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CORMON, X., LOOTS, C., VAZ, S., VERMARD, Y., & MARCHAL, P. (2014). Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) in the North Sea. Ices Journal Of Marine Science, 71(6), 1342–1355.
Résumé: Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) were investigated in the North Sea. Saithe is a well-established species in the North Sea, while occurrence of the less common hake has recently increased in the area. Spatial dynamics of these two species and their potential spatial interactions were explored using binomial generalized linear models (GLM) applied to the International Bottom Trawl Survey (IBTS) data from 1991 to 2012. Models included different types of variables: (i) abiotic variables including sediment types, temperature, and bathymetry; (ii) biotic variables including potential competitors and potential preys presence; and (iii) spatial variables. The models were reduced and used to predict and map probable habitats of saithe, hake but also, for the first time in the North Sea, the distribution of the spatial overlap between these two species. Changes in distribution patterns of these two species and of their overlap were also investigated by comparing species' presence and overlap probabilities predicted over an early (1991–1996) and a late period (2007–2012). The results show an increase in the probability over time of the overlap between saithe and hake along with an expansion towards the southwest and Scottish waters. These shifts follow trends observed in temperature data and might be indirectly induced by climate changes. Saithe, hake, and their overlap are positively influenced by potential preys and/or competitors, which confirms spatial co-occurrence of the species concerned and leads to the questions of predator–prey relationships and competition. Finally, the present study provides robust predictions concerning the spatial distribution of saithe, hake, and of their overlap in the North Sea, which may be of interest for fishery managers.
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Hattab, T., Albouy, C., Lasram, F. B. R., Somot, S., Le Loc'h, F., & Leprieur, F. (2014). Towards a better understanding of potential impacts of climate change on marine species distribution: a multiscale modelling approach. Global Ecology and Biogeography, 23(12), 1417–1429.
Résumé: Aim In this paper, we applied the concept of ‘hierarchical filters’ in community ecology to model marine species distribution at nested spatial scales. Location Global, Mediterranean Sea and the Gulf of Gabes (Tunisia). Methods We combined the predictions of bioclimatic envelope models (BEMs) and habitat models to assess the current distribution of 20 exploited marine species in the Gulf of Gabes. BEMs were first built at a global extent to account for the full range of climatic conditions encountered by a given species. Habitat models were then built using fine-grained habitat variables at the scale of the Gulf of Gabes. We also used this hierarchical filtering approach to project the future distribution of these species under both climate change (the A2 scenario implemented with the Mediterranean climatic model NEMOMED8) and habitat loss (the loss of Posidonia oceanica meadows) scenarios. Results The hierarchical filtering approach predicted current species geographical ranges to be on average 56% smaller than those predicted using the BEMs alone. This pattern was also observed under the climate change scenario. Combining the habitat loss and climate change scenarios indicated that the magnitude of range shifts due to climate change was larger than from the loss of P. oceanica meadows. Main conclusions Our findings emphasize that BEMs may overestimate current and future ranges of marine species if species–habitat relationships are not also considered. A hierarchical filtering approach that accounts for fine-grained habitat variables limits the uncertainty associated with model-based recommendations, thus ensuring their outputs remain applicable within the context of marine resource management.
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Lembrechts, J. J., Lenoir, J., Roth, N., Hattab, T., Milbau, A., Haider, S., et al. (2019). Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Glob. Ecol. Biogeogr., 28(11), 1578–1596.
Résumé: Aim Although species distribution models (SDMs) traditionally link species occurrences to free-air temperature data at coarse spatio-temporal resolution, the distribution of organisms might instead be driven by temperatures more proximal to their habitats. Several solutions are currently available, such as downscaled or interpolated coarse-grained free-air temperatures, satellite-measured land surface temperatures (LST) or in-situ-measured soil temperatures. A comprehensive comparison of temperature data sources and their performance in SDMs is, however, currently lacking. Location Northern Scandinavia. Time period 1970-2017. Major taxa studied Higher plants. Methods We evaluated different sources of temperature data (WorldClim, CHELSA, MODIS, E-OBS, topoclimate and soil temperature from miniature data loggers), differing in spatial resolution (from 1 '' to 0.1 degrees), measurement focus (free-air, ground-surface or soil temperature) and temporal extent (year-long versus long-term averages), and used them to fit SDMs for 50 plant species with different growth forms in a high-latitudinal mountain region. Results Differences between these temperature data sources originating from measurement focus and temporal extent overshadow the effects of temporal climatic differences and spatio-temporal resolution, with elevational lapse rates ranging from -0.6 degrees C per 100 m for long-term free-air temperature data to -0.2 degrees C per 100 m for in-situ soil temperatures. Most importantly, we found that the performance of the temperature data in SDMs depended on the growth forms of species. The use of in-situ soil temperatures improved the explanatory power of our SDMs (R-2 on average +16%), especially for forbs and graminoids (R-2 +24 and +21% on average, respectively) compared with the other data sources. Main conclusions We suggest that future studies using SDMs should use the temperature dataset that best reflects the ecology of the species, rather than automatically using coarse-grained data from WorldClim or CHELSA.
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Meynard, C. N., Leroy, B., & Kaplan, D. M. (2019). Testing methods in species distribution modelling using virtual species: what have we learnt and what are we missing? Ecography, 42(12), 2021–2036.
Résumé: Species distribution models (SDMs) have become one of the major predictive tools in ecology. However, multiple methodological choices are required during the modelling process, some of which may have a large impact on forecasting results. In this context, virtual species, i.e. the use of simulations involving a fictitious species for which we have perfect knowledge of its occurrence–environment relationships and other relevant characteristics, have become increasingly popular to test SDMs. This approach provides for a simple virtual ecologist framework under which to test model properties, as well as the effects of the different methodological choices, and allows teasing out the effects of targeted factors with great certainty. This simplification is therefore very useful in setting up modelling standards and best practice principles. As a result, numerous virtual species studies have been published over the last decade. The topics covered include differences in performance between statistical models, effects of sample size, choice of threshold values, methods to generate pseudo-absences for presence-only data, among many others. These simulations have therefore already made a great contribution to setting best modelling practices in SDMs. Recent software developments have greatly facilitated the simulation of virtual species, with at least three different packages published to that effect. However, the simulation procedure has not been homogeneous, which introduces some subtleties in the interpretation of results, as well as differences across simulation packages. Here we 1) review the main contributions of the virtual species approach in the SDM literature; 2) compare the major virtual species simulation approaches and software packages; and 3) propose a set of recommendations for best simulation practices in future virtual species studies in the context of SDMs.
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