Biodiversity and the mitigation of climate change through bioenergy: impacts of increased maize cultivation on farmland wildlife

The public promotion of renewable energies is expected to increase the number of biogas plants and stimulate energy crops cultivation (e.g. maize) in Germany. In order to assess the indirect effects of the resulting land‐use changes on biodiversity, we developed six land‐use scenarios and simulated the responses of six farmland wildlife species with the spatially explicit agent‐based model system ALMaSS. The scenarios differed in composition and spatial configuration of arable crops. We implemented scenarios where maize for energy production replaced 15% and 30% of the area covered by other cash crops. Biogas maize farms were either randomly distributed or located within small or large aggregation clusters. The animal species investigated were skylark (Alauda arvensis), grey partridge (Perdix perdix), European brown hare (Lepus europaeus), field vole (Microtus agrestis), a linyphiid spider (Erigone atra) and a carabid beetle (Bembidion lampros). The changes in crop composition had a negative effect on the population sizes of skylark, partridge and hare and a positive effect on the population sizes of spider and beetle and no effect on the population size of vole. An aggregated cultivation of maize amplified these effects for skylark. Species responses to changes in the crop composition were consistent across three differently structured landscapes. Our work suggests that with the compliance to some recommendations, negative effects of biogas‐related land‐use change on the populations of the six representative farmland species can largely be avoided.     

‘Murundus’ structures in the semi-arid region of Brazil: testing their geographical congruence with mound-building termites (Blattodea: Termitoidea: Termitidae)

Summary. Earth mounds called ‘murundus’ are conspicuous features in the semi-arid region of Brazil, where their distribution and origin remain largely unknown. We adopted an approach based on spatially explicit mapping and modeling to determine the current and potential geographical distribution of murundus. We set up a systematic grid survey to map their current distribution using high-resolution satellite imagery available via free open source software. To obtain insights into the origin of these earth mounds, predictive models were used to test their geographical congruence with six mound-building termites (genera Cornitermes Wasmann, 1897, and Syntermes Holmgren, 1909). The Maxent algorithm was used to generate the potential distribution models based on a set of five variables related to primary environmental regimes that determine the fundamental niche of termite species. To analyze if there was some congruence between associated environmental variables, we cross-checked the results obtained from the statistical tests using MAXENT software. Murundus mostly occur in the south-central region of the Caatinga biome (i.e. seasonally dry tropical forest) in areas with moderate annual mean temperature (20–24°C) and precipitation (600–910 mm), and soils with moderate to severe constraints concerning nutrient availability. We observed a strong geographical congruence between the potential distributions of densely packed murundus and four mound-building termites [i.e. Cornitermes bequaerti Emerson, 1952, C. silvestrii Emerson, 1949, Syntermes dirus (Burmeister, 1839) and S. wheeleri (Emerson, 1925)]. Based on the significant association of those distributions with the climate and soil nutrient availability, we concluded that the formation of murundus in the semi-arid domain might be an adaptive response of mound-building termites to particular regional environmental conditions.     

Modelling the Expansion of a Grey Squirrel population: Implications for Squirrel Control

A recently discovered population of the North American grey squirrel (Sciurus carolinensis), introduced to Ticino Park, Lombardy (N Italy), is likely to spread into continuous prealpine broadleaf forests of Lombardy and the south of Switzerland. We used Spatially Explicit Population Dynamics Models (SEPMs), successfully used to predict the spread of grey squirrels in England and Piedmont, Italy, to examine the effects of different control scenarios on grey squirrel expansion in a 20000 km² area around Ticino Park. Without control, grey squirrels will invade Switzerland within the next two decades, and, concomitantly, the size and distribution of local populations of native red squirrels will be reduced. Simulating different grey squirrel control or removal scenarios suggests that: (i) efficient control is possible and mainly determined by the spatial distribution and woodland size of the ‘target’ control areas; and (ii) immediate actions must be taken, since delay in grey squirrel control will result in the population increasing and spreading, which makes the problems of successful containment more difficult. Model scenarios were based on surveys that may underestimate the real distribution range and current population size of grey squirrels. Therefore, a combination of hair–tube monitoring and a public participation survey to detect grey squirrel presence, which may also help to increase public awareness, is recommended. Successful containment of further grey squirrel spread will require local co-operation between Italian and Swiss authorities involved in wildlife management.     

Simulating natural selection in landscape genetics

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially-explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors--mutation, gene flow, genetic drift and selection--that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces). We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency. The program provides a valuable tool (cdpop v1.0; http://cel.dbs.umt.edu/software/CDPOP/) for the study of evolutionary landscape genetics that allows explicit evaluation of the interactions between gene flow and selection in complex landscapes.