Building large-scale spatially explicit models to predict the distribution of suitable habitat patches for the Greater rhea (Rhea americana), a near-threatened species

Giordano, P.; Navarro, Joaquín L.; Martella, Mónica B.

doi:10.1016/j.biocon.2009.10.022

Cited by 30 publications

(22 citation statements)

References 34 publications

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“…(Guisan & Zimmermann 2000, Giordano et al 2010, Kosicki & Chylarecki 2012a, 2012b. Such data are only suitable for some species that have habitat requirements with sharp boundaries in the landscape, e.g.…”

mentioning

confidence: 99%

“…Changes in agricultural land use patterns, driven by the Common Agricultural Policy, have been identified as primary factors affecting species distribution at a regional and local scale (Pereira et al 2004, Holzkämper & Seppelt 2007, Giordano et al 2010. European grassland birds have already suffered longterm population decline as a result of changes in land use.…”

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confidence: 99%

“…As part of this process, conservationists pay a lot of attention to developing methods for collecting and analysing data from both small and large areas so they can monitor the population health of many species (Franco & Sutherland 2004, Posillico et al 2004, Balbotín 2005, Gregory et al 2007, Franklin 2010. Despite numerous techniques for predictive mapping of species distribution (Carpenter et al 1993, Elith et al 2006, Araújo & New 2007, Giordano et al 2010), e.g. MAXENT (Phillips 2005); BIOCLIM (Austin et al 1994); SAGA (http://www.saga-gis.org/en/index.html); GARP ; and ENFA (Hirzel et al 2002), procedures tend to be similar, i.e.…”

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confidence: 99%

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Predictive mapping of Meadow Pipit density using integrated remote sensing data and an atlas of vascular plants dataset

Kosicki

Chylarecki

2013

Bird Study

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Predictive mapping of Meadow Pipit density using integrated remote sensing data and an atlas of vascular plants dataset

Kosicki

Chylarecki

2013

Bird Study

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“…small-scale structural elements or habitat variety might influence their habitat selection decisions. However, this kind of detailed information cannot be obtained from generalized remote sensing-based data sources (Akc¸akaya 2001;Giordano et al 2010). On the large geographical scale, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Many of these studies use publicly available generalized Geographic Information Systems (GIS) datasets (i.e. Corine land cover, NDVI dataset, WordClim) as predictors (e.g., Giordano et al 2010;Kosicki and Chylarecki 2013;Morelli and Tryjanowski 2014). However, such data are only suitable for some opportunistic species that have habitat requirements with sharp boundaries in the landscape, e.g.…”

Section: Introductionmentioning

confidence: 99%

Complex species distribution models of Goldcrests and Firecrests densities in Poland: are remote sensing‐based predictors sufficient?

Kosicki

Stachura

Ostrowska

et al. 2015

Ecological Research

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Species distribution models should identify ecological requirements of species and predict their spatial density. However, data from remote sensing sources are often used alone as predictors in modelling distributions. Such data will only produce accurate models if features that are distinguishable by remote sensing are a good match to the environmental traits that delineate habitat requirements. Both the Goldcrest Regulus regulus and the Firecrest Regulus ignicapilla respond to complex features of habitats that are not described by simple remote sensing data. We tested the usefulness of remote sensing data as a predictor for two Regulus species according to data from 970 study plots sized 1 · 1 km. Predictors were aggregated using the PCAs and related to the Hayne estimator of species density using GAMs. The models based on both remote sensing data and detailed environmental data proved to be better than the model based only on remote sensing data and/or detailed forest structure data. The Goldcrest reached the highest density in areas with a high share of old spruce-dominated forests with a substantial share of the fir, avoiding the pine, and it preferred forests with a low number of tree species. In turn, the Firecrest favoured old forests, dominated by the spruce and the beech, with an admixture of single old fir and larch trees, avoiding the pine, and preferring forests with a high number of tree species. We suggest using not only free data sources, but also more detailed data containing thorough information on forest inventory derived from ground measurements.

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Influence of breeding season on fecal glucocorticoid levels in captive Greater Rhea (Rhea americana)

Lèche

Hansen²,

Navarro

et al. 2014

Zoo Biology

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Sex hormones and stress-related changes can be seasonally influenced. We investigate whether fecal glucocorticoid metabolite (FGM) levels can differ between male and female captive Greater Rheas during the breeding and non-breeding seasons. Over a 3-year-period, fresh fecal samples from 10 individuals (five of each sex) were collected during the breeding months (October, November, and December) and non-breeding months (April and June). A total of 960 samples were assayed using a commercial radioimmunoassay. Results showed that FGM levels (mean ± SE) were affected by the breeding season in a sex-dependent way. Male Greater Rheas showed significantly higher FGM levels in the breeding months than in the non-breeding months (13.44 ± 0.37 vs. 7.92 ± 0.1 ng/g feces, respectively). By contrast, females did not show FGM seasonal changes throughout the same sampling periods (7.55 ± 0.14 vs. 7.26 ± 0.73 ng/g feces). Moreover, during the breeding season months, males showed higher average FGM levels than females (13.44 ± 0.37 vs. 7.55 ± 0.14 ng/g feces, respectively), and no differences were found between sexes during the non-breeding season (7.92 ± 0.1 vs. 7.26 ± 0.73 ng/g feces, respectively). Our findings suggest that male Greater Rheas have a higher adrenocortical activity during the breeding season, which is probably indirectly related to the increased testosterone levels and agonist interactions that are also observed during that phase. Studies aimed to determine the appropriate sex ratio for captive rearing should be developed to minimize male agonist encounters and therefore improve welfare of the captive group.

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Building large-scale spatially explicit models to predict the distribution of suitable habitat patches for the Greater rhea (Rhea americana), a near-threatened species

Cited by 30 publications

References 34 publications

Predictive mapping of Meadow Pipit density using integrated remote sensing data and an atlas of vascular plants dataset

Predictive mapping of Meadow Pipit density using integrated remote sensing data and an atlas of vascular plants dataset

Complex species distribution models of Goldcrests and Firecrests densities in Poland: are remote sensing‐based predictors sufficient?

Influence of breeding season on fecal glucocorticoid levels in captive Greater Rhea (Rhea americana)

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