Feature Extraction Techniques for Measuring Piñon and Juniper Tree Cover and Density,and Comparison with Field-Based Management Surveys

Western North America is experiencing a dramatic expansion of piñon (Pinus spp.) and juniper (Juniperus spp.) (P-J) trees into shrub-steppe communities. Feature extracted data acquired from remotely sensed imagery can help managers rapidly and accurately assess this land cover change in order to manage rangeland ecosystems at a landscape-scale. The objectives of this study were to: (1) develop an effective and efficient method for accurately quantifying P-J tree canopy cover and density directly from high resolution photographs and (2) compare feature-extracted data to typical in-situ datasets used by land managers. Tree cover was extracted from aerial-photography using Feature Analyst^®. Tree density was calculated as the sum of the total number of individual polygons (trees) within the tree cover output file after isolation using a negative buffer post-processing technique. Feature-extracted data were compared to ground reference measurements from Utah’s Division of Wildlife Resources Range Trend Project (DWR-RTP). We found that the proposed feature-extraction techniques used for measuring cover and density were highly correlated to ground reference and DWR-RTP datasets. Feature-extracted measurements of cover generally showed a near 1:1 relationship to these data, while tree density was underestimated; however, after calibration for juvenile trees, a near 1:1 relationship was realized. Feature-extraction techniques used in this study provide an efficient method for assessing important rangeland indicators, including: density, cover, and extent of P-J tree encroachment. Correlations found between field and feature-extracted data provide evidence to support extrapolation between the two approaches when assessing woodland encroachment.     

Advancing the Integration of History and Ecology for Conservation

Abstract: The important role of humans in the development of current ecosystems was recognized decades ago; however, the integration of history and ecology in order to inform conservation has been difficult. We identified four issues that hinder historical ecological research and considered possible solutions. First, differences in concepts and methods between the fields of ecology and history are thought to be large. However, most differences stem from miscommunication between ecologists and historians and are less substantial than is usually assumed. Cooperation can be achieved by focusing on the features ecology and history have in common and through understanding and acceptance of differing points of view. Second, historical ecological research is often hampered by differences in spatial and temporal scales between ecology and history. We argue that historical ecological research can only be conducted at extents for which sources in both disciplines have comparable resolutions. Researchers must begin by clearly defining the relevant scales for the given purpose. Third, periods for which quantitative historical sources are not easily accessible (before AD 1800) have been neglected in historical ecological research. Because data from periods before 1800 are as relevant to the current state of ecosystems as more recent data, we suggest that historical ecologists actively seek out data from before 1800 and apply analytic methods commonly used in ecology to these data. Fourth, humans are not usually considered an intrinsic ecological factor in current ecological research. In our view, human societies should be acknowledged as integral parts of ecosystems and societal processes should be recognized as driving forces of ecosystem change.