Bioenergy production and Skylark (Alauda arvensis) population abundance – a modelling approach for the analysis of land‐use change impacts and conservation options

Abstract

Bioenergy production is seen as one way of meeting future energy needs. The growing demand for biomass for energy production induces the cultivation of a few fast growing and high-yielding energy crops on vast areas of arable land. This land-use change has been found associated with the reduction of habitat suitability for farmland birds and a decline in farmland biodiversity in general. A large number of studies have assessed the ecological effects of energy crop cultivation at the local scale of a single field. This study focuses on regional landscape changes caused by increased energy crop cultivation, which includes reduction of crop-type richness and spatial concentration of single crop-types. We present a spatially explicit ecological model to assess the population-level consequences of these effects on the abundance of the farmland bird species Skylark (Alauda arvensis). We also investigate the impacts of different land-use scenarios and aim to identify adaptive conservation options. We show that (1) the impacts of increased energy crop cultivation on Skylark population abundance depend strongly on the landscape structure; (2) impacts could be tolerated as long as a certain minimum level of crop-type heterogeneity is retained at the landscape level and (3) conservation actions are required and effective especially on landscapes where crop-field size is large.

Emerging Opportunities for Landscape Ecological Modelling

“…Neutral landscapes have been shown to be statistically similar to real landscapes, but are unable to reproduce all landscape features [76,81]. Thus, there are continuing developments to NLM methods to improve the representation of real landscape features such as patterns of land-ownership [82] and agricultural fields [83]. In addition to extensions of NLM models to incorporate increasing numbers of features, progress has also been made on developing the algorithms such that they are more efficient and free of some undesirable artefacts present in earlier versions [77].…”

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

“…Another important lesson emerges from the fact that, unlike many other models, G-RaFFe produces fields that are clean of natural habitat. That this yielded high performance demonstrates the unique attribute of human-dominated land-uses, namely, the rarity or absence of natural features apart from those remaining along property margins (see also [25] for purely agricultural lands). Similarly, most pattern-based models for generating fragmented landscapes tend to overlook the fact that human activities often result in a non-random association of land-cover types [10], with sharp contrast between patches of natural areas and neighboring, often homogeneous anthropogenic land types [53].…”

“…Simmap [24] is another neutral landscape model, which produces clustered patchy landscapes by assigning neighboring cells to the cell with the highest local density within a 3×3 neighborhood - an approach similar to Hiebeler [8], which applies a modal filter as in digital image processing techniques [24]. Another, newer generation of models attempts to reproduce also the spatial patterns that typify agricultural areas [25].…”

Bioenergy and Biodiversity: Key Lessons from the Pan American Region

“…Biomass sourced from diverse prairie plantings may support greater bird and insect diversity including pollinators Myers et al 2012;Werling et al 2014). However, these benefits depend on landscape-scale patterns that thoughtfully integrate land management and harvesting for bioenergy with surrounding ecosystems (Engel et al 2012;Robertson et al 2012;Werling et al 2014). Most management interventions favor some taxonomic groups over others (Stanley and Stout 2013), underscoring the importance of placebased analysis and planning that begin with understanding local concerns and priority targets for biodiversity conservation and other ecosystem services.…”