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Results for “Journal of Animal Science”

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USGS2022

Integrating distance sampling survey data with population indices to separate trends in abundance and temporary immigration

Managers rely on accurate estimators of wildlife abundance and trends for management decisions. Despite the focus of contemporary wildlife science on developing methods to improve inference from wildlife surveys, legacy datasets often rely on index counts that lack information about the detection process. Data integration can be a useful tool for combining index counts with data collected under more rigorous designs (i.e., designs that account for the detection process), but care is required when datasets represent different population processes or are mismatched in space and time. This can be particularly problematic in cases where animals aggregate in response to a spatially or temporally limited resource because individuals may temporarily immigrate from outside the study area and be included in the abundance index. Abundance indices based on brown bear ( Ursus arctos ) feeding aggregations within coastal meadows in early summer in Lake Clark National Park and Preserve, Alaska, USA, are one such example. These indices reflect the target population (brown bears residing within the park) and temporary immigrants (i.e., bears drawn from outside the park boundary). To properly account for the effects of temporary immigration, we integrated the index data with abundance data collected via park-wide distance sampling surveys, the latter of which properly addressed the detection process. By assuming that the distance data provide inference on abundance and the index counts represent some combination of abundance and temporary immigration processes, we were able to decompose the relative contribution of each to overall trend. We estimated that the density of brown bears within our study area was 38–54 adults/1,000 km 2 during 2003–2019 and that abundance increased at a rate of approximately 1.4%/year. The contribution of temporary immigrants to overall trend in the index was low, so we created 3 hypothetical scenarios to more fully demonstrate how the integrated approach could be useful in situations where the composite trend in meadow counts may obscure trends in abundance (e.g., opposing trends in abundance and temporary immigration). Our work represents a conceptual advance supporting the integration of legacy index data with more rigorous data streams and is broadly applicable in cases where trends in index values may represent a mixture of population processes.

Alaska↗

USGS2024

The potential for species distribution models to distinguish source populations from sinks

1. While species distribution models (SDM) are frequently used to predict species occurrences to help inform conservation management, there is limited evidence evaluating whether habitat suitability can reliably predict intrinsic growth rates or distinguish source from sink populations. Filling this knowledge gap is critical for conservation science, as applications of SDMs for management purposes ultimately depend on these typically unobserved population or metapopulation dynamics. 2. Using regression, we associate previously published population level estimates of intrinsic growth and abundance derived from a Bayesian analysis of mark-recapture data for 17 bird species found in the contiguous United States with SDM habitat suitability estimates fitted here to opportunistic data for these same species. We then use AUC to measure how well SDMs can distinguish populations categorized as sources and sinks, depending on their intrinsic growth rates estimated from the mark-recapture data. We built SDMs using two different approaches, boosted regression trees (BRT) and Generalized Linear Models (GLM), and compared their predictive performance. Each SDM was built with presence points obtained from eBird and 10 environmental variables previously selected to model intrinsic growth rates and abundance for these species. 3. We show that SDMs built with opportunistic data are poor predictors of species demography in general; both BRT and GLM explained very little spatial variation of intrinsic growth rate and population abundance (median R2 across 17 species was close to 0.1 for both SDM methods). SDMs do, however, estimate higher suitability for source populations as compared to sinks. Out of 13 species which had both source and sink populations, both BRT and GLM had AUC values greater than 0.7 for 7 species when discriminating between sources and sinks. 4. Habitat suitability have the potential to be a useful measure to indicate a population’s ability to sustain itself as a source population, however more research on a diverse set of taxa is essential to fully explore this potential. This interpretation of habitat suitability can be particularly useful for conservation practice, and identification of explicit cases of when and how SDMs fail to match population demography can be informative for advancing ecological theory.

Journal of Animal Ecology↗

USGS2010

Effect of diet on fecal and urinary estrogenic activity

The United States Environmental Protection Agency has identified estrogens from animal feeding operations as a major environmental concern, but few data are available to quantify the excretion of estrogenic compounds by dairy cattle. The objectives of this study were to quantify variation in estrogenic activity in feces and urine due to increased dietary inclusion of phytoestrogens. Ten Holstein heifers were assigned to 2 groups balanced for age and days pregnant; groups were randomly assigned to treatment sequence in a 2-period crossover design. Dietary treatments consisted of grass hay or red clover hay, and necessary supplements. Total collection allowed for sampling of feed refusals, feces, and urine during the last 4 d of each period. Feces and urine samples were pooled by heifer and period, and base extracts were analyzed for estrogenic activity (estrogen equivalents) using the yeast estrogen screen bioassay. Feces and urine samples collected from 5 heifers were extracted and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify excretion of 7 phytoestrogenic compounds. Excretion of 17-β estradiolequivalents in urine was higher and tended to be higher in feces for heifers fed red clover hay (84.4 and 120.2 mg/d for feces and urine, respectively) compared with those fed grasshay (57.4 and 35.6 mg/d). Analysis by LC-MS/MS indicated greater fecal excretion of equol, genistein, daidzein, coumestrol, and formononetin by heifers fed red clover hay (1634, 29.9, 96.3, 27.8, and 163 mg/d, respectively) than heifers fed grass hay (340, 3.0, 46.2, 8.8, and 18.3 mg/d, respectively). Diet had no effect on fecal biochanin A or 2-carbethoxy-5, 7-dihydroxy-4’-methoxyisoflavone. Four phytoestrogens were detected in urine (2-carbethoxy-5, 7-dihydroxy-4’-methoxyisoflavone, daidzein, equol, and formononetin) and their excretion was not affected by diet. Identifying sources of variation in estrogenic activity of manure will aid in the development of practices to reduce environmental estrogen accumulation.

Journal of Dairy Science↗