Local management and landscape drivers of pollination and biological control services in a Kenyan agro-ecosystem

Arthropods that have a direct impact on crop production (i.e. pests, natural enemies and pollinators) can be influenced by both local farm management and the context within which the fields occur in the wider landscape. However, the contributions and spatial scales at which these drivers operate and interact are not fully understood, particularly in the developing world. The impact of both local management and landscape context on insect pollinators and natural enemy communities and on their capacity to deliver related ecosystem services to an economically important tropical crop, pigeonpea was investigated. The study was conducted in nine paired farms across a gradient of increasing distance to semi-native vegetation in Kibwezi, Kenya. Results show that proximity of fields to semi-native habitats negatively affected pollinator and chewing insect abundance. Within fields, pesticide use was a key negative predictor of pollinator, pest and foliar active predator abundance. On the contrary, fertilizer application significantly enhanced pollinator and both chewing and sucking insect pest abundance. At a 1 km spatial scale of fields, there were significant negative effects of the number of semi-native habitat patches within fields dominated by mass flowering pigeonpea on pollinators abundance. For service provision, a significant decline in fruit set when insects were excluded from flowers was recorded. This study reveals the interconnections of pollinators, predators and pests with pigeonpea crop. For sustainable yields and to conserve high densities of both pollinators and predators of pests within pigeonpea landscapes, it is crucial to target the adoption of less disruptive farm management practices such as reducing pesticide and fertilizer inputs.

The impact of an insecticide on insect flower visitation and pollination in an agricultural landscape

1 Pesticides are considered a threat to pollinators but little is known about the potential impacts of their widespread use on pollinators. Less still is known about the impacts on pollination, comprising the ecosystem service that pollinators provide to wildflowers and crops. 2 The present study measured flower visitation and pollination in an agricultural landscape, by placing potted flowering plants (Petunia sp.) in vine fields sprayed with a highly toxic insecticide (fenitrothion). During two sampling rounds, insect visitors to the petunias were observed and measures of pollination were recorded by counting and weighing seeds. 3 In the earlier sampling round, a lower species richness of insect visitors was observed in fields that had received an early application of insecticide. No negative impacts were found from later applications. The results obtained suggest a greater potential harm to insect pollinators and flower visitation as a result of insecticide application early in the season. 4 No reduction in pollination was found in fields that received an early insecticide application. Pollination was greater with two insecticide applications between sampling rounds rather than one application. 5 In the present study system, insecticide application had a negative effect on pollinators but a possible positive effect on pollination services. In some cases, it may be that actions for conserving biodiversity will not benefit pollination services to all plants.

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics.

The effects of landscape modifications on the long-term persistence of animal populations

Background: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Methodology/Principal Findings: Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Significance: Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.