a b s t r a c tSpecies conservation largely depends on knowledge of habitat needs of target species. GIS-models are increasingly used to assess habitat preferences and distribution of target species, but their accuracy is constrained by availability of digital data layers. We developed a two-steps approach aiming at showing pros and cons of landscape (GIS)-and site-level habitat models, identifying key habitat factors for conservation of a threatened bird species, the red-backed shrike Lanius collurio. A spatially explicit GIS-model was generated using landscape variables, and a second model at site level was developed using fine-scale variables measured on the ground. The GIS-based model was then extrapolated to the entire region to obtain a map of distribution of suitable habitats. Positive associations between shrike occurrence and both hedgerow length and partial shrub cover were detected at both scales. Shrikes were also positively associated with grassland cover at landscape level and with partial cover of untilled herbaceous vegetation at the finer scale, and negatively affected by lucerne cover. The GIS-model led to an affordable map of predicted habitat suitability which should help conservationists to focus on different local priorities, but was unable to identify effects of untilled and lucerne cover. Site-level model gave fine details for habitat management, but its application elsewhere requires ground-measurements of factors. Combining the multiscale models could indicate more urgent actions at large scales (e.g. maintaining suitable habitats, or improving connectivity among isolated patches) and draw a detailed figure of the most suitable habitat for the species. Shrike occurrence was associated with a higher number of shrub and tree species: the indicator value of the species should ensure general benefits for biodiversity from dedicated management.
Land-use changes have strong impacts on biological communities. Among them, land abandonment is threatening a large number of conservation-concern species associated with semi-natural habitats shaped by 'traditional' farming. We focused on the red-backed shrike as a model for investigating the effect of land abandonment on a threatened bird species, and used historical data to model dynamic scenarios. We explored variations in habitat suitability from the 1950s to the present and predicted possible future variations. After investigating local habitat preferences of the species, we formulated a spatially explicit model of habitat suitability for shrikes according to current land-use types; then, we evaluated past habitat suitability, by applying the model to three known past scenarios, and simulated the habitat changes after land abandonment. By combining a habitat-association approach with past and future land use scenarios, we assessed and predicted the effects of habitat changes caused by abandonment. Shrike occurrence was favoured by the cover of four types of grassland and of shrubland with trees, and negatively affected by broadleaved woodlands. The current average habitat suitability is less than half of what it was in the 1950s. Future predictions in a complete abandonment scenario suggest that important decrease could be expected 10 or 20 years after abandonment, and that after 30 years the red-backed shrike would be completely extinct. Alternative scenarios involving partial abandonment suggested that subsidy policies may mitigate the effects of abandonment. Knowing land-use dynamics allowed the exploration of effects of land-use changes and corroborated the importance of low-intensity farming for conservation.
SummaryCorrelative species distribution models (SDMs) are increasingly widespread in the conservation literature. They can be used for a variety of purposes, including addressing practical conservation tasks on the basis of a spatially explicit assessment of environmental suitability for target taxa, which in turn allows for a transparent evaluation of needs and opportunities. Here we used the maximum entropy method (by means of the software MaxEnt) to model distribution of the rare Boreal Owl Aegolius funereus and the Black Woodpecker Dryocopus martius, which excavates the nest-holes used by the owl for breeding. We believe that monitoring surveys for Boreal Owl should consider areas suitable for both species as priority sites, whereas the provision of nest-boxes for the owl may be particularly desirable in habitat patches that are suitable for that species but not for the keystone species whose nest-holes represent the usual nest site for the owl. Finally, areas suitable for both species can represent priority areas for the conservation of forest birds in the Alps, as both species have been reported as umbrella and/or keystone species. Our example provides a possible framework to model management and monitoring opportunities in other species or species pairs, but such an approach can be used to infer the need for particular management options when both limiting factors and species distribution can be spatially modelled, and also to model the areas where different target species are more likely to overlap and interact. The use of distribution models as tools to address practical conservation tasks should also be encouraged in order to accomplish practical tasks according to sound knowledge and transparent methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.