Appropriate metrics to inform farmers about species diversity

Abstract

Farmers are key players in actions to halt biodiversity loss from farmland. However, if farmers are to sustain biodiversity, they must first be adequately informed about biodiversity and understand its drivers. Measuring biodiversity at the farm scale is difficult because of the structural complexity of many farms, and because different aspects of diversity can be considered desirable, e.g. species richness or rarity. In this study we examined 19 grassland farms in Central Switzerland, and sampled plants, earthworms, spiders and bees using a stratified sampling design. We considered several metrics of species diversity, but found two particularly useful at farm scale: average richness (area-weighted) and farm uniqueness in terms of species identity. Average richness reflects the expected species richness in a random sample taken on the farm, and farm uniqueness is the contribution of a farm to the total species richness of all farms under study. Average richness and farm uniqueness are complementary and reflect different aspects of biodiversity. We demonstrate how combining these metrics enables tailored recommendations for enhancing species diversity on the farm. AbstractFarmers are key players in actions to halt biodiversity loss from farmland. However, if farmers are to sustain biodiversity, they must first be adequately informed about biodiversity and understand its drivers. Measuring biodiversity at the farm scale is difficult because of the structural complexity of many farms, and because different aspects of diversity can be considered desirable, e.g. species richness or rarity. In this study we examined 19 grassland farms in Central Switzerland, and sampled plants, earthworms, spiders and bees using a stratified sampling design. We considered several metrics of species diversity, but found two particularly useful at farm scale: average richness (area-weighted) and farm uniqueness in terms of species identity. Average richness reflects the expected species richness in a random sample taken on the farm, and farm uniqueness is the contribution of a farm to the total 2 species richness of all farms under study. Average richness and farm uniqueness are complementary and reflect different aspects of biodiversity. We demonstrate how combining these metrics enables tailored recommendations for enhancing species diversity on the farm.

Motivations and attitudes influence farmers' willingness to participate in biodiversity conservation contracts

“…It has been shown elsewhere that farmers require a much better understanding of biodiversity in general and as it relates to their farm. Lüscher et al (2014) suggested two complementary metrics particularly helpful in a Swiss context: richness -i.e. number of species found on the farm and uniqueness -thereby encapsulating the contribution of the farm to total species richness of the region.…”

Relating costs to the user value of farmland biodiversity measurements

“…in the context of pesticide and GMO regulation (Firbank et al, 2003;White, 2005;Zabel and Roe, 2009;Hanley et al, 2012). Also, reporting the biodiversity status of farms to farmers could lead to the integration of environmental knowledge into farmers' decision making (Luescher et al, 2014). By becoming more aware of the functioning of the ecological sub-systems in which they operate, farmers can develop the capacity to manage their ecosystem services supply and motivate the participation in conservation programmes (Page and Bellotti, 2015).…”

Strikingly high effect of geographic location on fauna and flora of European agricultural grasslands

“…They generally found an effect of agricultural management and surrounding landscape on communities. Often, these effects varied, depending on the taxonomic group under study (Lüscher et al 2014a). In order to enact general directives at the European scale, studies on community structures and related ecological functions require investigations of various taxonomic groups at large spatial extent (Tscharntke et al 2012;Schneider et al 2014).…”