Marcer A., Saez L., Molowny-Horas R., Pons X., Pino J. (2013) Using species distribution modelling to disentangle realised versus potential distributions for rare species conservation. Biological Conservation. 166: 221-230.EnllaçDoi: 10.1016/j.biocon.2013.07.001
Range maps provide important information in species conservation management, specially in the case of rare species of conservation interest. For the vast majority of cases, this information can only be estimated by means of species distribution modelling. When absence data is unavailable, modelled distribution maps represent the spatial variation of the degree of suitability for the species rather than their realised distribution. Although discerning potentially suitable areas for a given species is an important asset in conservation, it is necessary to estimate current distributions in order to preserve current populations. This work explores the use of species distribution modelling (Maxent) for species of conservation interest when their Extent of Occurrence (EOO) is well-known and there is quality occurrence data. In this case, derived binary maps of potentially suitable areas can be obtained and used to assess the conservation and protection status of a given species in combination with the EOO and existing protected area networks. Seven species, which are rare and endemic to the Western Mediterranean, have been used as an example. Valuable information for conservation assessment such as potentially suitable areas, EOO, Areas of Occupancy (AOO) and degree of protection is provided for this set of species. In addition, the existing informal view that among experts these species have range sizes much smaller than their potentially suitable area is confirmed. This could probably be attributed to important but currently unknown predictor variables and to historical phylogeographic factors. © 2013 Elsevier Ltd.
Marcer A., Pino J., Pons X., Brotons L. (2012) Modelling invasive alien species distributions from digital biodiversity atlases. Model upscaling as a means of reconciling data at different scales. Diversity and Distributions. 18: 1177-1189.EnllaçDoi: 10.1111/j.1472-4642.2012.00911.x
Aim: There is a wealth of information on species occurrences in biodiversity data banks, albeit presence-only, biased and scarce at fine resolutions. Moreover, fine-resolution species maps are required in biodiversity conservation. New techniques for dealing with this kind of data have been reported to perform well. These fine-resolution maps would be more robust if they could explain data at coarser resolutions at which species distributions are well represented. We present a new methodology for testing this hypothesis and apply it to invasive alien species (IAS). Location: Catalonia, Spain. Methods: We used species presence records from the Biodiversity data bank of Catalonia to model the distribution of ten IAS which, according to some recent studies, achieve their maximum distribution in the study area. To overcome problems inherent with the data, we prepared different correction treatments: three for dealing with bias and five for autocorrelation. We used the MaxEnt algorithm to generate models at 1-km resolution for each species and treatment. Acceptable models were upscaled to 10 km and validated against independent 10 km occurrence data. Results: Of a total of 150 models, 20 gave acceptable results at 1-km resolution and 12 passed the cross-scale validation test. No apparent pattern emerged, which could serve as a guide on modelling. Only four species gave models that also explained the distribution at the coarser scale. Main conclusions: Although some techniques may apparently deliver good distribution maps for species with scarce and biased data, they need to be taken with caution. When good independent data at a coarser scale are available, cross-scale validation can help to produce more reliable and robust maps. When no independent data are available for validation, however, new data gathering field surveys may be the only option if reliable fine-scale resolution maps are needed. © 2012 Blackwell Publishing Ltd.
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