Species distribution modelling using bioclimatic variables to determine the impacts of a changing climate on the western ringtail possum (Pseudocheirus occidentals; Pseudocheiridae)

2013 ◽  
Vol 41 (2) ◽  
pp. 176-186 ◽  
Author(s):  
SHAUN W. MOLLOY ◽  
ROBERT A. DAVIS ◽  
EDDIE J. B. VAN ETTEN
Keyword(s):  
Species Distribution ◽  
Tree Species ◽  
Anthropogenic Impacts ◽  
Species Distribution Modelling ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Distribution Models ◽  
Core Habitat ◽  
Bioclimatic Variables ◽  
Ringtail Possum

SUMMARYThe ngwayir (western ringtail possum Pseudocheirus occidentalis) is an arboreal species endemic to south-western Australia. The range and population of this species have been significantly reduced through multiple anthropogenic impacts. Classified as vulnerable, the ngwayir is highly susceptible to extremes of temperature and reduced water intake. Ngwayir distribution was determined using three different species distribution models using ngwayir presence records related to a set of 19 bioclimatic variables derived from historical climate data, overlaid with 2050 climate change scenarios. MaxEnt was used to identify core habitat and demonstrate how this habitat may be impacted. A supplementary modelling exercise was also conducted to ascertain potential impacts on the tree species that are core habitat for ngwayir. All models predicted a reduction of up to 60% in the range of the ngwayir and its habitat, as a result of global warming towards the south-west of the project area, with a mean potential distribution of 10.3% of the total modelled area of 561 059 km2. All three tree species modelled (jarrah, marri and peppermint) were predicted to experience similar contractions in range throughout most of the predicted ngwayir range, although their distributions differed. Populations of ngwayir persisting outside core habitat may indicate potential conservation opportunities.

Hotspots of change in major tree species under climate warming

2020 ◽  
Author(s):  
Flurin Babst ◽  
Richard L. Peters ◽  
Rafel O. Wüest ◽  
Margaret E.K. Evans ◽  
Ulf Büntgen ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Tree Growth ◽  
Species Distribution ◽  
Tree Species ◽  
Habitat Suitability ◽  
Species Distribution Models ◽  
Sensitivity Index ◽  
Distribution Models ◽  
Bioclimatic Variables

<p>Warming alters the variability and trajectories of tree growth around the world by intensifying or alleviating energy and water limitation. This insight from regional to global-scale research emphasizes the susceptibility of forest ecosystems and resources to climate change. However, globally-derived trends are not necessarily meaningful for local nature conservation or management considerations, if they lack specific information on present or prospective tree species. This is particularly the case towards the edge of their distribution, where shifts in growth trajectories may be imminent or already occurring.</p><p>Importantly, the geographic and bioclimatic space (or “niche”) occupied by a tree species is not only constrained by climate, but often reflects biotic pressure such as competition for resources with other species. This aspect is underrepresented in many species distribution models that define the niche as a climatic envelope, which is then allowed to shift in response to changes in ambient conditions. Hence, distinguishing climatic from competitive niche boundaries becomes a central challenge to identifying areas where tree species are most susceptible to climate change.</p><p>Here we employ a novel concept to characterize each position within a species’ bioclimatic niche based on two criteria: a climate sensitivity index (CSI) and a habitat suitability index (HSI). The CSI is derived from step-wise multiple linear regression models that explain variability in annual radial tree growth as a function of monthly climate anomalies. The HSI is based on an ensemble of five species distribution models calculated from a combination of observed species occurrences and twenty-five bioclimatic variables. We calculated these two indices for 11 major tree species across the Northern Hemisphere.</p><p>The combination of climate sensitivity and habitat suitability indicated hotspots of change, where tree growth is mainly limited by competition (low HSI and low CSI), as well as areas that are particularly sensitive to climate variability (low HSI and high CSI). In the former, we expect that forest management geared towards adjusting the competitive balance between several candidate species will be most effective under changing environmental conditions. In the latter areas, selecting particularly drought-tolerant accessions of a given species may reduce forest susceptibility to the predicted warming and drying.</p>

scholarly journals Continent-Wide Tree Species Distribution Models May Mislead Regional Management Decisions: A Case Study in the Transboundary Biosphere Reserve Mura-Drava-Danube

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 330
Author(s):  
Markus Sallmannshofer ◽  
Debojyoti Chakraborty ◽  
Harald Vacik ◽  
Gábor Illés ◽  
Markus Löw ◽  
...  
Keyword(s):  
Species Distribution ◽  
Tree Species ◽  
Large Scale ◽  
Species Distribution Models ◽  
Riparian Forest ◽  
Forest Composition ◽  
Occurrence Probability ◽  
Environmental Predictors ◽  
Distribution Models ◽  
Bioclimatic Variables

The understanding of spatial distribution patterns of native riparian tree species in Europe lacks accurate species distribution models (SDMs), since riparian forest habitats have a limited spatial extent and are strongly related to the associated watercourses, which needs to be represented in the environmental predictors. However, SDMs are urgently needed for adapting forest management to climate change, as well as for conservation and restoration of riparian forest ecosystems. For such an operative use, standard large-scale bioclimatic models alone are too coarse and frequently exclude relevant predictors. In this study, we compare a bioclimatic continent-wide model and a regional model based on climate, soil, and river data for central to south-eastern Europe, targeting seven riparian foundation species—Alnus glutinosa, Fraxinus angustifolia, F. excelsior, Populus nigra, Quercus robur, Ulmus laevis, and U. minor. The results emphasize the high importance of precise occurrence data and environmental predictors. Soil predictors were more important than bioclimatic variables, and river variables were partly of the same importance. In both models, five of the seven species were found to decrease in terms of future occurrence probability within the study area, whereas the results for two species were ambiguous. Nevertheless, both models predicted a dangerous loss of occurrence probability for economically and ecologically important tree species, likely leading to significant effects on forest composition and structure, as well as on provided ecosystem services.

scholarly journals Modeling the Impact of Climate Change on the Distribution of Hagenia Abyssinica in Ethiopia

2020 ◽  
Author(s):  
Tsegaye Gobezie ◽  
Silesh Namomissa ◽  
Tamrat Bekele
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Climate Change Impacts ◽  
Climatic Conditions ◽  
Climate Data ◽  
Distribution Models ◽  
Hagenia Abyssinica ◽  
Bioclimatic Variables ◽  
Conservation Actions ◽  
The Impact

Research Highlights: Hagenia abyssinica is geographically localized, poor regenerated and endangered species in Ethiopia. Ethiopia has been experiencing variability of rainfall and rise in temperature due to the climate change. This study has hypothesized that the suitable areas for the species will be narrowed by the year 2070. Background and Objective The prediction of species distribution models help to implement appropriate conservation actions. The aim of this research was to identify the current and likely future distribution range and suitable areas for the species, and to determine the presence of H. absyssinica in risk in a short-term future. Material and method: To this end, occurrence data, bioclim variables, soil, elevation, and land cover map of Ethiopia were used. MaxEnt was used to predict distribution. Climate change impacts on the distribution of the species was performed using bioclimatic variables of the future climate data, 2070 (average for 2061-2080) was obtained from IPPC5 (CMIP5) at 30 seconds (1km) spatial resolution. The climate data was projected from GCMs, downscaled and calibrated using rcp4.5. Results: Both current and likely future distribution models were excellent and significantly better than random performance. This study has computed 59987 km2 to be the low impact area for the species under current conditions and will remain habitat under future climates and 39025 km2 area has been identified as the possible high impact areas or declining habitat. The model has also determined that 1238724 km2 of the areas are unsuitable at present and for future climates. The current study found that 15751 km2 of the area will be modified as a new suitable area for H. abyssinica due to climate change. Conclusion: Species distribution modeling is essential for the implementation of conservation actions that are compatible with the inevitable changing climatic conditions of the country.

scholarly journals Predicting the current and future distribution of four original plants of Gentianae Macrophyllae Radix in China under climate change scenarios

2021 ◽  
Author(s):  
Houkang Cao ◽  
Xiaohui Ma ◽  
Li Liu ◽  
Shaoyang Xi ◽  
Yanxiu Guo ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Future Climate ◽  
Climate Change Scenarios ◽  
Climate Scenarios ◽  
Distribution Models ◽  
Bioclimatic Variables ◽  
Gentiana Macrophylla ◽  
Suitable Habitats ◽  
The Impact

AbstractThe wild resources of the four original plants (Gentiana crasicaulis Duthie ex Burk, Gentiana daurica Fisch, Gentiana straminea Maxim, and Gentiana macrophylla Pall) of Gentianae Macrophyllae Radix are becoming exhausted. Predicting the distribution under current and future climate scenarios is of significance for the sustainable utilization of resources and ecological protection. In this study, we constructed four species distribution models (SDMs) combining species distribution informations, 19 bioclimatic variables, and the maximum entropy (MaxEnt) model. The results showed that these 4 plants prefer a cool and humid climate. Under the future climate scenarios, the areas of the highly suitable habitats for Gentiana crasicaulis Duthie ex Burk and Gentiana daurica Fisch were likely to decrease, while Gentiana straminea Maxim was likely to expand, and Gentiana macrophylla Pall was less affected. In addition, the centroids of the highly suitable habitats for the four species shifted north or west. Most notably, most of the highly suitable habitats for the four species remained unchanged, which would be the preferred area for semi-artificial cultivation. The above information in this study would contribute to the development of reasonable strategies to reduce the impact of climate change on the four original plants.

Do species distribution models explain spatial structure within tree species ranges?

2009 ◽  
Vol 18 (6) ◽  
pp. 662-673 ◽  
Author(s):  
Daniel Montoya ◽  
Drew W. Purves ◽  
Itziar R. Urbieta ◽  
Miguel A. Zavala
Keyword(s):  
Spatial Structure ◽  
Species Distribution ◽  
Tree Species ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Species Ranges

scholarly journals Using species distribution modelling to determine opportunities for trophic rewilding under future scenarios of climate change

2018 ◽  
Vol 373 (1761) ◽  
pp. 20170446 ◽  
Author(s):  
Scott Jarvie ◽  
Jens-Christian Svenning
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Species Distribution Modelling ◽  
Climatic Conditions ◽  
First Century ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Major Barrier ◽  
Methodological Choices ◽  
Biodiversity And Ecosystem Function

Trophic rewilding, the (re)introduction of species to promote self-regulating biodiverse ecosystems, is a future-oriented approach to ecological restoration. In the twenty-first century and beyond, human-mediated climate change looms as a major threat to global biodiversity and ecosystem function. A critical aspect in planning trophic rewilding projects is the selection of suitable sites that match the needs of the focal species under both current and future climates. Species distribution models (SDMs) are currently the main tools to derive spatially explicit predictions of environmental suitability for species, but the extent of their adoption for trophic rewilding projects has been limited. Here, we provide an overview of applications of SDMs to trophic rewilding projects, outline methodological choices and issues, and provide a synthesis and outlook. We then predict the potential distribution of 17 large-bodied taxa proposed as trophic rewilding candidates and which represent different continents and habitats. We identified widespread climatic suitability for these species in the discussed (re)introduction regions under current climates. Climatic conditions generally remain suitable in the future, although some species will experience reduced suitability in parts of these regions. We conclude that climate change is not a major barrier to trophic rewilding as currently discussed in the literature.This article is part of the theme issue ‘Trophic rewilding: consequences for ecosystems under global change’.

scholarly journals Evaluating ecological uniqueness over broad spatial extents using species distribution modelling

2021 ◽  
Author(s):  
Gabriel Dansereau ◽  
Pierre Legendre ◽  
Timothée Poisot
Keyword(s):  
North America ◽  
Species Distribution ◽  
Rare Species ◽  
Beta Diversity ◽  
Species Distribution Modelling ◽  
Distribution Models ◽  
Science Data ◽  
Distribution Modelling ◽  
Ecological Uniqueness ◽  
The Relationship

Aim: Local contributions to beta diversity (LCBD) can be used to identify sites with high ecological uniqueness and exceptional species composition within a region of interest. Yet, these indices are typically used on local or regional scales with relatively few sites, as they require information on complete community compositions difficult to acquire on larger scales. Here, we investigate how LCBD indices can be used to predict ecological uniqueness over broad spatial extents using species distribution modelling and citizen science data. Location: North America. Time period: 2000s. Major taxa studied: Parulidae. Methods: We used Bayesian additive regression trees (BARTs) to predict warbler species distributions in North America based on observations recorded in the eBird database. We then calculated LCBD indices for observed and predicted data and examined the site-wise difference using direct comparison, a spatial autocorrelation test, and generalized linear regression. We also investigated the relationship between LCBD values and species richness in different regions and at various spatial extents and the effect of the proportion of rare species on the relationship. Results: Our results showed that the relationship between richness and LCBD values varies according to the region and the spatial extent at which it is applied. It is also affected by the proportion of rare species in the community. Species distribution models provided highly correlated estimates with observed data, although spatially autocorrelated. Main conclusions: Sites identified as unique over broad spatial extents may vary according to the regional richness, total extent size, and the proportion of rare species. Species distribution modelling can be used to predict ecological uniqueness over broad spatial extents, which could help identify beta diversity hotspots and important targets for conservation purposes in unsampled locations.

scholarly journals Making species distribution models available on the web for reuse in biodiversity experiments: Euterpe edulis species case study

2009 ◽  
Vol 21 (1) ◽  
pp. 39-49
Author(s):  
Karla Donato Fook ◽  
Silvana Amaral ◽  
Antônio Miguel Vieira Monteiro ◽  
Gilberto Câmara ◽  
Arimatéa de Carvalho Ximenes ◽  
...  
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Species Distribution Modelling ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Urban And Regional Planning ◽  
Community Needs ◽  
Computational Environment ◽  
Decision Making Processes ◽  
The Web

Currently, biodiversity conservation is one of the most urgent and important themes. Biodiversity researchers use species distribution models to make inferences about species occurrences and locations. These models are fundamental for fauna and flora preservation, as well as for decision making processes for urban and regional planning and development. Species distribution modelling tools use large biodiversity datasets which are globally distributed, can be in different computational platforms, and are hard to access and manipulate. The scientific community needs infrastructures in which biodiversity researchers can collaborate and share knowledge. In this context, we present a computational environment that supports the collaboration in species distribution modelling network on the Web. This environment is based on a modelling experiment catalogue and on a set of geoweb services, the Web Biodiversity Collaborative Modelling Services - WBCMS.

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