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      New records and estimation of the potential distribution of the stump-tailed Porcupine Coendou rufescens

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          Abstract

          Abstract: The stump-tailed porcupine (Coendou rufescens) is a medium-sized species that inhabits subtropical, temperate and High-Andean forests of the northern Andes, at 800 to 3,650 m asl. This species is characterized by a short non-prehensile tail and a distinctive reddish color. Here, we report new localities for Coendou rufescens in Ecuador based on direct field sightings and the revision of mammal collections. In addition, we conducted a review of literature records of C. rufescens throughout its distribution range. A total of 52 georeferenced records were modeled for the potential distribution at the regional level (Colombia, Ecuador, and Peru) based on 19 bioclimatic variables. Finally, we overlaid the layers of vegetation remnants and state protected areas. We report 10 new localities for Coendou rufescens in Ecuador; these records are concentrated to southern Ecuador between 1,120 to 4,387 masl. Fifty two records found that the bioclimatic variables Temperature Seasonality (BIO4) and Minimum Temperature of the Coldest Month (BIO6) associated with the type of habitat made the greatest significant contribution to the distribution model of C. rufescens. The suitable habitat for the species spans across ~ 448,820 km2, with 50.4 % in Colombia. These findings indicate that the locality Camino del Inca in Sangay National Park, at 4,387 m asl, is considered the highest-elevation record for C. rufescens and the family Erethizontidae. Colombia and Peru include the highest proportion of potential habitat across its range (40.2 % and 32.7 %) based on remnant vegetation; however, Ecuador maintains the largest proportion of the porcupine distribution within protected areas (35.5%), with a larger extent of landscape connectivity, essential for the conservation of C. rufescens.

          Translated abstract

          Resumen: El puerco espín de cola corta (Coendou rufescens) es una especie de tamaño mediano que habita los bosques Subtropicales, Templados y Alto-Andinos de los Andes norte, entre los 800 a 3,650 m de elevación. Esta especie se caracteriza principalmente por presentar una cola corta y no prensil, además de su peculiar coloración rojiza. Se reportan nuevas localidades para Coendou rufescens sobre la base de avistamientos directos en campo y revisión de colecciones mastozoológicas. Adicionalmente se realizó una revisión de los registros bibliográficos de C. rufescens a lo largo de su distribución geográfica. Con un total de 52 registros recopilados y georefenciados, se modeló la distribución potencial a escala regional (Colombia, Ecuador y Perú) utilizando 19 variables bioclimáticas seleccionadas por su nivel de correlación. Finalmente, se superpusieron las capas de vegetación remanente y áreas protegidas estatales. Se adicionan 10 localidades para Coendou rufescens en Ecuador, los registros se concentran en el sur del país en un rango altitudinal entre 1,120 a 4,387 m. Con base a los 52 registros se determinó que las variables bioclimáticas que contribuyen más significativamente al modelo de distribución predictiva son BIO4: Temperatura estacional y BIO6: Temperatura mínima del mes más frío, las cuales están asociadas al tipo de hábitat. Se determinó que el hábitat idóneo para la especie es de ~448,820 km2, donde el 50.4 % de la distribución potencial se concentra en Colombia. La localidad del Camino del Inca en el Parque Nacional Sangay, ubicado a 4,387 m es el registro de mayor elevación para C. rufescens y la familia Erethizontidae. Colombia y Perú contienen la proporción más alta de hábitat adecuado para la especie (40.2 y 32.7 %) con base en la vegetación remanente; no obstante, Ecuador mantiene la mayor proporción de la distribución dentro de áreas protegidas (35.5 %), por ende, presentaría mayor conectividad de paisaje, lo cual es esencial para la conservación de C. rufescens.

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          Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

          Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.
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            Fit-for-Purpose: Species Distribution Model Performance Depends on Evaluation Criteria – Dutch Hoverflies as a Case Study

            Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species’ data characteristics (i.e. sample size, spatial distribution).
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              Physiological adaptation to high altitude: oxygen transport in mammals and birds.

              C Monge, F Leon (1991)
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                therya
                Therya
                Therya
                Asociación Mexicana de Mastozoología A. C. (La Paz, Baja California Sur, Mexico )
                2007-3364
                2018
                : 9
                : 2
                : 137-146
                Affiliations
                [2] Quito orgnameUniversidad San Francisco de Quito Ecuador creyesp@ 123456usfq.edu.ec
                [4] Quito Quito orgnameEscuela Politécnica Nacional orgdiv1Facultad de Ciencias Ecuador
                [3] Loja orgnameEquanativa Cía. Ltda Ecuador darwinvalle@ 123456gmail.com
                [1] Quito orgnameAsociación Ecuatoriana de Mastozoología Ecuador carlosnarvaez@ 123456icloud.com
                [5] Quito orgnameInstituto Nacional de Biodiversidad Ecuador jorgeyakuma@ 123456yahoo.es
                Article
                S2007-33642018000200137
                10.12933/therya-18-581
                7cc92728-b216-40ce-9580-ec196cb9366b

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 19 March 2018
                : 29 December 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 62, Pages: 10
                Product

                SciELO Mexico


                distribution model,mammals,protected area,altitudinal range,vegetation remnants

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