Browsing by Subject "DISTRIBUTION MODELS"

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  • Liao, Ziyan; Zhang, Lin; Nobis, Michael P.; Wu, Xiaogang; Pan, Kaiwen; Wang, Keqing; Dakhil, Mohammed A.; Du, Mingxi; Xiong, Qinli; Pandey, Bikram; Tian, Xianglin (2020)
    Aim As a prominent geographical distribution centre for the dark coniferous forests, mountains of Southwest China (MSWC) is experiencing an unprecedented warming trend, posing severe challenges to the survival of dominant fir (Abies) species. Although plant's migration ability is a prerequisite for its survival in changing environments, it has often been ignored in species distribution models (SDMs). This study aimed to quantify the magnitude and direction of range changes by the year 2080 for six dominant fir species, that is Abies recurvata, Abies faxoniana, Abies squamata, Abies ernestii, Abies forrestii and Abies georgei, with an emphasis on exploring the relationship between migration ability and projected distributions. Location The mountains of Southwest China. Methods We applied the Maximum Entropy (Maxent) algorithm to calibrate ecological niche models and to project the climatically suitable areas (CSAs) of each species under two emission scenarios (RCP 4.5 and RCP 8.5). Additionally, we delimited future species ranges by three migration scenarios (full-, no- and partial-migration scenarios). Results The simulations showed the distinctive responses of the six fir species to anthropogenic climate change (ACC). By 2080, the distribution areas of Abies recurvata were projected to decline only in the no-migration scenario but increase under the full- and partial-migration scenarios, while the other five species were projected to decline in the majority of emission x migration scenarios. Fir species in the southern region were predicted to be more vulnerable to ACC due to the larger losses in CSAs and a stronger effect of the partial-migration scenario on the newly colonized areas of this group. The studied species showed a simulated migration trend (northward and westward) to the interior Qinghai-Tibet Plateau under ACC. Main conclusions Benefits or losses for species under ACC depended on the geographical location, their ecological niches and migration abilities, which provide essential insights for a spatial conservation assessment of biodiversity hotspots in the future.
  • Liao, Ziyan; Chen, Youhua; Pan, Kaiwen; Dakhil, Mohammed A.; Lin, Kexin; Tian, Xianglin; Zhang, Fengying; Wu, Xiaogang; Pandey, Bikram; Wang, Bin; Zimmermann, Niklaus E.; Zhang, Lin; Nobis, Michael P. (2022)
    Background: We aimed to characterise the geographical distribution of Sorensen-based multi-site dissimilarity (beta(sor)) and its underlying true turnover (beta(sim)) and nestedness (beta(sne)) components for Chinese Lauraceae and to analyse their relationships to current climate and past climate change. Methods: We used ensembles of small models (ESMs) to map the current distributions of 353 Lauraceae species in China and calculated beta(sor) and its beta(sim) and beta(sne) components. We tested the relationship between beta(sor), beta s(ne) and beta(sim) with current climate and past climate change related predictors using a series of simultaneous autoregressive (SAR(err)) models. Results: Spatial distribution of beta(sor) of Lauraceae is positively correlated with latitude, showing an inverse relationship to the latitudinal alpha-diversity (species richness) gradient. High beta(sor) occurs at the boundaries of the warm temperate and subtropical zones and at the Qinghai-Tibet Plateau due to high beta(sne). The optimized SAR(err) model explains beta(sor) and beta(sne) well, but not beta(sim). Current mean annual temperature determines beta(sor) and beta(sne) of Lauraceae more than anomalies and velocities of temperature or precipitation since the Last Glacial Maximum. Conclusions: Current low temperatures and high climatic heterogeneity are the main factors explaining the high multi-site beta-diversity of Lauraceae. In contrast to analyses of the beta-diversity of entire species assemblages, studies of single plant families can provide complementary insights into the drivers of beta-diversity of evolutionarily more narrowly defined entities.
  • Milicic, Marija; Vujic, Ante; Cardoso, Pedro (2018)
    Climate change presents a serious threat to global biodiversity. Loss of pollinators in particular has major implications, with extirpation of these species potentially leading to severe losses in agriculture and, thus, economic losses. In this study, we forecast the effects of climate change on the distribution of hoverflies in Southeast Europe using species distribution modelling and climate change scenarios for two time-periods. For 2041-2060, 19 analysed species were predicted to increase their areas of occupancy, with the other 25 losing some of their ranges. For 2061-2080, 55% of species were predicted to increase their area of occupancy, while 45% were predicted to experience range decline. In general, range size changes for most species were below 20%, indicating a relatively high resilience of hoverflies to climate change when only environmental variables are considered. Additionally, range-restricted species are not predicted to lose more area proportionally to widespread species. Based on our results, two distributional trends can be established: the predicted gain of species in alpine regions, and future loss of species from lowland areas. Considering that the loss of pollinators from present lowland agricultural areas is predicted and that habitat degradation presents a threat to possible range expansion of hoverflies in the future, developing conservation management strategy for the preservation of these species is crucial. This study represents an important step towards the assessment of the effects of climate changes on hoverflies and can be a valuable asset in creating future conservation plan, thus helping in mitigating potential consequences.
  • Rouyet, L.; Karjalainen, O.; Niittynen, P.; Aalto, J.; Luoto, Miska; Lauknes, T. R.; Larsen, Y.; Hjort, J. (2021)
    Periglacial environments are characterized by highly dynamic landscapes. Freezing and thawing lead to ground movement, associated with cryoturbation and solifluction. These processes are sensitive to climate change and variably distributed depending on multiple environmental factors. In this study, we used multi-geometry Sentinel-1 Synthetic Aperture Radar Interferometry (InSAR) to investigate the spatial distribution of the mean annual ground velocity in a mountainous landscape in Northern Norway. Statistical modeling was employed to examine how periglacial ground velocity is related to environmental variables characterizing the diverse climatic, geomorphic, hydrological and biological conditions within a 148 km(2) study area. Two-dimensional (2D) InSAR results document mean annual ground velocity up to 15 mm/yr. Vertical and horizontal velocity components in the East-West plane show variable spatial distribution, which can be explained by the characteristics of cryoturbation and solifluction operating differently over flat and sloping terrain. Statistical modeling shows that slope angle and mean annual air temperature variables are the most important environmental factors explaining the distribution of the horizontal and vertical components, respectively. Vegetation and snow cover also have a local influence, interpreted as indicators of the ground material and moisture conditions. The results show contrasted model performance depending on the velocity component used as a response variable. In general, our study highlights the potential of integrating radar remote sensing and statistical modeling to investigate mountainous regions and better understand the relations between environmental factors, periglacial processes and ground dynamics.
  • Mauri, Achille; Girardello, Marco; Strona, Giovanni; Beck, Pieter S. A.; Forzieri, Giovanni; Caudullo, Giovanni; Manca, Federica; Cescatti, Alessandro (2022)
    We present "EU-Trees4F", a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. "EU-Trees4F", can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking.
  • Kotta, Jonne; Vanhatalo, Jarno Petteri; Jänes, Holger; Orav-Kotta, Helen; Rugiu, Luca; Jormalainen, Veijo; Bobsien, Ivo; Viitasalo, Markku; Virtanen, Elina; Nyström Sandman, Antonia; Isaeus, Martin; Leidenberger, Sonja; Jonsson, Per R.; Johannesson, Kerstin (2019)
    Predictive species distribution models are mostly based on statistical dependence between environmental and distributional data and therefore may fail to account for physiological limits and biological interactions that are fundamental when modelling species distributions under future climate conditions. Here, we developed a state-of-the-art method integrating biological theory with survey and experimental data in a way that allows us to explicitly model both physical tolerance limits of species and inherent natural variability in regional conditions and thereby improve the reliability of species distribution predictions under future climate conditions. By using a macroalga-herbivore association (Fucus vesiculosus - Idotea balthica) as a case study, we illustrated how salinity reduction and temperature increase under future climate conditions may significantly reduce the occurrence and biomass of these important coastal species. Moreover, we showed that the reduction of herbivore occurrence is linked to reduction of their host macroalgae. Spatial predictive modelling and experimental biology have been traditionally seen as separate fields but stronger interlinkages between these disciplines can improve species distribution projections under climate change. Experiments enable qualitative prior knowledge to be defined and identify cause-effect relationships, and thereby better foresee alterations in ecosystem structure and functioning under future climate conditions that are not necessarily seen in projections based on non-causal statistical relationships alone.
  • Uusitalo, Ruut Jaael; Siljander, Mika; Culverwell, Christine Lorna; Mutai, Noah; Forbes, Kristian Michael; Vapalahti, Olli; Pellikka, Petri Kauko Emil (2019)
    Mosquitoes are vectors for numerous pathogens, which are collectively responsible for millions of human deaths each year. As such, it is vital to be able to accurately predict their distributions, particularly in areas where species composition is unknown. Species distribution modeling was used to determine the relationship between environmental, anthropogenic and distance factors on the occurrence of two mosquito genera, Culex Linnaeus and Stegomyia Theobald (syn. Aedes), in the Taita Hills, southeastern Kenya. This study aims to test whether any of the statistical prediction models produced by the Biomod2 package in R can reliably estimate the distributions of mosquitoes in these genera in the Taita Hills; and to examine which factors best explain their presence. Mosquito collections were acquired from 122 locations between January–March 2016 along transects throughout the Taita Hills. Environmental-, anthropogenic- and distance-based geospatial data were acquired from the Taita Hills geo-database, satellite- and aerial imagery and processed in GIS software. The Biomod2 package in R, intended for ensemble forecasting of species distributions, was used to generate predictive models. Slope, human population density, normalized difference vegetation index, distance to roads and elevation best estimated Culex distributions by a generalized additive model with an area under the curve (AUC) value of 0.791. Mean radiation, human population density, normalized difference vegetation index, distance to roads and mean temperature resulted in the highest AUC (0.708) value in a random forest model for Stegomyia distributions. We conclude that in the process towards more detailed species-level maps, with our study results, general assumptions can be made about the distribution areas of Culex and Stegomyia mosquitoes in the Taita Hills and the factors which influence their distribution.
  • Visconti, Piero; Bakkenes, Michel; Baisero, Daniele; Brooks, Thomas; Butchart, Stuart H. M.; Joppa, Lucas; Alkemade, Rob; Di Marco, Moreno; Santini, Luca; Hoffmann, Michael; Maiorano, Luigi; Pressey, Robert L.; Arponen, Anni; Boitani, Luigi; Reside, April E.; van Vuuren, Detlef P.; Rondinini, Carlo (2016)
    To address the ongoing global biodiversity crisis, governments have set strategic objectives and have adopted indicators to monitor progress toward their achievement. Projecting the likely impacts on biodiversity of different policy decisions allows decision makers to understand if and how these targets can be met. We projected trends in two widely used indicators of population abundance Geometric Mean Abundance, equivalent to the Living Planet Index and extinction risk (the Red List Index) under different climate and land-use change scenarios. Testing these on terrestrial carnivore and ungulate species, we found that both indicators decline steadily, and by 2050, under a Business-as-usual (BAU) scenario, geometric mean population abundance declines by 18-35% while extinction risk increases for 8-23% of the species, depending on assumptions about species responses to climate change. BAU will therefore fail Convention on Biological Diversity target 12 of improving the conservation status of known threatened species. An alternative sustainable development scenario reduces both extinction risk and population losses compared with BAU and could lead to population increases. Our approach to model species responses to global changes brings the focus of scenarios directly to the species level, thus taking into account an additional dimension of biodiversity and paving the way for including stronger ecological foundations into future biodiversity scenario assessments.
  • Mateo, Ruben G.; Broennimann, Olivier; Normand, Signe; Petitpierre, Blaise; Araujo, Miguel B.; Svenning, Jens-C.; Baselga, Andres; Fernandez-Gonzalez, Federico; Gomez-Rubio, Virgilio; Munoz, Jesus; Suarez, Guillermo M.; Luoto, Miska; Guisan, Antoine; Vanderpoorten, Alain (2016)
    It remains hotly debated whether latitudinal diversity gradients are common across taxonomic groups and whether a single mechanism can explain such gradients. Investigating species richness (SR) patterns of European land plants, we determine whether SR increases with decreasing latitude, as predicted by theory, and whether the assembly mechanisms differ among taxonomic groups. SR increases towards the south in spermatophytes, but towards the north in ferns and bryophytes. SR patterns in spermatophytes are consistent with their patterns of beta diversity, with high levels of nestedness and turnover in the north and in the south, respectively, indicating species exclusion towards the north and increased opportunities for speciation in the south. Liverworts exhibit the highest levels of nestedness, suggesting that they represent the most sensitive group to the impact of past climate change. Nevertheless, although the extent of liverwort species turnover in the south is substantially and significantly lower than in spermatophytes, liverworts share with the latter a higher nestedness in the north and a higher turn-over in the south, in contrast to mosses and ferns. The extent to which the similarity in the patterns displayed by spermatophytes and liverworts reflects a similar assembly mechanism remains, however, to be demonstrated.
  • 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.