Two-species occupancy models that account for false absences provide a robust method for testing for evidence of competitive exclusion, but previous model parameterizations were inadequate for incorporating covariates. We present a new parameterization that is stable when covariates are included: the conditional two-species occupancy model, which can be used to examine alternative hypotheses for species' distribution patterns. This new model estimates the probability of occupancy for a subordinate species conditional upon the presence of a dominant species. It can also be used to test if the detection of either species differs when one or both species are present, and if detection of the subordinate species depends on the detection of the dominant species when both are present. We apply the model to test if the presence of the larger Virginia Rail (Rallus limicola) affects probabilities of detection or occupancy of the smaller California Black Rail (Laterallus jamaicensis coturniculus) in small freshwater marshes that range in size from 0.013 to 13.99 ha. We hypothesized that Black Rail occupancy should be lower in small marshes when Virginia Rails are present than when they are absent, because resources are presumably more limited and interference competition should increase. We found that Black Rail detection probability was unaffected by the detection of Virginia Rails, while, surprisingly, Black and Virginia Rail occupancy were positively associated even in small marshes. The average probability of Black Rail occupancy was higher when Virginia Rails were present (0.74 +/- 0.053, mean +/- SE) than when they were absent (0.36 +/- 0.069), and for both species occupancy increased with marsh size. Our results contrast with recent findings from patchy forest systems, where small birds were presumed to be excluded from small habitat patches by larger competitors.
California Black Rails (Laterallus jamaicensis coturniculus) have a disjunct and poorly understood distribution. After a new population was discovered in Yuba County in 1994, we conducted call playback surveys from 1994 to 2006 in the Sierra foothills and Sacramento Valley region to determine the distribution and residency of Black Rails, estimate densities, and obtain estimates of site occupancy and detection probability. We found Black Rails in 164 small, widely scattered marshes distributed along the lower western slopes of the Sierra Nevada foothills from just northeast of Chico (Butte County) to Rocklin (Placer County). Marshes were surrounded by unsuitable habitat, creating a patchy or metapopulation structure. We observed Black Rails nesting and found that they are year‐round residents. Assuming perfect detectability, we estimated a mean density of 1.78 rails/ha. Assuming a detection probability of 0.5, this estimate increases to a mean density of 3.55 rails/ha. The probability of detecting occupancy with a single call playback survey at a marsh was high (= 0.84), and the estimated proportion of marshes occupied (across all years) was 0.58. Irrigation ditches were the primary water source for 75% of the marshes with Black Rails. Our results indicate that Black Rails are more widespread in the Sierra foothills than previously known, and the foothills distribution appears to be discontinuous with populations in the San Francisco Bay‐Delta Estuary. Occupancy surveys may be an improved method for monitoring population trends of this secretive marsh bird where habitat patches are highly fragmented.
Utilizing unmanned aircraft systems (UAS) can be an efficient and repeatable means of surveying wildlife, especially waterbirds. As with any technology in its infancy, case studies offer opportunities to explore drawbacks and limitations, both anticipated and unanticipated. We examined the relationship between flight altitude and camera focal length on bird identification. We then conducted a post-hoc analysis to examine the effect of flight altitude on bird flushing behavior. We flew UAS missions at three locations in California and Nevada to assess the use of UAS for censusing non-nesting waterbirds. A minimum pixel resolution of approximately 5 mm was needed be able to identify most waterbird species from imagery. Sensors needed to be carefully calibrated in order to obtain images of sufficient quality to identify waterbirds over open water. Our results suggest that gas-powered UAS may result in increased rates of flushing at low flight altitudes for some waterbirds. With careful design of surveys and processing workflow, UAS show promise for censusing and monitoring waterbirds. Environmental Practice 17: 201-210 (2015)
Species distribution models (SDMs) are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial “Pleistocene rewilding” proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion) was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of organisms in response to climate change.
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