Geology topics

Mark C. Otto

Publications and source records attributed to Mark C. Otto.

3 recordsLinked to original sources

USGS2022

The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts

Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.

California, Illinois, Iowa, Missouri↗

USGS2015

A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos

Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle ( Aquila chrysaetos ) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year -1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year -1 ) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80 th quantile, 6.3). In this case, the increased precision in the fatality prediction lowered the level of authorized take, and thus lowered the required amount of compensatory mitigation.

PLoS ONE↗

USGS2011

Monitoring bald eagles using lists of nests: Response to Watts and Duerr

The post-delisting monitoring plan for bald eagles ( Haliaeetus leucocephalus ) roposed use of a dual-frame sample design, in which sampling of known nest sites in combination with additional area-based sampling is used to estimate total number of nesting bald eagle pairs. Watts and Duerr (2010) used data from repeated observations of bald eagle nests in Virginia, USA to estimate a nest turnover rate and used this rate to simulate decline in number of occupied nests in list nests over time. Results of Watts and Duerr suggest that, given the rates of loss of nests from the list of known nest sites in Virginia, the list information will be of little value to sampling unless lists are constantly updated. Those authors criticize the plan for not placing sufficient emphasis on updating and maintaining lists of bald eagle nests. Watts and Duerr's metric of turnover rate does not distinguish detectability or temporary nonuse of nests from permanent loss of nests and likely overestimates turnover rate. We describe a multi-state capture–recapture model that allows appropriate estimation of rates of loss of nests, and we use the model to estimate rates of loss from a sample of nests from Maine, USA. The post-delisting monitoring plan addresses the need to maintain and update the lists of nests, and we show that dual frame sampling is an effective approach for sampling nesting bald eagle populations.

Virginia↗