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Roy Renkin

Publications and source records attributed to Roy Renkin.

2 recordsLinked to original sources

Patterns of primary production and ecological drought in Yellowstone

Introduction: Photosynthesis converts sunlight into stored energy in millions of leaves, flowers and seeds that maintain the web of life in Yellowstone. This transformation of energy fixes carbon, supplies organic matter to soils, and can become fuel for wildfire. As the first link of the food chain, new plant biomass is called primary production and provides energy to consumers, including wildlife. While Yellowstone is a mountain environment with deep winter snowpack, the park can get very dry in some years as evidenced by massive wildfires in 1988 and 2016. Droughts like these not only contribute to fire potential, but they affect primary production, the food chain and likely will play an increasingly important role in transforming vegetation structure and composition in the future. Meteorological, agricultural, and hydrological drought have been assessed quantitatively for many years, but key indicators of drought in wildland ecosystems have not been formally defined until recently (Crausbay et al., 2017). One promising new method to do this is by measuring how vegetation responds to negative effects of drought, and positive effects of favorable conditions that offset negative effects of drought. The balance of drought stress and growth has important implications for future vegetation condition as the climate of Yellowstone changes. Monitoring primary production, and predicting future vegetation changes are needed to provide a comprehensive view of park health and anticipate future ecosystem changes (Crabtree et al. 2009, Nemani et al. 2009). Although an important indicator of ecosystem condition, primary production can be time and resource-intensive to monitor in wildland settings using traditional ground-based methods such as clipping and weighing. Fortunately, ground-based methods can be complemented and enhanced by monitoring primary production with satellite imagery. Measurements of solar radiation reflectance in visible and near infra-red wavelengths can indicate primary production at frequent weekly intervals from the Moderate Resolution Imaging Spectrometer (MODIS) on satellites operated by NASA. The Greater Yellowstone Inventory and Monitoring Network (GRYN) uses this information to track changes in primary production across Yellowstone over time. They link these measurements to vegetation types, soils, and climate to understand where and when changes in production have occurred and may occur in the future.

Yellowstone National Park↗

Coefficients of productivity for Yellowstone's grizzly bear habitat

This report describes methods for calculating coefficients used to depict habitat productivity for grizzly bears in the Yellowstone ecosystem. Calculations based on these coefficients are used in the Yellowstone Grizzly Bear Cumulative Effects Model to map the distribution of habitat productivity and account for the impacts of human facilities. The coefficients of habitat productivity incorporate detailed information that was collected over a 20-year period (1977-96) on the foraging behavior of Yellowstone's bears and include records of what bears were feeding on, when and where they fed, the extent of that feeding activity, and relative measures of the quantity consumed. The coefficients also incorporate information, collected primarily from 1986 to 1992, on the nutrient content of foods that were consumed, their digestibility, characteristic bite sizes, and the energy required to extract and handle each food. Coefficients were calculated for different time periods and different habitat types, specific to different parts of the Yellowstone ecosystem. Stratifications included four seasons of bear activity (spring, estrus, early hyperphagia, late hyperphagia), years when ungulate carrion and whitebark pine seed crops were abundant versus not, areas adjacent to (< 100 m) or far away from forest/nonforest edges, and areas inside or outside of ungulate winter ranges. Densities of bear activity in each region, habitat type, and time period were incorporated into calculations, controlling for the effects of proximity to human facilities. The coefficients described in this report and associated estimates of grizzly bear habitat productivity are unique among many efforts to model the conditions of bear habitat because calculations include information on energetics derived from the observed behavior of radio-marked bears.

Biological Science Report↗