Prioritizing Beneficial Management Practices for Species at Risk in Agricultural Lands.

Agricultural expansion and intensification are major drivers of ecosystem degradation and loss of biodiversity around the world. Countries are relying on protected areas to conserve habitats and prevent species decline, but these are either too few, too small, or too disconnected to capture and protect the needs of species at risk (SAR). Privately owned and managed lands and agricultural producers are increasingly needed to assist with habitat conservation and SAR recovery. Uptake of environmentally beneficial management practices (BMPs) by producers is often hindered by the lack of awareness of the needs of SAR and of the contribution they can make to their habitats, an actual or perceived negative economic and operational impact of the necessary management changes, the fear of losing management control over their land, and mistrust toward public agencies. We present an eight-step model framework that allows agricultural producers to privately determine the potential SAR occurring in a land parcel of interest and to identify and prioritize mutually compatible and outcome-oriented BMPs relevant to these species. In Alberta, Canada, the framework resulted in the development of a confidential self-served online extension tool tailored to a typical farm-level management unit, and to the geographical and ecological context of the operation. We provide a case study using a land parcel from the agricultural region of Alberta to illustrate the model and the associated tool. This novel approach can alleviate producers concerns, promote uptake of BMPs, and foster voluntary stewardship of SAR habitats on privately owned or managed lands.

Energy gains predict the distribution of plains bison across populations and ecosystems.

Developing tools that help predict animal distribution in the face of environmental change is central to understanding ecosystem function, but it remains a significant ecological challenge. We tested whether a single foraging currency could explain bison (Bison bison) distribution in dissimilar environments: a largely forested environment in Prince Albert National Park (Saskatchewan, Canada) and a prairie environment in Grasslands National Park (Saskatchewan, Canada). We blended extensive behavioral observations, relocations of radio-collared bison, vegetation surveys, and laboratory analyses to spatially link bison distribution in the two parks and expected gains for different nutritional currencies. In Prince Albert National Park, bison were more closely associated with the distribution of plants that maximized their instantaneous energy intake rate (IDE) than their daily intake of digestible energy. This result reflected both bison's intensity of use of individual meadows and their selection of foraging sites within meadows. On this basis, we tested whether IDE could explain the spatial dynamics of bison reintroduced to Grasslands National Park. As predicted, bison distribution in this park best matched spatial patterns of plants offering rapid IDE rather than rapid sodium intake, phosphorus intake, or daily intake of digestible energy. Because the two study areas have very different plant communities, a phenomenological model of resource selection developed in one area could not be used to predict animal distribution in the other. We were able, however, to successfully infer the distribution of bison from their foraging objective. This consistency in foraging currency across ecosystems and populations provides a strong basis for forecasting animal distributions in novel and dynamic environments.

Comparison of laboratory and field remote sensing methods to measure forage quality.

Recent research in range ecology has emphasized the importance of forage quality as a key indicator of rangeland condition. However, we lack tools to evaluate forage quality at scales appropriate for management. Using canopy reflectance data to measure forage quality has been conducted at both laboratory and field levels separately, but little work has been conducted to evaluate these methods simultaneously. The objective of this study is to find a reliable way of assessing grassland quality through measuring forage chemistry with reflectance. We studied a mixed grass ecosystem in Grasslands National Park of Canada and surrounding pastures, located in southern Saskatchewan. Spectral reflectance was collected at both in-situ field level and in the laboratory. Vegetation samples were collected at each site, sorted into the green grass portion, and then sent to a chemical company for measuring forage quality variables, including protein, lignin, ash, moisture at 135 °C, Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), Total Digestible, Digestible Energy, Net Energy for Lactation, Net Energy for Maintenance, and Net Energy for Gain. Reflectance data were processed with the first derivative transformation and continuum removal method. Correlation analysis was conducted on spectral and forage quality variables. A regression model was further built to investigate the possibility of using canopy spectral measurements to predict the grassland quality. Results indicated that field level prediction of protein of mixed grass species was possible (r² = 0.63). However, the relationship between canopy reflectance and the other forage quality variables was not strong.

Patch selection by red deer in relation to energy and protein intake: a re-evaluation of Langvatn and Hanley's (1993) results.

Langvatn and Hanley (1993) recently reported that patch use by red deer (Cervus elaphus) was more strongly correlated with short term rates of intake of digestible protein than dry matter. Such short term measures overlook effects of gut filling, which may constrain intake by ruminants over longer time scales (i.e., daily rates of gain). We reanalyzed Langvatn and Hanley's data using an energy intake model incorporating such a processing constraint, to determine whether their conclusions are robust. We found that the use of patches by red deer was just as strongly correlated with an estimate of the daily rate of intake of digestible energy as one of digestible protein during four out of seven trials, but slightly lower in three out of seven trials. In all cases, daily intake of digestible energy was a much better predictor of patch preference by red deer than was the intake of dry matter. Our reanalysis suggests that the daily intake of energy was highly correlated with that of protein in these trials, as may often be the case for herbivores feeding on graminoids. Hence the observed pattern of patch use by red deer could simultaneously enhance rates of both protein and energy intake.