scholarly journals Mapping habitat suitability at range‐wide scales: Spatially‐explicit distribution models to inform conservation and research for marsh birds

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Bryan S. Stevens ◽  
Courtney J. Conway
Keyword(s):  
Habitat Suitability ◽  
Spatially Explicit ◽  
Distribution Models ◽  
Marsh Birds

scholarly journals Lowland tapir distribution and habitat loss in South America

2015 ◽  
Author(s):  
Jose Luis Passos Cordeiro ◽  
José MV Fragoso ◽  
Danielle Crawshaw ◽  
Luiz Flamarion B Oliveira
Keyword(s):  
South America ◽  
Protected Areas ◽  
Habitat Loss ◽  
Habitat Suitability ◽  
Distribution Patterns ◽  
Distribution Models ◽  
Potential Habitat ◽  
Geographical Regions ◽  
Suitability Maps ◽  
Complex Relationships

The development of species distribution models (SDMs) can help conservation efforts by generating potential distributions and identifying areas of high environmental suitability for protection. Our study presents a rigorously derived distribution and habitat map for lowland tapir in South America. We also describe the potential habitat suitability of various geographical regions and habitat loss, inside and outside of protected areas network. Two different SDM approaches, MAXENT and ENFA, produced relative different Habitat Suitability Maps for the lowland tapir. While MAXENT was efficient at identifying areas as suitable or unsuitable, it was less efficient (when compared to the results by ENFA) at identifying the gradient of habitat suitability. MAXENT is a more multifaceted technique that establishes more complex relationships between dependent and independent variables. Our results demonstrate that for at least one species, the lowland tapir, the use of a simple consensual approach (average of ENFA and MAXENT models outputs) better reflected its current distribution patterns. The Brazilian ecoregions have the highest habitat loss for the tapir. Cerrado and Atlantic Forest account for nearly half (48.19%) of the total area lost. The Amazon region contains the largest area under protection, and the most extensive remaining habitat for the tapir, but also showed high levels of habitat loss outside protected areas, which increases the importance of support for proper management.

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 Late Quaternary habitat suitability models for chimpanzees (Pan troglodytes) since the Last Interglacial (120,000 BP)

2020 ◽  
Author(s):  
Christopher D. Barratt ◽  
Jack D. Lester ◽  
Paolo Gratton ◽  
Renske E. Onstein ◽  
Ammie K. Kalan ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Pan Troglodytes ◽  
Habitat Suitability ◽  
Late Quaternary ◽  
Stability Estimates ◽  
Last Interglacial ◽  
Distribution Models ◽  
Habitat Stability ◽  
Bioclimatic Variables ◽  
Time Periods

AbstractAimPaleoclimate reconstructions have enhanced our understanding of how past climates may have shaped present-day biodiversity. We hypothesize that habitat stability in historical Afrotropical refugia played a major role in the habitat suitability and persistence of chimpanzees (Pan troglodytes) during the late Quaternary. We aimed to build a dynamic model of changing habitat suitability for chimpanzees at fine spatio-temporal scales to provide a new resource for understanding their ecology, behaviour and evolution.LocationAfrotropics.TaxonChimpanzee (Pan troglodytes), including all four subspecies (P. t. verus, P. t. ellioti, P. t. troglodytes, P. t. schweinfurthii).MethodsWe used downscaled bioclimatic variables representing monthly temperature and precipitation estimates, historical human population density data and an extensive database of georeferenced presence points to infer chimpanzee habitat suitability at 62 paleoclimatic time periods across the Afrotropics based on ensemble species distribution models. We mapped habitat stability over time using an approach that accounts for dispersal between time periods, and compared our modelled stability estimates to existing knowledge of Afrotropical refugia. Our models cover a spatial resolution of 0.0467 degrees (approximately 5.19 km2 grid cells) and a temporal resolution of every 1,000–4,000 years dating back to the Last Interglacial (120,000 BP).ResultsOur results show high habitat stability concordant with known historical forest refugia across Africa, but suggest that their extents are underestimated for chimpanzees. We provide the first fine-grained dynamic map of historical chimpanzee habitat suitability since the Last Interglacial which is suspected to have influenced a number of ecological-evolutionary processes, such as the emergence of complex patterns of behavioural and genetic diversity.Main ConclusionsWe provide a novel resource that can be used to reveal spatio-temporally explicit insights into the role of refugia in determining chimpanzee behavioural, ecological and genetic diversity. This methodology can be applied to other taxonomic groups and geographic areas where sufficient data are available.

Habitat Suitability and Distribution Models

2017 ◽  
Author(s):  
Antoine Guisan ◽  
Wilfried Thuiller ◽  
Niklaus E. Zimmermann
Keyword(s):  
Habitat Suitability ◽  
Distribution Models

A spatially explicit method for evaluating accuracy of species distribution models

2010 ◽  
Vol 16 (6) ◽  
pp. 996-1008 ◽  
Author(s):  
Mary Smulders ◽  
Trisalyn A. Nelson ◽  
Dennis E. Jelinski ◽  
Scott E. Nielsen ◽  
Gordon B. Stenhouse
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Spatially Explicit ◽  
Explicit Method ◽  
Distribution Models
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