ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling

Abstract. Pradhan P, Setyawan AD. 2021. Filtering multi-collinear predictor variables from multi-resolution rasters of WorldClim 2.1 for Ecological Niche Modeling in Indonesian context. Asian J For 5: 111-122. WorldClim is one of the popular environmental datasets which hosts multi-resolution interpolated gridded climate raster surfaces and derived bioclimatic variables for both the immediate past, present and future scenarios. Bioclimatic variables along with other environmental factors like solar radiation, wind speed, water vapour pressure etc. have been used as primary set of explanatory variables for mapping and spatial modeling of many biological processes, including defining environmental niche of a species and identifying potential areas for its distribution through machine learning methods like Ecological Niche Modeling or Species Distribution Modeling or Habitat Suitability Modeling. However, the interpolated explanatory datasets are known to cause over-fitting of the models mainly due to multi-collinearity or redundancy within the variables. In the present study, 58 bioclimatic and environmental variables of Indonesian extent extracted from WorldClim 2.1 are screened to investigate the presence of multi-collinearity or redundancy. From the total 3364 variable pairs per raster resolution, 174 variable pairs were known to be affected by multicollinearity, from which temperature related bioclimatic variables, water vapour pressure and elevation associated variables were highly notable. For all the raster resolutions, bioclimatic variable 2, 3, 4, 15, 18 and 19, as well as slope, aspect, solar radiation for January, April, May, September, wind speed for August and November were found to be non-collinear. While, solar radiation for March and July were found to be non-collinear for 30s, 2.5m and 5m raster resolutions; Wind speed of July was non-collinear for 30s and 2.5m; Solar radiation for February and June were non-collinear for 10m; water vapour pressure for August for 2.5m and wind speed for January was non-collinear for 30s raster resolutions. The results of this study might serve as a convenient reference for investigators of the region for selection of bioclimatic and other environmental variables for conducting ecological niche modeling studies.

The widespread use of spatial planning tools in conjunction with increases in the availability of geographic information systems and associated data has led to the rapid growth in the exploration and application of species distribution models. Conservation professionals can choose from a considerable number of modelling techniques, but there has been relatively little evaluation of predictive performance, data requirements, or type of inference of these models. Empirical data for woodland caribou Rangifer tarandus caribou was used to examine four species distribution models, namely a qualitative habitat suitability index and quantitative resource selection function, Mahalanobis distance and ecological niche models. Models for three sets of independent variables were developed and then a temporally independent set of caribou locations evaluated predictive performance. The similarity of species distribution maps among the four modelling approaches was also quantified. All of the quantitative species distribution models were good predictors of the validation data set, but the spatial distribution of mapped habitats differed considerably among models. These results suggest that choice of model and variable set could influence the identification of areas for conservation emphasis. Model choice may be limited by the type of species locations or desired inference. Conservation professionals should choose a model and variable set based on the question, the ecology of the species and the availability of requisite data.

Climate change is anticipated to escalate the frequency and severity of global natural disasters over the next few decades, thereby significantly reshaping species distributions and populations. Species distribution models (SDMs), as essential tools in biogeography and biodiversity conservation, are pivotal for evaluating the impacts of climate change on species and forecasting their distribution ranges under different climate change scenarios over various periods. However, the absence of necessary background knowledge for model construction significantly affects the accuracy of these models, with the selection of different occurrence data sources being a key factor that constrains the accuracy of model predictions. In this study, using Quercus variabilis as a case study, which has diverse ecological, economic, and cultural values, we employed the Biomod2 ensemble modeling platform to comparatively analyze disparities between two different occurrence data sources (i.e., online specimen and scientific survey data) in the species distribution prediction accuracy, relative contribution of major environmental variables, and predicted distribution ranges. Furthermore, we examined potential discrepancies between these two data sources in the migration distance and direction of the species distribution centroid under different future climate scenarios over various periods. Our results indicated substantial differences in the simulation outcomes of SDMs derived from various occurrence data sources. SDMs based on scientific survey data had higher predictive accuracy (AUC = 0.9720, TSS = 0.8370), with the simulated species distribution ranges not only closely matching the actual distributions but also showing more pronounced changes in suitable habitat areas and centroid migration trends under future climate scenarios. In comparison, models based on online specimen data predicted a wider species distribution range, yet exhibited less pronounced trends in suitable area changes and centroid migration under future climate scenarios. Additionally, although the main environmental variables affecting the simulation outcomes from different occurrence data sources were essentially identical, they varied in their contributions and order of importance. Among them, human activity had a relatively stronger contribution for the online specimen data (17.76%), while topographic variables had a stronger impact for the scientific survey data, such as elevation (17.79%). Therefore, the choice of occurrence data sources have a significant impact on SDMs modeling results; this study provides insights and guidance for selecting optimal occurrence data sources to enhance the reliability of SDMs simulations.

The distribution of freshwater benthic macroinvertebrates can be quantified by means of species distribution models (SDMs). For this purpose, the occurrence of a taxon is linked to environmental variables the occurrence sites to calculate the presence probability in the study area. The application of SDMs in freshwater ecosystems is relatively recent, as such models deliver limited information on potential species distribution at the catchment scale. Furthermore, the use of extensive environmental variables such as hydrological and hydraulic data is desirable in order to take into account relevant terrestrial and limnic processes and their interactions. Such information is rarely available. In the upper Changjiang catchment (approx. 1,717 km(2)) in China's south-east, an ecohydrological SWAT-model and a biological BIOMOD/R SDM were integrated for the first time, based on the examples of two taxa (Corbicula sp. and Hydropsyche sp.). The occurrence probability of the two taxa was calculated through hydrologic, climatic and topographic variables at a high resolution of 90 m. The hydrology-related variables (e.g. mean temperature during dry season) had the greatest impact on the modelled occurrence of the taxa. Their application and improvement point to a better understanding of the interactions between terrestrial and limnic processes, which is of great importance considering current environmental changes such as landuse and climate change.

ISSN 1948-6596 news and update workshop summary The application of species distribution models in the megadi- verse Neotropics poses a renewed set of research questions Species distribution models: applications, challenges and perspectives – Belo Horizonte, Brazil, 29 th –30 th August 2011 The community of researchers and technicians interested in biogeography is large and growing in Brazil, with members coming from fields as di- verse as ecology, evolution and conservation. The increment in the number of postgraduate pro- grams in ecology and evolutionary biology is linked to many research questions about the causes and dynamics of species’ ranges, as well as about their consequences for short-term evolu- tionary processes. As a result, the use (and abuse) of species distribution models (SDMs) as a tool in research and technical studies has grown rapidly in recent years. Systems that integrate biodiver- sity databases (e.g. SpeciesLink 1 ) allow one to ob- tain distributional information about many spe- cies; and easy-to-use SDM software (e.g. MaxEnt 2 , Phillips et al. 2004, or openModeller 3 , Munoz et al. 2011) is also available online. The easy avail- ability of data and SDM tools provides a powerful means for answering questions about the geo- graphic distribution of species. Potential users include non-specialist researchers, untrained post- graduate students and government technicians. But is this helping to develop a sound and solidly grounded knowledge of the distribution of Neotropical diversity? In order to unite the Brazilian community of SDM users and provide them with a better under- standing of the technique, the Postgraduate Course on Plant Biology of the Universidade Fed- eral de Minas Gerais organized a workshop in Belo Horizonte last August. This workshop allowed more than 100 students and technicians to meet and discuss with researchers working with SDMs. The main conclusions of the meeting were that there is a growing interest in using the technique to study species’ distributions and find unknown populations of rare species, and that there is a need for a code of good practice in both field sur- veys and SDM applications. These conclusions have been already discussed elsewhere (Kamino et al. 2011). Here we develop further one of the problems identified during the workshop: the lack of clear questions in many studies using SDMs; in other words, the mere application of species dis- tribution modelling as a fashionable technique often ‘justifies’ a study. Reviews summarizing the most important challenges for SDMs (e.g. Araujo and Guisan 2006, Zimmermann et al. 2010, Peterson et al. 2011) typically present how users view the field and what problems they perceive in each step in the modelling process. However, things move fast in this emerging field of research because, while the number of studies using SDMs increases steadily (see Fig. 1 in Lobo et al. 2010), the technique is also used to address completely new questions. Thus, the challenges to their application are them- selves changing. We believe that the most impor- tant of these challenges are theoretically rather than methodologically grounded, although we recognize that both kinds of problems overlap to some extent. Here we outline the basic questions that we believe SDM users must take into account while studying current species’ distributions. Soberon (2007) provides perhaps the best starting point to understand the theoretical prob- lems of SDMs (see also Colwell and Rangel 2009; Soberon 2010). The first problem is the definition of a clear research question. Here it is important to discriminate between theoretical questions such as “Why is this species here?” – which are more interesting in the long run – from those that are eminently practical such as “Where is this spe‐ cies?” – which unfortunately seem to be the most common. But even practical questions stimulated 1 http://www.splink.org.br; last accessed 10/11/2011 2 http://www.cs.princeton.edu/~schapire/maxent/; last accessed 10/11/2011 3 http://openmodeller.sourceforge.net/; last accessed 10/11/2011 frontiers of biogeography 4.1, 2012 — © 2012 the authors; journal compilation © 2012 The International Biogeography Society

BackgroundThe Quaternary had worldwide consequences in forming the contemporary diversity of many populations, species and communities, which is characterized by marked climatic oscillations between glacial and interglacial periods. The origin and evolution of biodiversity in mountainous areas are highly dependent on historical orogenesis and associated climatic changes. The Chinese grouse Tetrastes sewerzowi is a forest-dwelling species endemic to the mountains to the east of the Qinghai–Tibet Plateau, which has been listed as Near Threatened with a decreasing trend by the IUCN because of ongoing deforestation and fragmentation of coniferous forests. It is important to place current population status into a broader ecological and evolutionary context to understand their demographic history.ResultsAnalyses of the Chinese Grouse genome revealed fluctuations throughout the Pleistocene in effective population size. Populations decreased during early to middle Pleistocene but showed an expansion during late Pleistocene which was then followed by a sharp decline during the last glacial maximum (LGM). Ecological niche modeling indicated that a suitable habitat shift between high altitude regions to low altitude regions was due to a changing climate. This result parallels patterns of population size change in Chinese Grouse estimated from PSMC modelling, which suggested an expansion in population size from the last interglacial period (LIG) and then a peak and a bottleneck occurring at the last glacial maximum (LGM). Furthermore, the present-day distribution of Chinese Grouse is greatly reduced and fragmented. It will likely become even more fragmented in the future since coniferous forest cover is threatened in the region of their distribution and the availability of such habitat restricts their ecological niche.ConclusionsThe Chinese Grouse have experienced substantial population size changes from the beginning to the LIG and reached a peak before the LGM. A sharp decrease and bottleneck occurred during the LGM, when the coniferous forests were subjected to extensive loss. The results inferred from the whole genome sequencing and species distribution models both support historical population fluctuations. The distribution of the Chinese Grouse is strongly dependent on the coniferous forest cover. To protect the fragmented coniferous forests is an essential action to protect the Chinese Grouse.

The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species’ ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model’s output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.

AimSpecies distributions have been continuously adjusting to changing climatic conditions throughout the glacial–interglacial cycles. In the marine realm, evidence suggests that latitudinal range shifts, involving both spatial expansions and trailing‐edge contractions, may represent a common response to climatic oscillations. The biogeographical histories of coastal organisms, however, have been inferred primarily using molecular markers, potentially overlooking past range dynamics beyond contemporary rear edges. In this study we combined species distribution models (SDMs) and mitochondrial DNA (mtDNA) data to investigate the biogeographical history of the high‐intertidal seaweed Pelvetia canaliculata. We investigated the hypotheses that its distribution is set by both marine and terrestrial climates and that its range has shifted northwards since the Last Glacial Maximum.LocationNorth‐eastern Atlantic intertidal from Portugal to Norway.MethodsIn total, 432 individuals at 27 sites covering the extant range of Pelvetia canaliculata were sampled and sequenced for a c. 500 bp mtDNA intergenic spacer. A niche model was developed using marine and terrestrial variables. Range dynamics were reconstructed based on the geographical patterns of genetic variation and on the SDM projections for the Last Glacial Maximum (LGM) and the present.ResultsThe best distribution models incorporated both marine and terrestrial variables. LGM projections revealed suitable habitat between southern Morocco and the periglacial shorelines of the Celtic Sea. Pelvetia canaliculata exhibited a highly structured phylogeography, being subdivided into three largely disjunct lineages, two of them endemic to Iberia. The central/northern European lineage exhibited the highest haplotypic diversity and showed a consistent decline in nucleotide diversity and haplotypic richness at higher latitudes.Main conclusionsAssuming species/climate equilibrium, SDMs supported the hypothesis of a post‐glacial latitudinal range shift. Molecular variation revealed contrasting demographic behaviours in Iberian and periglacial regions. In Iberia the low haplotypic diversity suggested complex range dynamics that are not fully captured by SDM projections. Periglacial regions, identified as the source of poleward colonization, were inferred to have been comparatively more stable. Greater attention should be paid to marine range dynamics at low‐latitude range margins, particularly in genetically structured low‐dispersal species exhibiting southern endemic variation.

Can remote sensing of land cover improve species distribution modelling?

Current and future applications of species distribution and ecological niche modelling for the study of ticks and tick-borne pathogens.

Increasing forest wildfires in Portugal remain a growing concern since forests in the Mediterranean region are vulnerable to recent global warming and reduction of precipitation. Therefore, a long-term negative effect is expected on the vegetation, with increasing drought and areas burnt by fires. The strawberry tree (Arbutus unedo L.) is particularly used in Portugal to produce a spirit by processing its fruits and is the main income for forestry owners. Other applications are possible due to the fruit and leaves’ anti-oxidant properties and bioactive compounds production, with a potential for clinical and food uses. It is a sclerophyllous plant, dry-adapted and fire resistant, enduring the Mediterranean climate, and recently considered as a possibility for afforestation, to intensify forest discontinuity where pines and eucalypts monoculture dominate the region. To improve our knowledge about the species’ spatial distribution we used 318 plots (the centroid of a 1 km2 square grid) measuring the species presence and nine environmental attributes. The seven bioclimatic variables most impacting on the species distribution and two topographic features, slope and altitude, were used. The past, current and future climate data were obtained through WorldClim. Finally, the vulnerability of the strawberry tree to the effects of global climate change was examined in the face of two emission scenarios (RCP 4.5 and 8.5), to predict distribution changes in the years 2050 and 2070, using a species distribution models (MaxEnt). The reduction of suitable habitat for this species is significant in the southern regions, considering the future scenarios of global warming. Central and northern mountainous regions are putative predicted refuges for this species. Forest policy and management should reflect the impact of climate change on the usable areas for forestry, particularly considering species adapted to the Mediterranean regions and wildfires, such as the strawberry tree. The distribution of the species in the Last Glacial Maximum (LGM) and Mid-Holocene (MH) agrees with previous genetic and paleontological studies in the region, which support putative refuges for the species. Two in the southern and coastal-central regions, since the LGM, and one in the east-central mountainous region, considered as cryptic refugia.

Modeling current and future species distribution of breeding birds as regional essential biodiversity variables (SD EBVs): A bird perspective in Swiss Alps

The success of a species in future climate change scenarios depends on its morphological, physiological, and demographic adaptive responses to changing climate. The existence of threatened species against climate adversaries is constrained due to their small population size, narrow genetic base, and narrow niche breadth. We examined if ecological niche model (ENM)-based distribution predictions of species align with their morpho-physiological and demographic responses to future climate change scenarios. We studied three threatened Ilex species, viz., Ilex khasiana Purkay., I. venulosa Hook. f., and I. embelioides Hook. F, withrestricted distribution in Indo-Burma biodiversity hotspot.Demographic analysis of the natural populations of each species in Meghalaya, Indiarevealed an upright pyramid suggesting a stable population under the present climate scenario. I. khasiana was confined to higher elevations only while I. venulosa and I. embelioides had wider altitudinal distribution ranges. The bio-climatic niche of I. khasiana wasnarrow, while the other two species had relatively broader niches. The ENM-predicted potential distribution areas under the current (2022) and future (2050) climatic scenarios (General Circulation Models (GCMs):IPSL-CM5A-LR and NIMR-HADGEM2-AO) revealed that the distribution of highly suitable areas for the most climate-sensitive I. khasiana got drastically reduced. In I. venulosa and I. embelioides, there was an increase in highly suitable areas under the future scenarios. The eco-physiological studies showed marked variation among the species, sites, and treatments (p < 0.05), indicating the differential responses of the three species to varied climate scenarios, but followed a similar trend in species performance aligning with the model predictions.

Ecological niche modelling is useful in estimating the environmental requirements of species and, by extension, can also estimate their distributional areas. For most cacti, ecological niche modelling and comparisons between species have only been performed for a set of variables mainly associated with temperature and precipitation. To expand environmental predictors in addition to climate variables, we use topographic and edaphic variables. The aims of this study were to determine which environmental factors influence the geographical distribution of the P. leucocephalus species group s.s. from Mexico and Central America, to build species distribution models, and to assess whether species have different climatic preferences. Based on ecological niche modelling, the main environmental variables that contribute to the distribution of species and the similarities or differences in ecological niches between species were inferred using Maxent and ENMTools. The results revealed that the studied species had different responses to environmental variables, resulting in a unique combination of conditions for each species, showing only six environmental variables in common. In general, variables with the greatest contributions to the models were climatic, followed by edaphic and topographic variables. The results of the quantification of niches between species showed that there was less than 0.5 overlap in Schoener’s D values, suggesting niche divergence for the group species but in environments more similar than would be expected by random chance. Although species shared affinities for seasonally dry tropical forests, the importance of preferences for different sets of environmental variables by each species was clear. In addition, niche divergence between closely related species of the P. leucocephalus group s.s. is concordant with the previous delimitation at the species level.

Effective biodiversity conservation requires knowledge of species' distributions across large areas, yet prevalence data for marine sessile species is scarce, with traditional variables often unavailable at appropriate temporal and spatial resolutions. As marine organism distributions generally depend on terrain heterogeneity, topographic variables derived from digital elevation models (DEMs) can be useful proxies in ecological modelling, given appropriate spatial resolutions. Here, we use three reef-building Acropora coral species across the Great Barrier Reef, Australia, in a case study to (1) assess high-resolution bathymetry DEM sources for accuracy, (2) harness their derived topographic variables for regional coral species distribution models (SDMs), and (3) develop a transferable framework to produce, select and integrate multi-resolution variables into marine spatial models. For this, we obtained and processed three distinct bathymetric digital depth models that we treat as DEMs, which are available across the GBR extent: (i) Allen Coral Atlas (ACA) at 10 m, (ii) DeepReef at 30 m and (iii) DeepReef at 100 m. We generalised the three DEMs to multiple nested spatial resolutions (15 m-120 m) and derived the same eight topographic variables to assess SDM sensitivity to bathymetry source and spatial resolution. The ACA and DeepReef DEMs shared similar vertical accuracies, each producing topographic variables relevant to marine SDMs. Slope and vector ruggedness measure (VRM), capturing hydrodynamic movement and shelter or exposure, were the most relevant variables in SDMs of all three species. Interestingly, variables at the finest resolution (15 m) were not always the most relevant for producing accurate coral SDMs, with optimal resolutions between 15 and 60 m depending on the variable type and species. Using multi-resolution topographic variables in SDMs provided nuanced insights into the multiscale drivers of regional coral distributions. Drawing from this case study, we provide a practical and transferable framework to facilitate the adoption of multiscale SDMs for better-informed conservation and management planning.