Ecological-Niche Factor Analysis: How to Compute Habitat-Suitability Maps Without Absence Data?

Hirzel, Alexandre H.; Hausser, Jacques; Chessel, Daniel; Perrin, Nicolas

doi:10.1890/0012-9658(2002)083[2027:enfaht]2.0.co;2

Cited by 1,216 publications

(680 citation statements)

References 25 publications

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“…Applied in terrestrial settings for a decade (reviewed in Hirzel et al 2002), ENMs and similar models have only recently been employed in the deep sea (Metaxas & Bryan 2007). Tittensor et al (2009) are the first to examine deep-sea communities at a global scale using ENMs to disentangle important environmental variables influencing coral distributions on seamounts and predict locations of suitable habitat.…”

Section: H E N R I C I a L I S A B A T H Y A L S E A S T A R T H O mentioning

confidence: 99%

The dynamics of biogeographic ranges in the deep sea

2010

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Anthropogenic disturbances such as fishing, mining, oil drilling, bioprospecting, warming, and acidification in the deep sea are increasing, yet generalities about deep-sea biogeography remain elusive. Owing to the lack of perceived environmental variability and geographical barriers, ranges of deep-sea species were traditionally assumed to be exceedingly large. In contrast, seamount and chemosynthetic habitats with reported high endemicity challenge the broad applicability of a single biogeographic paradigm for the deep sea. New research benefiting from higher resolution sampling, molecular methods and public databases can now more rigorously examine dispersal distances and species ranges on the vast ocean floor. Here, we explore the major outstanding questions in deep-sea biogeography. Based on current evidence, many taxa appear broadly distributed across the deep sea, a pattern replicated in both the abyssal plains and specialized environments such as hydrothermal vents. Cold waters may slow larval metabolism and development augmenting the great intrinsic ability for dispersal among many deep-sea species. Currents, environmental shifts, and topography can prove to be dispersal barriers but are often semipermeable. Evidence of historical events such as points of faunal origin and climatic fluctuations are also evident in contemporary biogeographic ranges. Continued synthetic analysis, database construction, theoretical advancement and field sampling will be required to further refine hypotheses regarding deep-sea biogeography.

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Section: H E N R I C I a L I S A B A T H Y A L S E A S T A R T H O mentioning

confidence: 99%

The dynamics of biogeographic ranges in the deep sea

2010

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“…Una especie puede ser altamente marginal si el área de estudio es muy extensa o si se incluyen muchas regiones diferentes en el análisis; pero no mostrará marginalidad si el área de estudio se ajusta (o es igual) a la distribución espacial de la especie. Algunos autores sugieren que los valores pueden ser usados sólo para comparar muchas especies de una misma área o bien para estudiar cómo es la dinámica ecológica de una especie con el paso del tiempo en una región determinada (Hirzel, Hausser, Chessel, & Perrin, 2002a;Ureta, Martínez-Meyer, Perales, & Álvarez-Buylla, 2012).…”

Section: Ecological Niche Factor Analysis (Enfa)unclassified

“…A species can be highly marginal if the study area is very extensive or if many different regions are included in the analysis, but it will not display marginalization if the study area is adjusted (or is equal) to the spatial distribution of the species. Some authors suggest that the values can be used only to compare many species in the same area or to study how the ecological dynamics of a species is over time in a given region (Hirzel, Hausser, Chessel, & Perrin, 2002a;Ureta, Martínez-Meyer, Perales, & Álvarez-Buylla, 2012).…”

Section: Hábitat Conveniente Actual Y Futuromentioning

confidence: 99%

Bosque Mesófilo De Montaña Y Escenarios De Cambio Climático: Una Evaluación en Hidalgo, México

Monterroso-Rivas¹,

Gómez-Díaz²,

Tinoco-Rueda³

2013

Rev Cha Se Cie For y del Amb

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) representativas del bosque mesófilo de montaña en el estado de Hidalgo se evaluó en condiciones actuales y bajo escenarios de cambio climático. Se utilizó el marco conceptual de nicho ecológico y se evaluaron doce variables: una topográfica, cinco paisajísticas y seis climáticas. Se realizó un análisis factorial de nicho ecológico con el software Biomapper, que básicamente es un análisis estadístico de reducción de dimensiones. Para cada especie, se obtuvieron mapas de hábitat potencial al modificar seis variables climáticas por cada modelo de cambio climático aplicado, generando igual número de mapas para condiciones futuras. Se analizaron las diferencias en hábitat potencial para las condiciones actuales y aquéllas previstas por cambio climático, encontrando que es posible que la superficie óptima de crecimiento para seis especies se reduzca. Las especies identificadas como amenazadas por el cambio climático son L. macrophylla, A. arguta, C. caroliniana, C. mexicana, P. patula, y N. sanguínea. Estas especies componen principalmente el estrato arbóreo alto del bosque mesófilo, por lo que se concluye que el ecosistema puede verse seriamente afectado como consecuencia del cambio climático. ABSTRACTT he habitat of eight forest species (Liquidambar macrophylla, Alnus arguta, Carpinus caroliniana, Clethra mexicana, Pinus patula, Nectandra sanguínea, Podocarpus reichei and Quercus spp.) representative of cloud forest in the state of Hidalgo was assessed under current and projected climate conditions. We used the ecological niche conceptual framework and considered twelve variables: one related to topography, five to landscape and six to climate. An ecological niche factorial analysis was carried out with Biomapper software. Habitat suitability maps were obtained for each forest species by changing six climatic variables for each climate change model applied, generating the same number of maps for future conditions. We analyzed the differences in suitable habitat for current conditions and those projected by climate change, finding that the optimal growth area for six species may be reduced. The species identified as threatened by climate change are L. macrophylla, A. arguta, C. caroliniana, C. mexicana, P. patula, and N. sanguinea, which comprise mainly the high tree layer of the cloud forest. We therefore conclude that the ecosystem can be seriously affected by climate change.

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“…The Ecological Niche Factor Analysis (ENFA, [47]) model identifies a set of uncorrelated factors that accounts for the information by comparing the distributions of environmental variables and the population distribution dataset across the surveyed geographical area. One factor, Marginality, was defined as the ecological distance between the species optimum and the mean habitat within a reference area.…”

Section: Methodsmentioning

confidence: 99%

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains

et al. 2010

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BackgroundGene flow maintains genetic diversity within a species and is influenced by individual behavior and the geographical features of the species' habitat. Here, we have characterized the geographical distribution of genetic patterns in giant pandas (Ailuropoda melanoleuca) living in four isolated patches of the Xiaoxiangling and Daxiangling Mountains. Three geographic distance definitions were used with the "isolation by distance theory": Euclidean distance (EUD), least-cost path distance (LCD) defined by food resources, and LCD defined by habitat suitability.ResultsA total of 136 genotypes were obtained from 192 fecal samples and one blood sample, corresponding to 53 unique genotypes. Geographical maps plotted at high resolution using smaller neighborhood radius definitions produced large cost distances, because smaller radii include a finer level of detail in considering each pixel. Mantel tests showed that most correlation indices, particularly bamboo resources defined for different sizes of raster cell, were slightly larger than the correlations calculated for the Euclidean distance, with the exception of Patch C. We found that natural barriers might have decreased gene flow between the Xiaoxiangling and Daxiangling regions.ConclusionsLandscape features were found to partially influence gene flow in the giant panda population. This result is closely linked to the biological character and behavior of giant pandas because, as bamboo feeders, individuals spend most of their lives eating bamboo or moving within the bamboo forest. Landscape-based genetic analysis suggests that gene flow will be enhanced if the connectivity between currently fragmented bamboo forests is increased.

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Ecological-Niche Factor Analysis: How to Compute Habitat-Suitability Maps Without Absence Data?

Cited by 1,216 publications

References 25 publications

The dynamics of biogeographic ranges in the deep sea

The dynamics of biogeographic ranges in the deep sea

Bosque Mesófilo De Montaña Y Escenarios De Cambio Climático: Una Evaluación en Hidalgo, México

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains

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