Linking field experiments to long-term simulation of impacts of nitrogen deposition on heathlands and moorlands

The results from three long-term field manipulation studies of the impacts of increased nitrogen deposition (0–120 kg N ha^–1 yr^–1) on lowland and upland heathlands in the UK were compared, to test if common responses are observed. Consistent increases in Calluna foliar N content and decreases in litter C:N ratios were found across all sites, while increases in N leaching were not observed at any site over the range 0–80 kg ha^–1 yr^–1. However, the response of Calluna biomass did vary between sites, possibly reflecting site differences in nutrient status and management histories. Five versions of a simulation model of heathland responses to N were developed, each reflecting different assumptions about the fate and turnover of soil N. Model outputs supported the deduction from mass balance calculations at two of the field sites that N additions have resulted in an increase in immobilisation; the latter was needed to prevent the model overestimating measured N leaching. However, this version of the model significantly underestimated Calluna biomass. Model versions, which included uptake of organic N by Callunaand re-mobilisation of N from the soil organic store provided some improvement in the fit between modelled and field biomass data, but re-mobilisation also led to an overestimation of N leaching. Quantification of these processes and their response to increased N deposition are therefore critical to interpreting experimental data and predicting the long-term impacts of atmospheric deposition on heathlands and moorlands.     

Effect of pollinator abundance on self-fertilization and gene flow: application to GM Canola.

Cross-pollination from fields of transgenic crops is of great public concern. Although cross-pollination in commercial canola (Brassica napus) fields has been empirically measured, field trials are expensive and do not identify the causes of cross-pollination. Therefore, theoretical models can be valuable because they can provide estimates of cross-pollination at any given site and time. We present a general analytical model of field-to-field gene flow due to the following competing mechanisms: the wind, bees, and autonomous pollination. We parameterize the model for the particular case of field-to-field cross-pollination of genetically modified (GM) canola via the wind and via bumble bees (Bombus spp.) and honey bees (Apis mellifera). We make extensive use of the large data set of bee densities collected during the recent U.K. Farm Scale Evaluations. We predict that canola approaches almost full seed set without pollinators and that autonomous pollination is responsible for > or = 25% of seed set, irrespective of pollinator abundance. We do not predict the relative contribution of bees vs. the wind in landscape-scale gene flow in canola. However, under model assumptions, we predict that the maximum field-to-field gene flow due to bumble bees is 0.04% and 0.13% below the current EU limit for adventitious GM presence for winter- and spring-sown canola, respectively. We predict that gene flow due to bees is approximately 3.1 times higher at 20% compared to 100% male-fertility, and due to the wind, 1.3 times higher at 20% compared to 100% male-fertility, for both winter- and spring-sown canola. Bumble bee-mediated gene flow is approximately 2.7 times higher and wind-mediated gene flow approximately 1.7 times lower in spring-sown than in winter-sown canola, regardless of the degree of male-sterility. The model of cross-pollination due to the wind most closely predicted three previously published observations: field-to-field gene flow is low; gene flow increases with the proportion of plants that are male-sterile; and gene flow is higher in winter- than in spring-sown canola. Our results therefore suggest that the wind, not bees, is the main vector of long-distance gene flow in canola.     

Stakeholder perspectives on the value proposition of enterprise-level natural capital accounting for three primary industries

Environment Systems and Decisions - Globally we are experiencing a decline in aggregate natural capital. Many primary industries and enterprises are highly dependent on renewable and non-renewable...