Geology topics

David R. Luukkonen

Publications and source records attributed to David R. Luukkonen.

3 recordsLinked to original sources

USGS2019

A comparative analysis of common methods to identify waterbird hotspots

1. Hotspot analysis is a commonly used method in ecology and conservation to identify areas of high biodiversity or conservation concern. However, delineating and mapping hotspots is subjective and various approaches can lead to different conclusions with regard to the classification of particular areas as hotspots, complicating long-term conservation planning and implementation efforts. 2. We present a comparative analysis of recent approaches for identifying waterbird hotspots, with the goal of developing insights about the appropriate use of these methods. We selected four commonly used measures to identify persistent areas of high use: kernel density estimation, Getis-Ord Gi*, hotspot persistence, and hotspots conditional on presence, which represent the range of quantitative hotspot estimation approaches used in waterbird analyses. We applied each of the methods to aerial survey waterbird count data collected in the Great Lakes from 2012-2014 using a 5 km2 grid. For each approach, we identified areas of high use for seven species/species groups and then compared the results across all methods. 3. Our results indicate that formal hotspot analysis frameworks do not always lead to the same conclusions. The kernel density and Getis-Ord Gi* methods yielded the most similar results across all species analyzed. We found that these two models can differ substantially from the hotspot persistence and hotspots conditional on presence estimation approaches, which were not consistently similar to one another. The hotspot persistence approach differed most significantly from the other methods but is the only method to explicitly account for temporal variation. 4. We recommend considering the ecological question and scale of any conservation or management activities prior to designing survey methodologies. Deciding the appropriate definition and scale for analysis is critical for interpretation of hotspot analysis results. Combining methods using an integrative approach, either within a single analysis or post-hoc, could lead to greater consistency in the identification of waterbird hotspots.

Lake Erie, Lake Huron, Lake Michigan↗

USGS2015

A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus ) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

Natural Resource Modeling↗

USGS2003

Survival and recovery rates of American woodcock banded in Michigan

American woodcock (Scolopax minor) population indices have declined since U.S. Fish and Wildlife Service (USFWS) monitoring began in 1968. Management to stop and/or reverse this population trend has been hampered by the lack of recent information on woodcock population parameters. Without recent information on survival rate trends, managers have had to assume that the recent declines in recruitment indices are the only parameter driving woodcock declines. Using program MARK, we estimated annual survival and recovery rates of adult and juvenile American woodcock, and estimated summer survival of local (young incapable of sustained flight) woodcock banded in Michigan between 1978 and 1998. We constructed a set of candidate models from a global model with age (local, juvenile, adult) and time (year)-dependent survival and recovery rates to no age or time-dependent survival and recovery rates. Five models were supported by the data, with all models suggesting that survival rates differed among age classes, and 4 models had survival rates that were constant over time. The fifth model suggested that juvenile and adult survival rates were linear on a logit scale over time. Survival rates averaged over likelihood-weighted model results were 0.8784 +/- 0.1048 (SE) for locals, 0.2646 +/- 0.0423 (SE) for juveniles, and 0.4898 +/- 0.0329 (SE) for adults. Weighted average recovery rates were 0.0326 +/- 0.0053 (SE) for juveniles and 0.0313 +/- 0.0047 (SE) for adults. Estimated differences between our survival estimates and those from prior years were small, and our confidence around those differences was variable and uncertain. juvenile survival rates were low.

Journal of Wildlife Management↗