M.E. Seamans | USGS Science

USGS2011

Climate change, uncertainty, and natural resource management

Climate change and its associated uncertainties are of concern to natural resource managers. Although aspects of climate change may be novel (e.g., system change and nonstationarity), natural resource managers have long dealt with uncertainties and have developed corresponding approaches to decision-making. Adaptive resource management is an application of structured decision-making for recurrent decision problems with uncertainty, focusing on management objectives, and the reduction of uncertainty over time. We identified 4 types of uncertainty that characterize problems in natural resource management. We examined ways in which climate change is expected to exacerbate these uncertainties, as well as potential approaches to dealing with them. As a case study, we examined North American waterfowl harvest management and considered problems anticipated to result from climate change and potential solutions. Despite challenges expected to accompany the use of adaptive resource management to address problems associated with climate change, we conclude that adaptive resource management approaches will be the methods of choice for managers trying to deal with the uncertainties of climate change. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗

USGS2007

Occupancy estimation and modeling with multiple states and state uncertainty

The distribution of a species over space is of central interest in ecology, but species occurrence does not provide all of the information needed to characterize either the well-being of a population or the suitability of occupied habitat. Recent methodological development has focused on drawing inferences about species occurrence in the face of imperfect detection. Here we extend those methods by characterizing occupied locations by some additional state variable ( e. g., as producing young or not). Our modeling approach deals with both detection probabilities,1 and uncertainty in state classification. We then use the approach with occupancy and reproductive rate data from California Spotted Owls ( Strix occidentalis occidentalis ) collected in the central Sierra Nevada during the breeding season of 2004 to illustrate the utility of the modeling approach. Estimates of owl reproductive rate were larger than naive estimates, indicating the importance of appropriately accounting for uncertainty in detection and state classification.

Ecology↗

USGS2004

Population dynamics of the California Spotted Owl (Strix occidentalis occidentalis): a meta-analysis

We conducted a meta-analysis to provide a current assessment of the population characteristics of California Spotted Owls (Strix occidentalis occidentalis) resident on four study areas in the Sierra Nevada and one study area in southern California. Our meta-analysis followed rigorous a priori analysis protocols, which we derived through extensive discussion during a week-long analysis workshop. Because there is great interest in the owl?s population status, we used state-of-the-art analytical methods to obtain results as precise as possible. Our meta-analysis included data from five California study areas located on the Lassen National Forest (1990-2000), Eldorado National Forest (1986-2000), Sierra National Forest (1990-2000), Sequoia and Kings Canyon national parks (1990-2000), and San Bernardino National Forest (1987-1998). Four of the five study areas spanned the length of the Sierra Nevada, whereas the fifth study area encompassed the San Bernardino Mountains in southern California. Study areas ranged in size from 343 km2 (Sequoia and Kings Canyon) to 2,200 km (Lassen). All studies were designed to use capture-recapture methods and analysis. We used survival in a meta-analysis because field methods were very similar among studies. However, we did not use reproduction in a meta-analysis because it was not clear if variation among individual study-area protocols used to assess reproductive output of owls would confound results. Thus, we analyzed fecundity only by individual study area. We examined population trend using the reparameterized Jolly-Seber capture-recapture estimator (8t) We did not estimate juvenile survival rates because of estimation problems and potential bias because of juvenile emigration from study areas. We used mark-recapture estimators under an information theoretic framework to assess apparent survival rates of adult owls. The pooled estimate for adult apparent survival for the five study areas was 0.833, which was lower than pooled adult survival rates (0.850) from 15 Northern Spotted Owl (S. o. caurina) studies. Estimates of survival from the best model on the Lassen (N = 0.829, 95% confidence intervals [CI = 0.798 to 0.857), Eldorado (N = 0.815, 95% CI = 0.772 to 0.851), Sierra (N = 0.818, 95% CI = 0.781 to 0.850), and San Bernardino (N = 0.813, 95% CI = 0.782 to 0.841) were not different. However, the Sequoia and Kings Canyon population had a higher survival rate (N = 0.877, 95% CI = 0.842 to 0.905) than the other study areas. Management history and forest structure (e.g. presence of giant sequoia [Sequoiadendron giganteum]) on the Sequoia and Kings Canyon study area differed from all other study areas. There appears to be little or no evidence for temporal variation in adult apparent survival on any of the study areas. Although we did not directly compare fecundity estimates were highly variable among years within all study areas (CV of temporal process variation = 0.672-0.817). Estimates for fecundity among the study populations were Lassen (b = 0.336, SE = 0.083), Eldorado (b = 0.409, SE = 0.087), Sierra (b = 0.284, SE = 0.073), Sequoia and Kings Canyon (b = 0.289, SE = 0.074), and San Bernardino (b = 0.362, SE = 0.038). During most years, the Sierra Nevada populations showed either moderate or poor fecundity. However, 1992 appeared to be an exceptional reproductive year for owls in the Sierra Nevada. In contrast, the San Bernardino population had less variable reproduction (CV of temporal process variation = 0.217), but experienced neither the exceptional reproduction of 1992 nor the extremely poor years that characterized all of the Sierra Nevada study areas. Because fecundity may be influenced by weather patterns, it was possible that the different weather patterns between southern California and the Sierra Nevada accounted for that difference. Except for Eldorado, all estimates for 8t, were <1.0, but none was different from 8 = 1.0 given the 95% confidence i

Ornithological Monographs↗