Coordinator: Dr. Michel Baguette

Participating countries: FR, UK, DE

Habitat loss and fragmentation may thus not only reduce biodiversity in terms of species numbers, but also may affect genetic structure and viability of a single species. It is crucial to understand how organisms are able to effectively disperse in largely human affected landscapes (landscape connectivity), and what would be an impact of management decisions.

‘TenLamas’ is a project in which empiricists and modellers cooperate in order to develop and better mechanistic understanding of the behavioural mechanisms underlying dispersal. We investigate relative performances of the different approaches currently used to predict dispersal across heterogeneous landscapes. Models utilising least-cost paths algorithms will be compared with detailed simulation models of individual movement behaviour. Two organisms, for which suitable long term data exist, have been selected as model species. These are the bog fritillary (Proclossiana eunomia) butterfly and viviparous lizard (Lacerta vivipara). Realistic individual-based models of animal movement, taking advantage of different modelling frameworks (i.e. lattice vs. continuous space) will be build for both species, depending on the species-specific characteristics of movement strategies, and species’ life history in general.

The effectiveness of conservation areas (nature reserves and parks, N2k network) is impacted by dispersal, especially, if single sites are unlikely to guarantee long-term persistence of local populations. Consequently, dispersal is a key mechanism for the determining alpha and beta, and generating gamma diversity. Dispersal, however, is affected by changes in the size of source populations and/or modifications in the distances between suitable habitat patches in the landscape. In the current context of global change, anthropogenic disturbances may force organisms to move along environmental gradients. Yet, this response may be strongly truncated by habitat fragmentation, as it may prove difficult for organisms to disperse from one (formerly) suitable habitat patch to another in highly fragmented landscapes where interpatch distances are increasingly larger. To counter the deleterious effect of local population isolation (extinction vortex) and hence to increase metapopulation viability, conservation strategies explicitly focus on ecological networks that should allow organisms to move among remnant habitats and local populations. However, network functionality has rarely been tested. It will largely be determined by the network’s net effect on the mobility of the target organisms, which in turn depends on landscape features and on the target organism’s ecological attributes, especially the rules according to which it takes its movement decisions. Accordingly, there is a clear need for conservation instruments that derive functional connectivity for a set of target organisms from the characteristics of landscapes or existing networks of protected areas. These instruments should have the capability to predict both the colonizability of vacant habitat patches and the rate of immigration into existing populations and should also facilitate the balancing of potentially conflicting interests when conservation efforts target different species or diversity at large. TenLamas will evaluate alternative models for assessing the value of particular ecological networks and for comparing different scenarios of landscape management. The final objective of the project is to deliver recommendations for the suitability of different tools to evaluate connectivity of landuse scenarios and projected networks. We will achieve this goal by testing the relative performance of the different approaches currently used to predict dispersal across real heterogeneous landscapes, i.e. landscape connectivity. From simple to complex, current connectivity estimates are

(1) synthetic parameter of structural connectivity that is a function of the presence/distribution, and either the area or the length of, habitat corridors or stepping stones,

(2) general pattern-based algorithms based on least-cost paths and

(3) the use of detailed simulation models of individual behaviour (generating most probable paths).

In TenLamas we will evaluate the relative accuracy of these concurrent connectivity estimates for selected model species in test landscapes with respect to the required level of precision in landscape and organism information. Practically, this evaluation will be performed by supplying dispersal matrices generated by these three approaches to a simple model, using metapopulation viability and genetic structure as dependent variable. We expect that precision will decrease from individual-based models to pattern-based algorithms to structural connectivity estimates. Both the metapopulation and the metacommunity concept emphasize the importance of dispersal respectively for the persistence of species in fragmented landscapes and the functioning of ecosystems. Landscape connectivity is considered as mirroring this crucial role in practical landscape management measures. Accordingly, current methods used to build ecological networks consist of looking for ecological structures based on the continuity of broadly defined ecosystems (forests, wetlands) at wide spatial scales (1/100k or less). The main problem with this top-down approach is that it is by no means a possibility to predict if such structures limit isolation and enhance metapopulation viability. We propose to adopt bottom-up logic for ecological network implementation: their design should start from the real ecological problem - the isolation of populations within landscapes. It is obviously impossible to test all species in all landscapes. Accordingly, we want to provide a toolbox that generates clear statements about the relative accuracy of predictive tools of functional connectivity. We think that this assessment is an indispensable step in the development of functional ecological networks and is the main added value of our project.