scholarly journals The effects of spatial survey bias and habitat suitability on predicting the distribution of threatened species living in remote areas

2017 ◽  
Vol 28 (4) ◽  
pp. 581-592 ◽  
Author(s):  
LAURA CARDADOR ◽  
JOSÉ A. DÍAZ-LUQUE ◽  
FERNANDO HIRALDO ◽  
JAMES D. GILARDI ◽  
JOSÉ L. TELLA
Keyword(s):  
Land Use ◽  
Geographical Distribution ◽  
Species Distribution ◽  
Potential Distribution ◽  
Variation Partitioning ◽  
Sampling Bias ◽  
Landscape Scale ◽  
Habitat Characteristics ◽  
Distribution Models ◽  
Joint Contribution

SummaryKnowledge of a species’ potential distribution and the suitability of available habitat are fundamental for effective conservation planning and management. However, the quality of information on the distribution of species and their required habitats is highly variable in terms of accuracy and availability across taxa and regions, particularly in tropical landscapes where accessibility is especially challenging. Species distribution models (SDMs) provide predictive tools for addressing gaps for poorly surveyed species, but they rarely consider biases in geographical distribution of records and their consequences. We applied SDMs and variation partitioning analyses to investigate the relative importance of habitat characteristics, human accessibility, and their joint effects in the global distribution of the Critically Endangered Blue-throated MacawAra glaucogularis, a species endemic to the Amazonian flooded savannas of Bolivia. The probability of occurrence was skewed towards more accessible areas, mostly secondary roads. Variability in observed occurrence patterns was mostly accounted for by the pure effect of habitat characteristics (76.2%), indicating that bias in the geographical distribution of occurrences does not invalidate species-habitat relationships derived from niche models. However, observed spatial covariation between land-use at a landscape scale and accessibility (joint contribution: 22.3%) may confound the independent role of land-use in the species distribution. New surveys should prioritise collecting data in more remote (less accessible) areas better distributed with respect to land-use composition at a landscape scale. Our results encourage wider application of partitioning methods to quantify the extent of sampling bias in datasets used in habitat modelling for a better understanding of species-habitat relationships, and add insights into the potential distribution of our study species and opportunities for its conservation.

scholarly journals Geographical distribution and habitat of Trochillidae (Aves) in the state of Guerrero, Mexico

2016 ◽  
Vol 64 (1) ◽  
pp. 363 ◽  
Author(s):  
Pablo Sierra Morales ◽  
R. Carlos Almazán-Núñez ◽  
Elizabeth Beltrán-Sánchez ◽  
César A. Ríos-Muñoz ◽  
María Del Coro Arizmendi
Keyword(s):  
Land Use ◽  
Geographical Distribution ◽  
Potential Distribution ◽  
The State ◽  
Primary Forest ◽  
Risk Category ◽  
Bird Conservation ◽  
Distribution Models ◽  
Sierra Madre Del Sur ◽  
Scientific Collections

The distribution and abundance of species of Trochillidae family is usually influenced by the flowering and phenology of plants used as a feeding source, mainly in primary forest, so that changes in vegetation cover could impact their populations. We analyzed and characterized the geographical distribution and habitat for 22 species of resident hummingbirds in the state of Guerrero using the vegetation and the land use map of INEGI Series IV (2007-2010). Distribution models were generated with the Genetic Algorithm for Rule Set Production (GARP), using historical records of scientific collections and fieldwork (2001-2009), in combination with climatic and topographic variables. Of the 22 modeled species, six are endemic to Mexico, the same number of species found in a risk category. The highest concentration with regards to richness (14-20 species), endemism (5-6 species) and number of threatened species of hummingbirds (5-6 species) occurred in the biotic province of Sierra Madre del Sur. However, the potential distribution of most of the hummingbirds occurred in disturbed sites or agroecosystems, as a result of changes in land-use. For Campylopterus hemileucurus, Lamprolaima rhami and Heliomaster longisrostris, their potential distribution was highest in areas of primary vegetation. Areas of high hummingbirds presence do not coincide with the Important Bird Areas proposed for bird conservation in Guerrero, considering that, despite its diversity and its extreme popularity, from the conservation perspective hummingbirds have received relatively little attention.

How many predictors in species distribution models at the landscape scale? Land use versus LiDAR-derived canopy height

2014 ◽  
Vol 28 (8) ◽  
pp. 1723-1739 ◽  
Author(s):  
Gentile Francesco Ficetola ◽  
Anna Bonardi ◽  
Caspar A. Mücher ◽  
Niels L.M. Gilissen ◽  
Emilio Padoa-Schioppa
Keyword(s):  
Land Use ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Landscape Scale ◽  
Canopy Height ◽  
Distribution Models

scholarly journals Sampling bias correction in species distribution models by quasi-linear Poisson point process

2020 ◽  
Vol 55 ◽  
pp. 101015 ◽  
Author(s):  
Osamu Komori ◽  
Shinto Eguchi ◽  
Yusuke Saigusa ◽  
Buntarou Kusumoto ◽  
Yasuhiro Kubota
Keyword(s):  
Point Process ◽  
Species Distribution ◽  
Bias Correction ◽  
Poisson Point Process ◽  
Species Distribution Models ◽  
Sampling Bias ◽  
Distribution Models

Sampling bias in geographic and environmental space and its effect on the predictive power of species distribution models

2012 ◽  
Vol 10 (3) ◽  
pp. 305-315 ◽  
Author(s):  
Nadia Bystriakova ◽  
Mykyta Peregrym ◽  
Roy H.J. Erkens ◽  
Olesya Bezsmertna ◽  
Harald Schneider
Keyword(s):  
Species Distribution ◽  
Predictive Power ◽  
Species Distribution Models ◽  
Sampling Bias ◽  
Distribution Models ◽  
Environmental Space

scholarly journals Climatic constraints and the distribution of Patagonian mice

2019 ◽  
Author(s):  
Trinidad Ruiz Barlett ◽  
Gabriel M Martin ◽  
María Fabiana Laguna ◽  
Guillermo Abramson ◽  
Adrián Monjeau
Keyword(s):  
Potential Distribution ◽  
Vegetation Index ◽  
Habitat Characteristics ◽  
Climatic Variables ◽  
Rodent Species ◽  
Forest Steppe ◽  
Distribution Models ◽  
Humid Climate ◽  
Local Conditions ◽  
Bioclimatic Variables

Abstract We generated potential distribution models for 14 sigmodontine rodent species that inhabit the Andean–Patagonian forest region and adjacent areas, and retrieved the main climatic variables responsible for these models. Our main objective was to compare these climatic variables and the distribution patterns generated for each species, and explore the effects of the physical environment in shaping the composition of rodent communities in the area. We retrieved a total of 1,215 records of species presence from 580 sites. Maxent was used to generate potential distribution models for the 14 rodent species studied. We used a total of 20 variables obtained from the WorldClim database, including elevation and 19 bioclimatic variables, in addition to normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Our results showed a clear discrimination between two groups of rodents, one concentrated in the western part of our study area, with more humid climate and a rugged mountainous and discontinuous habitat, and another inhabiting the eastern, drier part of our study area, which appears to be more uniform in habitat characteristics. These groups showed a mosaic of phylogenetically non-related species from different tribes, that probably arrived or expanded into Patagonia during the last millennia. The overlap of all models showed the forest-steppe ecotone east of Nahuel Huapi Lake and south to −43° latitude as the area with the highest species richness (8–11 species). All species showed a high correspondence with temperature and precipitation that define patterns at a landscape scale, with little to very little information contained in the typical vegetation variables that would define local conditions. En este trabajo generamos modelos de distribución potencial para cada especie de roedor sigmodontino que habita la región de los bosques andino-patagónicos y áreas adyacentes, identificando las principales variables climáticas que influyen en dichas distribuciones. Nuestro principal objetivo fue comparar las variables climáticas y los patrones de distribución generados para cada especie, y explorar los efectos del entorno físico en la composición de los ensambles de especies. Recopilamos un total de 1215 registros de presencia de especies de 580 sitios. Se utilizó MaxEnt para generar los modelos de distribución potencial de las 14 especies de roedores estudiadas, con 20 variables obtenidas de la base de datos WorldClim, incluida la elevación, 19 variables bioclimáticas, además del NDVI y EVI. Nuestros resultados muestran una clara discriminación entre dos grupos de roedores, uno concentrado en el área occidental, con un clima más húmedo y montañoso, y otro que habita en el área más seca del este. Curiosamente, estos grupos muestran un mosaico de especies, filogenéticamente no relacionadas y de diferentes tribus, que probablemente llegaron o se expandieron en la Patagonia durante los últimos milenios. La superposición de todos los modelos muestra el ecotono bosque-estepa, al este del lago Nahuel Huapi y hacia el sur hasta los -43°, como la zona más rica en especies (8 a 11 especies). Todas las especies muestran una alta correspondencia con las variables ambientales (temperatura y precipitación) que definen patrones a escala del paisaje, con muy poca información contenida en las variables típicas de la vegetación que definirían las condiciones locales.

Multispecies and Watershed Approaches to Freshwater Fish Conservation

2019 ◽  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Fisheries Management ◽  
Species Distribution ◽  
Large Scale ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Climate Conditions ◽  
Resource Sustainability ◽  
Riparian Protection

<em>Abstract</em>.—Increasingly, fisheries managers must make important decisions in complex environments where rapidly changing landscape and climate conditions interact with historical impacts to influence resource sustainability. Successful fisheries management in this setting will require that we adapt traditional management approaches to incorporate information on these complex interacting factors—a process referred to as resilient fisheries management. Large-scale species distribution data and predictive models have the potential to enhance the management of freshwater fishes through improved understanding of how past, present, and future natural and anthropogenic factors combine to determine species vulnerability and resiliency. Here we describe a resilient fisheries management framework that provides guidance on how and when these models can be incorporated into traditional approaches to meet specific goals and objectives for resource sustainability. In addition to elucidating complex drivers of distributional patterns and change, species distribution models can inform the prioritization, application, and implementation of management activities such as restoration (e.g., instream habitat and riparian), protection (e.g., areas where additional land use would result in a change in species distribution), and regulations (e.g., harvest restriction) in a way that informs resiliency to land use and climate change. Although considerable progress has been made with respect to applying species distribution models to the management of Brook Trout <em>Salvelinus fontinalis </em>and other aquatic species, there are several areas where a more unified research and management effort could increase the ability of distribution models to inform resilient management. Future efforts should aim to improve (1) data availability, consistency (sampling methodology), and quality (accounting for detection); (2) partnerships among researchers, agencies, and managers; and (3) model accessibility and understanding of limitations and potential benefits to managers (e.g., incorporation into publicly available decision support systems). The information and recommendations provided herein can be used to promote and advance the use of models in resilient fisheries management in the face of continued large-scale land use and climate change.

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