Bioclimatic variables derived from remote sensing: assessment and application for species distribution modelling

2014 ◽  
Vol 5 (10) ◽  
pp. 1033-1042 ◽  
Author(s):  
Eric Waltari ◽  
Ronny Schroeder ◽  
Kyle McDonald ◽  
Robert P. Anderson ◽  
Ana Carnaval
Keyword(s):  
Remote Sensing ◽  
Species Distribution ◽  
Species Distribution Modelling ◽  
Distribution Modelling ◽  
Bioclimatic Variables

First record of Cnemidochroma phyllopus (Coleoptera: Cerambycidae) in the province of Corrientes, Argentina and potential distribution in the southern part of South America

Zootaxa ◽  
2021 ◽  
Vol 5082 (1) ◽  
pp. 53-64
Author(s):  
NÉSTOR G. VALLE ◽  
MARIO G. IBARRA-POLESEL ◽  
MARIANA ALEJANDRA CHERMAN ◽  
MARCELA L. MONNÉ ◽  
MIRYAM P. DAMBORSKY
Keyword(s):  
South America ◽  
Species Distribution ◽  
Current Distribution ◽  
Potential Distribution ◽  
Atlantic Coast ◽  
First Record ◽  
Species Distribution Modelling ◽  
Distribution Modelling ◽  
Bioclimatic Variables ◽  
Small Genus

Cnemidochroma Schmidt, 1924, a small genus of the tribe Callichromatini endemic in South America, comprises six species of which the only one recorded in Paraguay, Uruguay, Argentina and Brazil is C. phyllopus (Guérin-Méneville, 1844). The aim of this study was to estimate potential suitable areas for C. phyllopus to provide further knowledge on its current distribution. A dataset of 43 records was compiled and species distribution modelling was employed linking these occurrences with bioclimatic variables. Results indicate higher suitability conditions along the Atlantic coast of Brazil, reaching north Uruguay and extending inland to Paraguay and northern parts of Argentina. In addition, we report a new distributional record from Corrientes, Argentina.  

Integrating remote sensing and species distribution modelling to predict benthic communities in a Great Lakes connecting channel

2017 ◽  
Vol 33 (8) ◽  
pp. 1336-1344
Author(s):  
K. Mehler ◽  
L.E. Burlakova ◽  
A.Y. Karatayev ◽  
Z. Biesinger ◽  
E. Bruestle ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Great Lakes ◽  
Species Distribution ◽  
Benthic Communities ◽  
Species Distribution Modelling ◽  
Distribution Modelling

scholarly journals SPECIES DISTRIBUTION MODELLING OF TWO SPECIES ENDEMIC TO THE PHILIPPINES TO SHOW THE APPLICABILITY OF MAXENT

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 449-454
Author(s):  
M. Z. G. Untalan ◽  
D. F. M. Burgos ◽  
K. P. Martinez
Keyword(s):  
Species Distribution ◽  
Endemic Species ◽  
Species Distribution Model ◽  
Species Distribution Modelling ◽  
The Philippines ◽  
Distribution Model ◽  
Distribution Modelling ◽  
Machine Learning Model ◽  
Monitor Lizard ◽  
Bioclimatic Variables

Abstract. Maxent is a machine learning model used for species distribution modelling (SDM) that is rising in popularity. As with any species distribution model, it needs to be validated for certain species before being used to generate insights and trusted predictions. Using Maxent, SDM of two endemic species in the Philippines, Varanus palawanensis (Palawan monitor lizard) and Caprimulgus manillensis (Philippine nightjar), were created using presence-only data, with 14 V. palawanensis and 771 C. manillensis occurrences, and 19 bioclimatic variables from BIOCLIM. This study shows the consistency to historical facts of Maxent on two endemic species of the Philippines of varying nature. The applicability of Maxent on the two very different species show that Maxent has high likelihood to give good results for other species. Showing that Maxent is applicable to the species of the Philippines gives additional tools for ecologists and national administrators to lead the development of the Philippines in the direction that conserves the biodiversity of the Philippines and that increases the productivity and quality of life in the Philippines.

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’.

Sign in / Sign up

Export Citation Format

Share Document