Browsing by Subject "species distribution models"

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  • Selwood, Katherine E.; Wintle, Brendan A.; Kujala, Heini (2019)
    The importance of expert input to spatial conservation prioritization outcomes is poorly understood. We quantified the impacts of refinements made during consultation with experts on spatial conservation prioritization of Christmas Island. There was just 0.57 correlation between the spatial conservation priorities before and after consultation, bottom ranked areas being most sensitive to changes. The inclusion of a landscape condition layer was the most significant individual influence. Changes (addition, removal, modification) to biodiversity layers resulted in a combined 0.2 reduction in correlation between initial and final solutions. Representation of rare species in top ranked areas was much greater after expert consultation; representation of widely distributed species changed relatively little. Our results show how different inputs have notably different impacts on the final plan. Understanding these differences helps plan time and resources for expert consultation.
  • Muscatello, Angela; Elith, Jane; Kujala, Heini (2021)
    Species distribution models (SDMs) are increasingly used in conservation and land use planning as inputs to describe biodiversity patterns. SDMs can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting and evaluation all alter the resulting predictions. Commonly, the true distribution of species is not known, nor is there independent data to verify which SDM variant to choose. Such model uncertainty is concerning to planners. We analysed how 11 routine decisions about model complexity, predictors, bias treatment and thresholding of predicted values altered conservation priority patterns across 25 species. While all SDM variants had good model performance (AUC>0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not deal with bias or to apply binary thresholds to predicted values, where on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively), while using fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modelling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model‐based uncertainty and quantify the relative impacts of SDM building decisions. When the truth about the best SDM approach and conservation plan is not known, solving uncertainty or spending time considering alterative options is most important for those decisions that change plans the most.
  • Niskanen, Annina Kaisa Johanna; Niittynen, Pekka; Aalto, Juha; Väre, Henry; Luoto, Miska (2019)
    Aim: Species' biogeographical patterns are already being altered by climate change. Here, we provide predictions of the impacts of a changing climate on species' geographical ranges within high-latitude mountain flora on a sub-continental scale. We then examined the forecasted changes in relation to species' biogeographic histories. Location: Fennoscandia, Northern Europe (55-72 degrees N). Methods: We examined the sensitivity of 164 high-latitude mountain species to changing climate by modelling their distributions in regard to climate, local topography and geology at a 1 km(2) resolution. Using an ensemble of six statistical modelling techniques and data on current (1981-2010) and future (2070-2099) climate based on three Representative Concentration Pathways (RCPs 2.6, 4.5, 8.5), we developed projections of current and future ranges. Results: The average species richness of the mountain flora is predicted to decrease by 15%-47% per 1 km(2) cell, depending on the climate scenario considered. Arctic flora is projected to undergo severe range loss along with non-poleward range contractions, while alpine flora is forecasted to find suitable habitat in a warmer North. A substantial majority (71%-92%) of the studied species are projected to lose more than half of their present range by the year 2100. Species predicted to lose all suitable habitat had ranges centred in the northernmost (>68 degrees N) part of continental Europe. Main conclusions: Climate change is predicted to substantially diminish the extent and richness of Europe's high-latitude mountain flora. Interestingly, species' biogeographic histories affect their vulnerability to climate change. The vulnerability of true Arctic and endemic species marks them as highly important for conservation decisions.
  • Jorcin, Pierre; Barthe, Laurent; Berroneau, Matthieu; Dore, Florian; Geniez, Philippe; Grillet, Pierre; Kabouche, Benjamin; Movia, Alexandre; Naimi, Babak; Pottier, Gilles; Thirion, Jean-Marc; Cheylan, Marc (2019)
    The Ocellated Lizard, Timon lepidus (Daudin 1802) occupies the Mediterranean regions of southwestern Europe (Portugal, Spain, France, and the extreme northwest of Italy). Over the last decades, a marked decline in its population has been observed, particularly on the northern edge of its distribution. As a result, it is currently considered a threatened species, especially in France and Italy. In France, a national action plan for its conservation has been put in place. In this study, ecological niche modelling (ENM) was carried out over the entire area of France in order to evaluate the species' potential distribution, more accurately define its ecological niche, guide future surveys, and inform land use planning so this species can be better taken into consideration. The modelling used data representing 2,757 observation points spread over the known range of the species, and 34 ecogeographical variables (climate, topography, and vegetation cover) were evaluated. After removing correlated variables, models were fitted with several combinations of variables using eight species distribution model (SDM) algorithms, and then their performance was assessed using three model accuracy metrics. Iterative trials changing the input variables were used to obtain the best model. The optimized model included nine determining variables. The results indicate the presence of this species is linked primarily to three climate variables: precipitation in the driest month, precipitation seasonality, and mean temperature in the driest quarter. The model was checked by a sample dataset that was not used to fit the model, and this validation dataset represented 25% of the overall field observations. Of the known occurrence locations kept aside to check the results, 94% fell within the presence area predicted by the modelled map with a presence probability greater than 0.7, and 90% fell within the area with a presence probability ranging from 0.8 to 1, which represents a very high predictive value. These results indicate that the models closely matched the observed distribution, suggesting a low impact of either geographical factors (barriers to dispersal), historical factors (dispersal process), or ecological factors (e.g., competition, trophic resources). The overlap between the predicted distribution and protected areas for this species reveals that less than 1% of the potential distribution area is protected by strong regulatory measures (e.g., national parks and natural reserves). The knowledge obtained in this study allows us to recommend some guidelines that would favor the conservation of this species.
  • Lehikoinen, Aleksi; Virkkala, Raimo (2016)
    There is increasing evidence that climate change shifts species distributions towards poles and mountain tops. However, most studies are based on presence-absence data, and either abundance or the observation effort has rarely been measured. In addition, hardly any studies have investigated the direction of shifts and factors affecting them. Here, we show using count data on a 1000km south-north gradient in Finland, that between 1970-1989 and 2000-2012, 128 bird species shifted their densities, on average, 37km towards the north north-east. The species-specific directions of the shifts in density were significantly explained by migration behaviour and habitat type. Although the temperatures have also moved on average towards the north north-east (186km), the species-specific directions of the shifts in density and temperature did not correlate due to high variation in density shifts. Findings highlight that climate change is unlikely the only driver of the direction of species density shifts, but species-specific characteristics and human land-use practices are also influencing the direction. Furthermore, the alarming results show that former climatic conditions in the north-west corner of Finland have already moved out of the country. This highlights the need for an international approach in research and conservation actions to mitigate the impacts of climate change.
  • Garate-Escamilla, Homero; Hampe, Arndt; Vizcaino-Palomar, Natalia; Robson, T. Matthew; Garzon, Marta Benito (2019)
    Aim To better understand and more realistically predict future species distribution ranges, it is critical to account for local adaptation and phenotypic plasticity in populations' responses to climate. This is challenging because local adaptation and phenotypic plasticity are trait-dependent and traits covary along climatic gradients, with differential consequences for fitness. Our aim is to quantify local adaptation and phenotypic plasticity of vertical and radial growth, leaf flushing and survival across the range of Fagus sylvatica and to estimate the contribution of each trait to explaining the species' occurrence. Location Europe. Time period 1995-2014; 2070. Major taxa studied Fagus sylvatica L. Methods We used vertical and radial growth, flushing phenology and mortality of F. sylvatica L. recorded in the BeechCOSTe52 database (>150,000 trees). Firstly, we performed linear mixed-effect models that related trait variation and covariation to local adaptation (related to the planted populations' climatic origin) and phenotypic plasticity (accounting for the climate of the plantation), and we made spatial predictions under current and representative concentration pathway (RCP 8.5) climates. Secondly, we combined spatial trait predictions in a linear model to explain the occurrence of the species. Results The contribution of plasticity to intraspecific trait variation is always higher than that of local adaptation, suggesting that the species is less sensitive to climate change than expected; different traits constrain beech's distribution in different parts of its range: the northernmost edge is mainly delimited by flushing phenology (mostly driven by photoperiod and temperature), the southern edge by mortality (mainly driven by intolerance to drought), and the eastern edge is characterized by decreasing radial growth (mainly shaped by precipitation-related variables in our model); considering trait covariation improved single-trait predictions. Main conclusions Population responses to climate across large geographical gradients are dependent on trait x environment interactions, indicating that each trait responds differently depending on the local environment.
  • Rissanen, Tuuli Katariina; Niittynen, Pekka; Soininen, Janne; Luoto, Miska (2021)
    Aim To examine how snow cover and permafrost affect plant species distributions at a subcontinental extent. Location Mountain realm of Fennoscandia, northern Europe. Time period Species data from 1 January 1990-25 February 2019. Major taxa studied Arctic-alpine and boreal vascular plants. Methods We examined the effect of snow persistence and permafrost occurrence on the distributions of arctic-alpine and boreal plant species while controlling for climate, topography and geological factors. Data comprised 475,811 observations from 671 species in the Fennoscandian mountains. We investigated the relationships between species distributions and environmental variables using four modelling methods and ensemble modelling building on both non-spatial and spatial models. Results Snow persistence was the most important driver of plant species distributions, with the greatest variable importance for both arctic-alpine (38.2%) and boreal (49.9%) species. Permafrost had a consistent minor effect on the predicted distributions. Arctic-alpine plants occur in areas with long snow persistence and permafrost, whereas boreal species showed the opposite habitat preferences. Main conclusions Our results highlight the importance of snow persistence in driving the distribution of vascular plant species in cold environments at a subcontinental scale. The notable contribution of the cryosphere to plant species distribution models indicates that the inclusion of snow information in particular may improve our understanding and model predictions of biogeographical patterns in cold regions.