Estimating effects of arable land use intensity on farmland birds using joint species modeling

Individual differences in habitat selection mediate landscape level predictions of a functional response

Predicting future space use by animals requires models that consider both habitat availability and individual differences in habitat selection. The functional response in habitat selection posits animals adjust their habitat selection to availability, but population-level responses to availability may differ from individual responses. Generalized functional response (GFR) models account for functional responses by including fixed effect interactions between habitat availability and selection. Population-level resource selection functions instead account for individual selection responses to availability with random effects. We compared predictive performance of both approaches using a functional response in elk (Cervus canadensis) selection for mixed forest in response to road proximity, and avoidance of roads in response to mixed forest availability. We also investigated how performance changed when individuals responded differently to availability from the rest of the population. Individual variation in road avoidance decreased performance of both models (random effects: β = 0.69, 95% CI 0.47, 0.91; GFR: β = 0.38, 95% CI 0.05, 0.71). Changes in individual road and forest availability affected performance of neither model, suggesting individual responses to availability different from the functional response mediated performance. We also found that overall, both models performed similarly for predicting mixed forest selection (F_{1, 58} = 0.14, p = 0.71) and road avoidance (F_{1, 58} = 0.28, p = 0.60). GFR estimates were slightly better, but its larger number of covariates produced greater variance than the random effects model. Given this bias-variance trade-off, we conclude that neither model performs better for future space use predictions.

Optimizing Species Richness in Mosaic Landscapes: A Probabilistic Model of Species-Area Relationships

Most landscapes are comprised of multiple habitat types differing in the biodiversity they contain. This is certainly true for human modified landscapes, which are often a mix of habitats managed with different intensity, semi-natural habitats and even pristine habitats. To understand fundamental questions of how the composition of such landscapes affects biodiversity conservation, and to evaluate biodiversity consequences of policies that affect the composition of landscapes, there is a need for models able to translate information on biodiversity from individual habitats to landscape-wide predictions. However, this is complicated by species richness not being additive. We constructed a model to help analyze and solve this problem based on two simple assumptions. Firstly, that a habitat can be characterized by the biological community inhabiting it; i.e., which species occur and at what densities. Secondly, that the probability of a species occurring in a particular unit of land is dictated by its average density in the associated habitats, its spatial aggregation, and the size of the land unit. This model leads to a multidimensional species-area relation (one dimension per habitat). If the goal is to maximize species diversity at the landscape scale (γ-diversity), within a fixed area or under a limited budget, the model can be used to find the optimal allocation of the different habitats. In general, the optimal solution depends on the total size of the species pool of the different habitats, but also their similarity (β-diversity). If habitats are complementary (high β), a mix is usually preferred, even if one habitat is poorer (lower α diversity in one habitat). The model lends itself to economic analyses of biodiversity problems, without the need to monetarize biodiversity value, i.e., cost-effectiveness analysis. Land prices and management costs will affect the solution, such that the model can be used to estimate the number of species gained in relation to expenditure on each habitat. We illustrate the utility of the model by applying it to agricultural landscapes in southern Sweden and demonstrate how empirical monitoring data can be used to find the best habitat allocation for biodiversity conservation within and between landscapes.

A comprehensive approach for agroecosystem services and disservices valuation

The use of the ecosystem services approach for ecosystem management, including the valuation of ecosystem services, has grown in recent decades. Although a common framework is used, each ecosystem has its own characteristics. The agroecosystem, for example, is an anthropised ecosystem where ecosystem service flows are highly interrelated with the environment, positively or negatively. Therefore, agroecosystem services are usually accompanied by disservices. The valuation of agroecosystem services and disservices requires adaptation of existing ecosystem services paradigms to accommodate the innate agroecosystem idiosyncrasies. To this end, in this study, a comprehensive approach for valuation of agroecosystem services and disservices was proposed and validated in a semi-arid western Mediterranean agricultural area through stakeholder assessment, using a choice experiment. The results suggest that all categories of services (provisioning, regulating, and cultural) should be taken into account when valuing agroecosystem services and disservices. In particular, food provision (a provisioning service), water (a provisioning disservice), local climate regulation and biodiversity (regulating services), waste treatment and water purification (regulating disservices), and recreation and tourism (cultural services) are relevant for this purpose. Their relative importance in agroecosystems valuation reached 70% for agroecosystem services and 30% for disservices. Specifically, biodiversity (38%) emerged as the most relevant agroecosystem service to be valued, followed by recreation and tourism (20%), local climate regulation (7%), and food provision (5%). Among the agroecosystem disservices, water and waste treatment (15%), and water purification (15%) together contributed to 30% of the total importance. Agroecosystems should be valued considering their multifunctional character and the integration of agroecosystem services and disservices.

Landscape-scale terrestrial factors are also vital in shaping Odonata assemblages of watercourses

Habitat loss and fragmentation causes a decline in insect populations. Odonata (both dragonflies and damselflies) are especially threatened by the destruction of both aquatic and terrestrial environment. Moreover, effects of large-scale habitat heterogeneity on Odonata assemblages are poorly studied. In a two years study along East-European lowland watercourses both aquatic and terrestrial environment were studied to reveal the importance of local (e.g. water depth, macrovegetation cover, etc.) and landscape-scale (e.g. farmland patch size, forest patch proportion, etc.) variables to Odonata (as well as to dragonflies and damselflies separately) through increasing spatial sampling scales. The specimens were sampled using 500 m long transects from May to September. Results, both on local and landscape scales emphasized the importance of terrestrial environment on Odonata. Local variables influence damselflies, while dragonflies are more sensitive to landscape variables. Damselfly’s diversity decreased with increasing macrovegetation cover, while dragonfly’s diversity decreased with the increasing degree of land use intensification, but increased with the length of watercourses. It is thus vital to stress the importance of partial watercourse clearing, and moderate maintenance of traditional farm management based on small parcel farming near watercourses to maintain diverse and healthy Odonata assemblages.