Marull J., Herrando S., Brotons L., Melero Y., Pino J., Cattaneo C., Pons M., Llobet J., Tello E. (2019) Building on Margalef: Testing the links between landscape structure, energy and information flows driven by farming and biodiversity. Science of the Total Environment. 674: 603-614.EnllaçDoi: 10.1016/j.scitotenv.2019.04.129
The aim of this paper is to test two methodologies, applicable to different spatial scales (from regional to local), to predict the capacity of agroecosystems to provide habitats for the species richness of butterflies and birds, based on the ways their socio-metabolic flows change the ecological functionality of bio-cultural landscapes. First, we use the more general Intermediate Disturbance-Complexity (IDC) model to assess how different levels of human appropriation of photosynthetic production affect the landscape functional structure that hosts biodiversity. Second, we apply a more detailed Energy-Landscape Integrated Analysis (ELIA) model that focusses on the energy storage carried out by the internal biomass loops, and the energy information held in the network of energy flows driven by farmers, in order to correlate both (the energy reinvested and redistributed) with the energy imprinted in the landscape patterns and processes that sustain biodiversity. The results obtained after applying both models in the province and the metropolitan region of Barcelona support the Margalef's energy-information-structure hypothesis by showing positive relations between butterflies' species richness, IDC and ELIA, and between birds' species richness and energy information. Our findings support the view that strong relationships between farming energy flows, agroecosystem functioning and biodiversity can be detected, and highlight the importance of farmers' knowledge and labour to maintain bio-cultural landscapes. © 2019 Elsevier B.V.
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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