Conservation planning aims to protect biodiversity by sustainng the natural physical, chemical, and biological processes within representative ecosystems. Often data to measure these components are inadequate or unavailable. The impact of human activities on ecosystem processes complicates integrity assessments and might alter ecosystem organization at multiple spatial scales. Freshwater conservation targets, such as populations and communities, are influenced by both intrinsic aquatic properties and the surrounding landscape, and locally collected data might not accurately reflect potential impacts. We suggest that changes in five major biotic drivers-energy sources, physical habitat, flow regime, water quality, and biotic interactions-might be used as surrogates to inform conservation planners of the ecological integrity of freshwater ecosystems. Threats to freshwater systems might be evaluated based on their impact to these drivers to provide an overview of potential risk to conservation targets. We developed a risk-based protocol, the Ecological Risk Index (ERI), to identify watersheds with least/most risk to conservation targets. Our protocol combines risk-based components, specifically the frequency and severity of human-induced stressors, with biotic drivers and mappable land- and water-use data to provide a summary of relative risk to watersheds. We illustrate application of our protocol with a case study of the upper Tennessee River basin, USA. Differences in risk patterns among the major drainages in the basin reflect dominant land uses, such as mining and agriculture. A principal components analysis showed that localized, moderately severe threats accounted for most of the threat composition differences among our watersheds. We also found that the relative importance of threats is sensitive to the spatial grain of the analysis. Our case study demonstrates that the ERI is useful for evaluating the frequency and severity of ecosystem-wide risk, which can inform local and regional conservation planning.
A steady increase in archery hunting participation and frequent changes in hunter regulations led to an evaluation of harvest data used in a common white‐tailed deer (Odocoileus virginianus) population model. Our goal was to determine if model parameters and population estimates traditionally estimated solely by firearm harvest data were biased with respect to altered sex and age ratios brought about by increases in archery hunting and harvest success. The sex‐age‐kill (SAK) model, commonly used by state agencies, was developed in the mid‐1900s when deer numbers were low and firearm harvest was predominant. Management actions were concentrated on increasing deer numbers, and model assumptions relied heavily on a stable age distribution and a minimal antlerless deer harvest. We evaluated the reliance of SAK in a modern hunting scenario using a 10‐year dataset obtained from Michigan, USA, that encompassed a variety of climatic regions, hunting seasons, and regulation scenarios. We found that firearm and archery harvest sex and age ratios differed among 5 geographic groups and study years for males, females, and fawns (P<0.001, P = 0.001, and P = 0.037, respectively). Also, the addition of archery harvest data increased population estimates but did not alter overall trends. We recommend that managers reassess harvest‐based population estimates in 2 situations: 1) if regulation changes affect antlerless deer harvest, and 2) when trends in hunter success rates cause fluctuations in harvest data.
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