Moira C. Williams

Effects of Land Use on Threatened Species

There is widespread agreement that biodiversity loss must be reduced, yet to alleviate threats to plant and animal species, the forces driving these losses need to be better understood. We searched for explanatory variables for threatened-species data at the country level through land-use information instead of previously used socioeconomic and demographic variables. To explain the number of threatened species in one country, we used information on land-use patterns in all neighboring countries and on the extent of the countrys sea border. We carried out multiple regressions of the numbers of threatened species as a function of land-use patterns, and we tested various specifications of this function, including spatial autocorrelation. Most cross-border land-use patterns had a significant influence on the number of threatened species, and land-use patterns explained the number of threatened species better than less proximate socioeconomic variables. More specifically, our overall results showed a highly adverse influence of plantations and permanent cropland, a weaker negative influence of permanent pasture, and, for the most part, a beneficial influence of nonarable lands and natural forest. Surprisingly, built-up land also showed a conserving influence on threatened species. The adverse influences extended to distances between about 250 km (plants) and 2000 km (birds and mammals) away from where the species threat was recorded, depending on the species. Our results highlight that legislation affecting biodiversity should look beyond national boundaries.

Managing Alien Plants for Biodiversity Outcomes—the Need for Triage

Abstract Recognition that alien plants pose a significant threat to biodiversity has not always translated into effective management strategies, policy reforms, and systems to establish priorities. Thus, many alien plant management decisions for the protection of biodiversity occur with limited knowledge of what needs to be protected (other than biodiversity in a generalized sense) or the urgency of actions. To rectify this, we have developed a triage system that enables alien plant management decisions to be made based on (1) the urgency of control relative to the degree of threat posed to biodiversity, compared with (2) the likelihood of achieving a successful conservation outcome as a result of alien plant control. This triage system is underpinned by a two-step approach, which identifies the biodiversity at risk and assesses sites to determine priorities for control. This triage system was initially developed to manage the threat posed by bitou bush to native species in New South Wales (NSW), Australia. It has subsequently been improved with the national assessment of lantana in Australia, and the adaptation from a single to multiple alien plant species approach on a regional scale. This triage system identifies nine levels of priority for alien plant management aimed at biodiversity conservation, ranging from immediate, targeted action to limited or no action. The development of this approach has enabled long-term management priorities to be set for widespread alien plants that are unlikely to be eradicated. It also enables control to occur in a coordinated manner for biodiversity conservation at a landscape scale, rather than as a series of individual unconnected short-term actions. Nomenclature: Bitou bush, Chrysanthemoides monilifera (L.) Norl.; lantana, Lantana camara L.

Modelling Interactions Between Economic Activity, Greenhouse Gas Emissions, Biodiversity and Agricultural Production

In this article, we develop a modelling approach which examines selected drivers of ecosystem functioning and agricultural productivity. In particular, we develop linkages between land use and biodiversity and between biodiversity and agricultural productivity. We review the literature for quantitative estimates of key relationships and their parameters for modelling human consumption, land use, energy use, and greenhouse gas emissions on biodiversity and agricultural productivity. We assemble these specifications into an iterative causal model and carry out a number of scenario projections of country-level consumption, production, land use, energy use, greenhouse gas emissions, species diversity, and agricultural production up to 2050. Finally, we dissect the projections into key drivers using structural decomposition and sensitivity analyses.