Browsing by Subject "species distribution modelling"

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  • Pajunen, Virpi; Jyrkänkallio-Mikkola, Jenny; Luoto, Miska; Soininen, Janne (2019)
    Species occurrences are influenced by numerous factors whose effects may be context dependent. Thus, the magnitude of the effects and their relative importance to species distributions may vary among ecosystems due to anthropogenic stressors. To investigate context dependency in factors governing microbial bioindicators, we developed species distribution models (SDMs) for epilithic stream diatom species in human-impacted and pristine sites separately. We performed SDMs using boosted regression trees for 110 stream diatom species, which were common to both data sets, in 164 human-impacted and 164 pristine sites in Finland (covering similar to 1,000 km, 60 degrees to 68 degrees N). For each species and site group, two sets of models were conducted: climate model, comprising three climatic variables, and full model, comprising the climatic and six local environmental variables. No significant difference in model performance was found between the site groups. However, climatic variables had greater importance compared with local environmental variables in pristine sites, whereas local environmental variables had greater importance in human-impacted sites as hypothesized. Water balance and conductivity were the key variables in human-impacted sites. The relative importance of climatic and local environmental variables varied among individual species, but also between the site groups. We found a clear context dependency among the variables influencing stream diatom distributions as the most important factors varied both among species and between the site groups. In human-impacted streams, species distributions were mainly governed by water chemistry, whereas in pristine streams by climate. We suggest that climatic models may be suitable in pristine ecosystems, whereas the full models comprising both climatic and local environmental variables should be used in human-impacted ecosystems.
  • Farstad, Miia (Helsingin yliopisto, 2021)
    Due to the harsh conditions in high latitude alpine and arctic regions, climate or land use changes make them very vulnerable. Thus, it is vital to study the habitats of these regions and increase our understanding of what factors impact species distributions. Species distribution modelling can be used to predict possible habitats for species and further inspect the relationships between different environmental variables and species. Generally, these species distribution models have been created using variables describing the topographical and climatic conditions of the study area. Recently there has been more evidence supporting the inclusion of biotic variables to species distribution models at all scales. Including biotic variables can be difficult, as these relationships can be challenging to quantify. This study uses the Normalized Difference Vegetation Index (NDVI) as a surrogate for plant biomass, thus representing biotic interactions. This study aims to answer what are the relationships between environmental variables and the predicted distributions and will including a biotic variable improve the species distribution models. The study data includes observational data from 683 arctic and alpine plant species from Norway, Sweden, and Finland. The observation data were collected from the three national databanks of Norway, Sweden and Finland and completed with observations from the Global Biodiversity Information Facility and observation data collected by the BioGeoClimate Modelling Lab. The cohesive study area was outlined with the biogeographical regions defined by the European Environment Agency. Overall, six environmental variables are used in this study: annual mean temperature, the maximum temperature of the warmest month, annual precipitation, elevation difference in a cell, bedrock class, and NDVI. The NDVI data was gathered by NASA’s MODIS sensors. The observations and the environmental variables were projected into a grid consisting of 1 x 1 km cells covering the whole study area. This study uses the ensemble modelling technique with four individual modelling methods: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM) and random forests (RF). The modelling process consisted of two modelling rounds so that the impact of NDVI could be evaluated. The first modelling round included all the environmental variables except NDVI (the topoclimate model) and the second modelling round included all the environmental variables (the full model). The two temperature variables, annual mean temperature and the maximum temperature of the warmest month, had the highest mean variable importance values. With the topoclimate model, annual precipitation ranked third with the rest of the climate variables, but when NDVI was added to the models, it rose above annual precipitation. Overall, among the studied arctic and alpine species, the variable importance values of both the edaphic and topographical variables were low. In general, both the topoclimate models and full models performed very well. The mean AUC- and TSS-values were all higher for the full models, indicating that including a biotic variable improved the models. When the binary predictions of both modelling rounds were compared, it was clear that NDVI refined the projected distributions for most species. The results from this study confirm the discovery that including a biotic variable, such as NDVI, has the potential to increase the predictive power of species distribution models. One of the main problems with including biotic variables in species distribution models has been the difficulty of quantifying biotic interactions. NDVI can thus be a promising tool to overcome these difficulties, as it is one of the most direct variables to describe ecosystem productivity, can be acquired at various scales, and as remotely sensed data, it can also cover areas that are difficult to access.
  • Mammola, Stefano; Souza, Maysa Fernanda Villela Rezende; Isaia, Marco; Ferreira, Rodrigo Lopes (2021)
    Aim Historically, research on global distribution patterns has mostly concentrated on conspicuous organisms and thus a large proportion of biodiversity on Earth remains unmapped. We examined the global distribution of palpigrades, a poorly studied group of low dispersive arachnids specialized to subterranean life. We asked what is their typical range size, the ecological factors driving their distributions, and to what extent sampling bias may influence the observed patterns. Location Global. Taxon Palpigrades (Arachnida: Palpigradi) in the genus Eukoenenia. Methods We assembled a database of over 1000 localities and referring to 57 soil- and 69 cave-adapted palpigrades. We tested for differences in range sizes of soil- and cave-adapted species. We used variance partitioning analysis to explore the contribution of climate, nutrient availability and geology in driving observed distributions. Finally, we verified the potential correlation between the number of occurrence records and the number of palpigrades' researchers. Results Europe and Brazil emerged as centres of diversification of cave-adapted palpigrades. Conversely, the diversity of soil-adapted species was distributed over a broader geographical expanse, mainly in the Southern Hemisphere. Both cave and soil species had narrow distribution ranges, with a median value of 0.01 km(2); only a few parthenogenetic species were distributed over multiple continents. The distribution of cave- and soil-adapted palpigrades was primarily explained by climatic conditions, and secondarily by nutrient and habitat availability. In the Alps, the distribution of cave-adapted species also bears the signature of historical events related to glaciation cycles. We observed, however, a pronounced people-species correlation, suggesting that the observed patterns are not generalizable to poorly explored areas. Main conclusions Our study highlights enormous gaps in current knowledge about the biogeography of palpigrades. Even if the information is largely incomplete and biased, we show how data can be harnesses to draw a preliminary picture of the global distribution patterns of palpigrades. Thus, we offer a jumping-off point for future studies on the macroecology and conservation of poorly known organisms.
  • Adamo, Martino; Mammola, Stefano; Noble, Virgile; Mucciarelli, Marco (2020)
    We studied the ecology, distribution, and phylogeography of Tephroseris balbisiana, a rare plant whose range is centered to the South-Western Alps. Our aim was to assess the extent of intraspecific variability within the nominal species and the conservation status of isolated populations. We studied genetic diversity across the whole species range. We analyzed leaf traits, which are distinctive morphological characters within the Tephroseris genus. A clear pattern of genetic variation was found among populations of T. balbisiana, which clustered according to their geographic position. On the contrary, there was a strong overlap in the morphological space of individuals across the species' range, with few peripheral populations diverging in their leaf morphology. Studying habitat suitability by means of species distribution models, we observed that T. balbisiana range is primarily explained by solar radiation and precipitation seasonality. Environmental requirements could explain the genetic and morphological uniformity of T. balbisiana in its core distribution area and justify genetic, morphological, and ecological divergences found among the isolated populations of the Apennines. Our findings emphasize the need to account for the whole diversity of a species, comprising peripheral populations, in order to better estimate its status and to prioritize areas for its conservation.
  • Tikhonov, Gleb; Opedal, Oystein H.; Abrego, Nerea; Lehikoinen, Aleksi; de Jonge, Melinda M. J.; Oksanen, Jari; Ovaskainen, Otso (2020)
    Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio-temporal context of the study, providing predictive insights into community assembly processes from non-manipulative observational data of species communities. The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user-friendly r implementation. We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio-temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single-species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence-absence data. The package, along with the extended vignettes, makes JSDM fitting and post-processing easily accessible to ecologists familiar with r.
  • Zhang, Zhixin; Mammola, Stefano; Xian, Weiwei; Zhang, Hui (2020)
    Aim Species distribution models (SDMs) are an effective tool to explore the potential distribution of terrestrial, freshwater and marine organisms; however, SDMs have been seldom used to model ichthyoplankton distributions, and thus, our understanding of how larval stages of fishes will respond to climate change is still limited. Here, we developed SDMs to explore potential impacts of climate change on habitat suitability of ichthyoplankton. Location Yangtze Estuary, China. Methods Using long-term ichthyoplankton survey data and a large set of marine predictor variables, we developed ensemble SDMs for five abundant ichthyoplankton species in the Yangtze Estuary (Coilia mystus, Hypoatherina valenciennei, Larimichthys polyactis, Salanx ariakensis and Chelidonichthys spinosus). Then, we projected their habitat suitability under present and future climate conditions. Results The ensemble SDMs had good predictive performance and were successful in estimating the known distributions of the five species. Model projections highlighted two contrasting patterns of response to future climates: while C. mystus will likely expand its range, the ranges of the other four species will likely contract and shift northward. Main conclusions According to our SDM projections, the five ichthyoplankton species that we tested in the Yangtze Estuary are likely to respond differently to future climate changes. These projected different responses seemingly reflect the differential functional attributes and life-history strategies of these species. To the extent that climate change emerges as a critical driver of the future distribution of these species, our findings provide an important roadmap for designing future conservation strategies for ichthyoplankton in this region.
  • doninck, Jasper Van; Jones, Mirkka M.; Zuquim, Gabriela; Ruokolainen, Kalle; Moulatlet, Gabriel M.; Sirén, Anders; Cárdenas, Glenda; Lehtonen, Samuli; Tuomisto, Hanna (2020)
    Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.
  • Pavlek, Martina; Mammola, Stefano (2021)
    Abstract Aim To disentangle the role of evolutionary history, competition and environmental filtering in driving the niche evolution of four closely related subterranean spiders, with the overarching goal of obtaining a mechanistic description of the factors that determine species' realized distribution in simplified ecological settings. Location Dinaric karst, Balkans, Europe. Taxon Dysderidae spiders (Stalita taenaria, S. pretneri, S. hadzii and Parastalita stygia). Methods We resolved phylogenetic relationships among species and modelled each species' distribution using a set of climatic and habitat variables. We explored the climatic niche differentiation among species with n-dimensional hypervolumes and shifts in their trophic niche using morphological traits related to feeding specialization. Results Climate was the primary abiotic factor explaining our species' distributions, while karstic and soil features were less important. Generally, there was a high niche overlap among species, reflecting their phylogenetic relatedness, but on a finer scale, niche shifts explained the realized distribution patterns. Trophic interaction was another important factor influencing species distributions ? the non-overlapping distributions of three morphologically indistinguishable Stalita species is seemingly the outcome of competitive exclusion dynamics. The distribution of the fourth species, Parastalita stygia, overlaps with that of the other species, with several instances of coexistence within caves. As inferred from the morphology of the mouthparts, the mechanism that minimizes interspecific competition is the shift in the trophic niche of P. stygia towards a more specialized diet. Main conclusions We showed that similarity in niches only partly correlated with the phylogenetic distance among species, and that overlaps in species distributions are possible only when a parallel shift in diet occurs. Our work emphasized how even simplified environments still maintain the potential for diversification via niche differentiation. Ultimately, we provide an ecological explanation for the diversification of life in an important hotspot of subterranean diversity.
  • Gargiulo, Roberta; Pironon, Samuel; Zheleznaya, Ekaterina; Sanchez, Michele D.; Balazs, Zoltan R.; Podar, Dorina; Wilkinson, Timothy; Jäkäläniemi, Anne; Kull, Tiiu; Väre, Henry; Fay, Michael F. (2019)
    Aim We investigated the phylogeographical history of a clonal-sexual orchid, to test the hypothesis that current patterns of genetic diversity and differentiation retain the traces of climatic fluctuations and of the species reproductive system. Location Europe, Siberia and Russian Far East. Taxon Cypripedium calceolus L. (Orchidaceae). Methods Samples (>900, from 56 locations) were genotyped at 11 nuclear microsatellite loci and plastid sequences were obtained for a subset of them. Analysis of genetic structure and approximate Bayesian computations were performed. Species distribution modelling was used to explore the effects of past climatic fluctuations on the species range. Results Analysis of genetic diversity reveals high heterozygosity and allele diversity, with no geographical trend. Three genetic clusters are identified with extant gene pools derived from ancestral demes in glacial refugia. Siberian populations exhibit different plastid haplotypes, supporting an early divergence for the Asian gene pool. Demographic results based on genetic data are compatible with an admixture event explaining differentiation in Estonia and Romania and they are consistent with past climatic dynamics inferred through species distribution modelling. Current population differentiation does not follow isolation by distance model and is compatible with a model of isolation by colonization. Main conclusions The genetic differentiation observed today in C. calceolus preserves the signature of climatic fluctuations in the historical distribution range of the species. Our findings support the central role of clonal reproduction in the reducing loss of diversity through genetic drift. The dynamics of the clonal-sexual reproduction are responsible for the persistence of ancestral variation and stability during glacial periods and post-glacial expansion.
  • Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Remi; Dray, Stephane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frederic; Merigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frederic; Munoz, Francois; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric (2014)
    The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.
  • Lappalainen, Juho; Virtanen, Elina A.; Kallio, Kari; Junttila, Sofia; Viitasalo, Markku (Elsevier, 2019)
    Estuarine, Coastal and Shelf Science
    Canopy-forming macroalgae living on rocky bottoms provide valuable ecosystem services but long-term eutrophication has narrowed their distribution and depth zonation in the Baltic Sea. The spatial distribution of macroalgae is shaped by many factors, such as light, salinity, nutrients and wave exposure. In addition, the lack of suitable hard substrates limits the distribution of algae in many areas. Analysing how the spatial distribution of macroalgae is modified by changes in environmental conditions is relevant for focusing management actions. To quantify the resultant distribution under various environmental and management scenarios, both current environmental conditions and substrate limitation need to be considered. We estimated the potential distribution area of bladderwrack Fucus spp. under 11 water transparency scenarios in 9 Finnish sea areas differing in morphology and eutrophication status. The prevailing averaged long-term water transparency conditions were interpreted from satellite images. Ten scenarios were calculated based on hypothetical changes in euphotic depth from −50% to +50% of the present. Species distribution modelling was used to assess the potential distribution areas of Fucus. In addition, to quantify the influence of substrate limitation, we estimated the average substrate limitation with two correction methods: (i) by using field data from underwater videos within the predicted distribution areas and (ii) by using a habitat model representing the distribution of reefs (i.e. rocky bottoms) in the study area. The decrease of euphotic depth by 50% from the present level narrowed the distribution area of Fucus by 24–53% in the Southwestern archipelago, 55–70% in the Gulf of Finland, 37–66% in the Bothnian Sea and 59–100% in Kvarken. An increase in euphotic depth significantly broadened the spatial distribution of Fucus. Decreasing share of suitable hard substrate along depth gradient however hinders broadening of the distribution area. If all areas were suitable for growth, a 50% increase in euphotic depth would expand the distribution area by 124–803%, depending on area. When only suitable substrates were taken into account, this percentage remained at 9–270%. We conclude that substrate limitation needs to be taken into account when estimating macroalgal species distribution in the marine environment. We show how this can be done also when comprehensive bottom substrate maps are not available. Our results are valuable when setting the targets for environmental management plans, and for balancing the local management measures in a cost effective manner. Highlights • Benthic light conditions affect the distribution of canopy-forming macroalgae Fucus. • Also substrate limits the distribution and zonation of Fucus. • Scenario modelling and substrate correction methods were utilised. • Sea areas differ in substrate composition which affects potential distribution area. • Substrate limitation is more pronounced in inner than in outer archipelago.
  • Titeux, Nicolas; Maes, Dirk; Van Daele, Toon; Onkelinx, Thierry; Heikkinen, Risto K.; Romo, Helena; Garcia-Barros, Enrique; Munguira, Miguel L.; Thuiller, Wilfried; van Swaay, Chris A. M.; Schweiger, Oliver; Settele, Josef; Harpke, Alexander; Wiemers, Martin; Brotons, Lluis; Luoto, Miska (2017)
    Aim: Species distribution models built with geographically restricted data often fail to capture the full range of conditions experienced by species across their entire distribution area. Using such models to predict distribution shifts under future environmental change may, therefore, produce biased projections. However, restricted-scale models have the potential to include a larger sample of taxa for which distribution data are available and to provide finer-resolution projections that are better applied to conservation planning than the forecasts of broad-scale models. We examine the circumstances under which the projected shifts in species richness patterns derived from restricted-scale and broad-scale models are most likely to be similar. Location: Europe. Methods: The distribution of butterflies in Finland, Belgium/Netherlands and Spain was modelled based on restricted-scale (local) and broad-scale (continental) distribution and climate data. Both types of models were projected under future climate change scenarios to assess potential changes in species richness. Results: In Finland, species richness was projected to increase strongly based on restricted-scale models and to decrease slightly with broad-scale models. In Belgium/Netherlands, restricted-scale models projected a larger decrease in richness than broad-scale models. In Spain, both models projected a slight decrease in richness. We obtained similar projections based on restricted-scale and broad-scale models only in Spain because the climatic conditions available here covered the warm part of the distributions of butterflies better than in Finland and Belgium/Netherlands. Main conclusions: Restricted-scale models that fail to capture the warm part of species distributions produce biased estimates of future changes in species richness when projected under climatic conditions with no modern analogue in the study area. We recommend the use of distribution data beyond the boundaries of the study area to capture the part of the species response curves reflecting the climatic conditions that will prevail within that area in the future.