Geology topics

A.B. Franklin

Publications and source records attributed to A.B. Franklin.

4 recordsLinked to original sources

USGS2006

Comment on 'Are survival rates for northern spotted owls biased?'

Loehle et al. recently estimated survival rates from radio-telemetered northern spotted owls (Strix occidentalis caurina (Merriam, 1898)) and suggested that survival rates estimated for this species from capture-recapture studies were negatively biased, which subsequently resulted in the negatively biased estimates of rates of population change (lambda) reported by Anthony et al. (Wildl. Monogr. No. 163, pp. 1-47 (2006)). We argue that their survival estimates were inappropriate for comparison with capture-recapture estimates because (i) the manner in which they censored radio-telemetered individuals had the potential to positively bias their survival estimates, (ii) their estimates of survival were not valid for evaluating bias, and (iii) the size and distribution of their radiotelemetry study areas were sufficiently different from capture-recapture study areas to preclude comparisons. In addition, their inferences of negative bias in rates of population change estimated by Anthony et al. were incorrect and reflected a misunderstanding about those estimators.

Canadian Journal of Zoology↗

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↗

USGS2003

Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size ( NÌ‚ ) and effective sampling area ( AÌ‚ ) are used to calculate density ( DÌ‚ = NÌ‚ / AÌ‚ ); and models applicable to sampling regimes using distance-sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets ( n = 11) were developed using nine rodent species from capture–recapture live-trapping on both trapping grids and trapping webs in four replicate 4.2-ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates ( DÌ‚ ) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities ( D ) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models M b and M bh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research studies involving small-mammal abundances.

Ecological Monographs↗

USGS2003

Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly

Few species are likely to be so evident that they will always be detected when present. Failing to allow for the possibility that a target species was present, but undetected, at a site will lead to biased estimates of site occupancy, colonization, and local extinction probabilities. These population vital rates are often of interest in long-term monitoring programs and metapopulation studies. We present a model that enables direct estimation of these parameters when the probability of detecting the species is less than 1. The model does not require any assumptions of process stationarity, as do some previous methods, but does require detection/nondetection data to be collected in a manner similar to Pollock's robust design as used in mark?recapture studies. Via simulation, we show that the model provides good estimates of parameters for most scenarios considered. We illustrate the method with data from monitoring programs of Northern Spotted Owls (Strix occidentalis caurina) in northern California and tiger salamanders (Ambystoma tigrinum) in Minnesota, USA.

Ecology↗