Are species distribution models based on broad-scale environmental variables transferable across adjacent watersheds? A case study with eleven macroinvertebrate species

2015 ◽  
Vol 186 (1) ◽  
pp. 63-97 ◽  
Author(s):  
Maria Gies ◽  
Martin Sondermann ◽  
Daniel Hering ◽  
Christian K. Feld
2018 ◽  
Author(s):  
Mar Sacau Cuadrado ◽  
Ana Garcia-Alegre Garralda ◽  
Maria Grazia Pennino ◽  
Francisco Javier Murillo Pérez ◽  
Alberto Serrano López ◽  
...  

Species Distribution Models (SDMs) are widely used to identify species-environmentrelationships and predicting species occurrence and/or density at un-sampled locations.The SDMs implementation allows describing species geographical trends, toidentify spatial ontogenetic shifts of commercially exploited species and to assessthe effect of climate change on species distribution. Moreover, SDMs could bean essential tool to support the marine spatial planning framework providingessential and easy-to-use interpretation tools, such as predictive distributionmaps, with the final aim of improving management and conservation especially ofvulnerable species as sea pen corals. In this study, a 10-yr period (2007-2017) of a bottom trawl survey was used to estimateand predict the suitability habitat of sea pen species as a function of several environmental variables (i.e. bathymetry, sea bottom temperature, sea bottom salinity, slope, rugosity, aspectof the seabed, etc) in Flemish Cap and Flemish Pass (ATLAS Case Study No 11) using different SDM algorithms. Resultsshow that species exhibit specific habitat preferences and spatial patterns inresponse to environmental variables.


2018 ◽  
Author(s):  
Mar Sacau Cuadrado ◽  
Ana Garcia-Alegre Garralda ◽  
Maria Grazia Pennino ◽  
Francisco Javier Murillo Pérez ◽  
Alberto Serrano López ◽  
...  

Species Distribution Models (SDMs) are widely used to identify species-environmentrelationships and predicting species occurrence and/or density at un-sampled locations.The SDMs implementation allows describing species geographical trends, toidentify spatial ontogenetic shifts of commercially exploited species and to assessthe effect of climate change on species distribution. Moreover, SDMs could bean essential tool to support the marine spatial planning framework providingessential and easy-to-use interpretation tools, such as predictive distributionmaps, with the final aim of improving management and conservation especially ofvulnerable species as sea pen corals. In this study, a 10-yr period (2007-2017) of a bottom trawl survey was used to estimateand predict the suitability habitat of sea pen species as a function of several environmental variables (i.e. bathymetry, sea bottom temperature, sea bottom salinity, slope, rugosity, aspectof the seabed, etc) in Flemish Cap and Flemish Pass (ATLAS Case Study No 11) using different SDM algorithms. Resultsshow that species exhibit specific habitat preferences and spatial patterns inresponse to environmental variables.


Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1195
Author(s):  
Rebecca Dickson ◽  
Marc Baker ◽  
Noémie Bonnin ◽  
David Shoch ◽  
Benjamin Rifkin ◽  
...  

Projects to reduce emissions from deforestation and degradation (REDD) are designed to reduce carbon emissions through avoided deforestation and degradation, and in many cases, to produce additional community and biodiversity conservation co-benefits. While these co-benefits can be significant, quantifying conservation impacts has been challenging, and most projects use simple species presence to demonstrate positive biodiversity impact. Some of the same tools applied in the quantification of climate mitigation benefits have relevance and potential application to estimating co-benefits for biodiversity conservation. In western Tanzania, most chimpanzees live outside of national park boundaries, and thus face threats from human activity, including competition for suitable habitat. Through a case study of the Ntakata Mountains REDD project in western Tanzania, we demonstrate a combined application of deforestation modelling with species distribution models to assess forest conservation benefits in terms of avoided carbon emissions and improved chimpanzee habitat. The application of such tools is a novel approach that we argue permits the better design of future REDD projects for biodiversity co-benefits. This approach also enables project developers to produce the more manageable, accurate and cost-effective monitoring, reporting and verification of project impacts that are critical to verification under carbon standards.


Ecography ◽  
2012 ◽  
Vol 36 (6) ◽  
pp. 649-656 ◽  
Author(s):  
Tereza Cristina Giannini ◽  
Daniel S. Chapman ◽  
Antonio Mauro Saraiva ◽  
Isabel Alves-dos-Santos ◽  
Jacobus C. Biesmeijer

Author(s):  
Balaguru Balakrishnan ◽  
Nagamurugan Nandakumar ◽  
Soosairaj Sebastin ◽  
Khaleel Ahamed Abdul Kareem

Conservation of the species in their native landscapes required understanding patterns of spatial distribution of species and their ecological connectivity through Species Distribution Models (SDM) by generation and integration of spatial data from different sources using Geographical Information System (GIS) tools. SDM is an ecological/spatial model which combines datasets and maps of occurrence of target species and their geographical and environmental variables by linking various algorithms together, that has been applied to either identify or predict the regions fulfilling the set conditions. This article is focused on comprehensive review of spatial data requirements, statistical algorithms and softwares used to generate the SDMs. This chapter also includes a case study predicting the suitable habitat distribution of Gnetum ula, an endemic and vulnerable plant species using maximum entropy (MaxEnt) species distribution model for species occurrences with inputs from environmental variables such as bioclimate and elevation.


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