Sheep in Species-Rich Temperate Grassland: Combining Behavioral Observations with Vegetation Characterization

Simple Summary Grasslands cover much of the world, and numerous people depend on the livestock that graze them for their livelihoods. These areas must be properly managed as they are often ecologically fragile. Therefore, how the foraging animal interacts with its environment needs to be understood. These interactions have mostly been studied in highly productive intensively managed and improved grasslands, which typically have only a limited number of commercially developed plant varieties. Little is known about how animals interact with less intensively managed, species-rich grasslands which are often of conservation significance because of their biodiversity. In this preliminary study, we have used video technology to investigate responses of sheep to the vegetation of unimproved grassland in Estonia. We classified the vegetation with a methodology that is standard in plant ecology but which has not been extensively applied in animal behavior. We also demonstrate the use of a novel procedure for quantifying foraging behavior. This combination of methodologies will enable the characterization of individual animal variations in these important behaviors, which could provide a basis for the rational design of sustainable grassland management systems. Foraging behavior of livestock in species-rich, less intensively managed grassland communities will require different methodologies from those appropriate in floristically simple environments. In this pilot study on sheep in species-rich grassland in northern Estonia, foraging behavior and the plant species of the immediate area grazed by the sheep were registered by continually-recording Go-Pro cameras. From three days of observation of five sheep (706 animal-minutes), foraging behavior was documented. Five hundred and thirty-six still images were sampled, and a plant species list was compiled for each. Each plant species was assigned a score indicating its location, in the ecophysiological sense, on the main environmental gradient. The scores of the plant species present were averaged for each image. Thus, the fine structure of foraging behavior could be studied in parallel with the vegetation of the precise area being grazed. As expected, there was considerable individual variation, and we characterized foraging behavior by quantifying the patterns of interspersion of grazing and non-grazing behaviors. This combination of behavior recording and vegetation classification could enable a numerical analysis of the responses of grazing livestock to vegetation conditions.