mixed-effect models. We also used ecological-niche factor analysis to study habitat composition within home range core areas in study areas characterized by different levels of human encroachment. We found that home range size was inversely related to density of supplemental feeding sites, and bears had larger home ranges at night (x̅ = 103.3 ± 72.8 km2) than during the day (x̅ = 62.3 ± 16.6 km2). Our results also revealed that bears living in more human-influenced areas concentrated their use far from human settlements and agricultural lands but stayed close to supplemental feeding sites. Our data suggest that bears alter their space-use patterns at the home range level in response to anthropogenic land use and food availability.

Out of sight, out of mind: Phylogenetic and taxonomic gaps imply great underestimations of the species’ vulnerability to global climate change

The study of the species’ climatic niche is an excellent proxy of their vulnerability to global climate change. It is well known that species with greater niche marginality or a smaller niche breadth are most vulnerable to global climate change. However, these measures have never been contextualized regarding the shortfalls in biogeography: Linnean and Darwinian shortfalls. Here based on the study of Liolaemidae, one of the most diverse families of tetrapods, we showed that as phylogenetic and taxonomic knowledge accumulated across time and shortfalls filled up, the split of species complexes (previously recognized as single species) generates new species much more vulnerable to the effect of global climate change. We calculated and compared via Ecological Niche Factor Analyses (ENFA), Climate-Niche Factor Analysis (CNFA), and ellipsenm the marginality and breadth of climatic niches of five monophyletic groups of lizards, considering two stages in their taxonomic knowledge: the original described species (past period), and currently the updated species (2020 period). For both stages, we also estimated their climate change exposure and vulnerability. The climatic niche of the updated species (current, 2020) was significantly more marginal and smaller, and therefore their exposure and vulnerability to global climate change significantly more remarkable, than the originally described species (past periods). Our findings evidence that the real vulnerability of biodiversity to global climate, could be masked for the lack of taxonomic and phylogenetic knowledge, highlighting the great importance of these disciplines for species’ risk assessments. This fact is especially exacerbated in those poorly known or unstudied diverse groups and countries.

Range expansion, habitat use, and choosiness in a butterfly under climate change: Marginality and tolerance of oviposition site selection.

Poleward range shifts under climate change involve the colonization of new sites and hence the foundation of new populations at the expanding edge. We studied oviposition site selection in a butterfly under range expansion (Lycaena dispar), a key process for the establishment of new populations. We described and compared the microhabitats used by the species for egg laying with those available across the study sites both in edge and in core populations. We carried out an ecological niche factor analysis (ENFA) to estimate (1) the variety of microhabitats used by the butterfly for egg laying (tolerance) and (2) the extent to which these selected microhabitats deviated from those available (marginality). Microhabitat availability was similar in edge and core populations. Ambient temperature recorded at the site level above the vegetation was on average lower at core populations. In contrast with what is often assumed, edge populations did not have narrower microhabitat use compared to core populations. Females in edge populations even showed a higher degree of generalism: They laid eggs under a wider range of microhabitats. We suggest that this pattern could be related to an overrepresentation of fast deciding personalities in edge populations. We also showed that the thermal time window for active female behavior was reduced in edge populations, which could significantly decrease the time budget for oviposition and decrease the threshold of acceptance during microhabitat selection for oviposition in recently established populations.

Application of modeling techniques for the identification the relationship between environmental factors and plant species in rangelands of Iran

The objective of the present research was to compare Ecological Niche Factor Analysis (ENFA) and Artificial Neural Networks (ANN) to determine the optimum threshold of plant species (Thymus kotschyanus Boiss and Hohen. and Dactylis glomerata L.) in rangelands of Ardabil province. Systematic random sampling of vegetation was performed, and an overall 111 sites were considered and divided into two groups, namely sites with plant species and sites without plant species. Five plots of one square meter were placed in each site. The size of the plots was based on the magnitude of one or double the average area of the most common plant species. Plots were positioned along a 40-m transect (from the bottom of the slope to high altitudes with a distance of 10 m between the plots). Soil sampling was done in a depth of 0–30 cm (selected based on the activity of root plant species). Maps of environmental factors were prepared in ArcGIS 10.4.1 software. The sensitivity and specificity were considered to specify the optimum threshold. The optimal threshold between plant species, determined by modeling methods, showed that the highest accuracy belonged to ENFA model in T. kotschyanus habitat (with optimum threshold = 0.62 and sensitivity = 0.58) and ANN model in D. glomerata habitat (with optimum threshold = 0.37 and sensitivity = 0.02) had the lowest accuracy.

Predicting global climatic suitability for the four most invasive anuran species using ecological niche factor analysis

Invasive species have a massive impact on their environment and predicting geographical zones at risk of invasion is paramount to the control of further invasions. Invasive anurans are particularly detrimental to native amphibian species, other vertebrates, and even aquaculture through competition, predation, disease transmission, toxicity, or a combination of these. Four species have been designated as the worst anuran invaders worldwide: Duttaphrynus melanostictus, Rhinella marina, Lithobates catesbeianus and Xenopus laevis. In this study, we modelled global habitat suitability for all four species using ecological niche factor analysis (ENFA) to predict the most susceptible areas to invasion. Models showed suitable climatic conditions for all four species expanded beyond their current native and invasive ranges. Tropical, subtropical, and island biomes around the world were among the areas with the highest ENFA suitability for all four species. Further, marginality statistics indicate niche expansion in D. melanostictus, and generalism in the three other species. As only climatic variables were used in the modelling, these results show the ultimate distributions if all landscape conditions are met without significant barriers to invasion.

Geographic range estimates and environmental requirements for the harpy eagle derived from spatial models of current and past distribution.

Understanding species–environment relationships is key to defining the spatial structure of species distributions and develop effective conservation plans. However, for many species, this baseline information does not exist. With reliable presence data, spatial models that predict geographic ranges and identify environmental processes regulating distribution are a cost‐effective and rapid method to achieve this. Yet these spatial models are lacking for many rare and threatened species, particularly in tropical regions. The harpy eagle (Harpia harpyja) is a Neotropical forest raptor of conservation concern with a continental distribution across lowland tropical forests in Central and South America. Currently, the harpy eagle faces threats from habitat loss and persecution and is categorized as Near‐Threatened by the International Union for the Conservation of Nature (IUCN). Within a point process modeling (PPM) framework, we use presence‐only occurrences with climatic and topographical predictors to estimate current and past distributions and define environmental requirements using Ecological Niche Factor Analysis. The current PPM prediction had high calibration accuracy (Continuous Boyce Index = 0.838) and was robust to null expectations (pROC ratio = 1.407). Three predictors contributed 96% to the PPM prediction, with Climatic Moisture Index the most important (72.1%), followed by minimum temperature of the warmest month (15.6%) and Terrain Roughness Index (8.3%). Assessing distribution in environmental space confirmed the same predictors explaining distribution, along with precipitation in the wettest month. Our reclassified binary model estimated a current range size 11% smaller than the current IUCN range polygon. Paleoclimatic projections combined with the current model predicted stable climatic refugia in the central Amazon, Guyana, eastern Colombia, and Panama. We propose a data‐driven geographic range to complement the current IUCN range estimate and that despite its continental distribution, this tropical forest raptor is highly specialized to specific environmental requirements.

Characterizing the climatic niche of mast seeding in beech: Evidences of trade-offs between vegetation growth and seed production

Masting is a complex mechanism which is mainly driven by a combination of internal plant resources and climatic conditions. While the driving role of climate in masting is being intensively studied, the interplay among climate, seed production, vegetation growth and phenology still needs further investigation. The objectives of thisstudy were to identify the climatic determinants of different levels of seed production and of NDVI-based vegetation growth and phenology in European beech, and to evaluate if exists a trade-off between these two plant processes. To answer these questions, we used a 25-year-long dataset of beech seed production. We exploited the concept of ecological niche assuming that a mast year can be modeled like a species with variable preferences for different resources, which are the underlying annual climatic conditions; we performed an Ecological Niche Factor Analysis (ENFA), a presence-only modeling tool conventionally used in zoology and botany, and used seasonal (spring, summer, autumn) Standardized Precipitation-Evaporation Index (SPEI) observations, considering the current year (y−0), and up to one (y−1) and two (y−2) years before the masting event. For analyzing the role of vegetation growth and phenology, we used seasonal Normalized Difference Vegetation Index (NDVI) values and associated NDVI-based phenological metrics derived from Landsat imagery. Results indicated the driving role of climate for masting, especially in VHSP years. A moist summer and dry spring at y−2 and a dry summer at y−1 represented the main driving climatic conditions for masting; while a moist spring during the observation year represented the key condition for triggering higher intensities of seed production. Summer NDVI at y−0 and y−1 represented the variables discriminating best between masting and non-masting years and resulted as driven by opposite summer climatic conditions than seed production, thus indicating a trade-off between seed production and vegetation phenology. We concluded that reproduction and vegetation growth act as two different climate-dependent plant responses in beech, in a way that certain conditions through the years promote mast seeding and the opposite conditions favor vegetation growth. The understanding of climate-growth-masting relationships represents indispensable knowledge for providing a holistic view of masting mechanisms and developing adaptive forest management strategies in this species.

Projecting the distribution range of the chestnut tiger butterfly Parantica sita sita (Lepidoptera: Nymphalidae: Danainae) in southwestern China

The chestnut tiger butterfly Parantica sita sita (Kollar) (Lepidoptera: Nymphalidae: Danainae) is a potential model to study the mechanisms underlying long-distance migrations in insects. However, few studies have investigated this subspecies. This study predicts the distribution of P. s. sita using a species distribution model (Maxent), and analyzes the key influencing factors using ecological niche factor analysis. Based on 104 occurrence sites, the suitable area of P. s. sita was projected to be most area of Yunnan, the southern foothills of the Himalayas in Tibet, west Guizhou, central Sichuan, the central and northern parts of Chongqing, and the southern boundary of Shaanxi and Gansu. Among examined environmental factors the isothermality and temperature seasonality proved to be most important. Furthermore, the distribution range during warm season was identical to that for the whole year, whereas the distribution range during cold season was projected as the southern part of Yunnan only. In addition to the climatic differences between the north and south of China, the projected seasonal migration of P. s. sita might explain the shift of its distribution range during different seasons. This study also provides essential information for further ecological research on P. s. sita.