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Boehning-Gaese, K.

Publications and source records attributed to Boehning-Gaese, K..

4 recordsLinked to original sources

Improved Estimation of Bird Abundance and Energy Consumption by Combining Point and Transect Observations

Point counts and transect surveys are both common methods for estimating bird abundance (by species, genus, or family) in a given environment. Sometimes both methods are used in the same study. Point counts reflect abundance directly, while transect observations of bird feeding instances reflect both the bird abundance and the mean energy consumption rate per bird. In this research we develop an improved estimator of bird abundance based on both sets of measurements, and derive error bars for these abundance estimates. The improved estimator is a linear combination of the two individual abundance estimates obtained from the two data types. The combination weights are obtained through a comparison of two separate energy estimates. The mathematical methods developed are applied to a dataset consisting of point counts and transect surveys of Ecuadorian frugivore bird species in six different types of environment (three elevations and two degrees of forestation). The improvement in accuracy achieved by this combined estimator is verified by simulations applied to bird family data. We also obtain 90% confidence intervals for the bird family relative abundance estimates, and verify the confidence intervals using simulations.

ecology↗

Clarifying space use concepts in ecology: range vs. occurrence distributions

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animals home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals. Open Research StatementTracking data on Aepyceros melampus, Beatragus hunteri, Bycanistes bucinator, Cerdocyon thous, Eulemur rufifrons, Glyptemys insculpta, Gyps coprotheres, Madoqua guentheri, Ovis canadensis, Propithecus verreauxi, Sus scrofa, and Ursus arctos are publicly archived in the Dryad repository (Noonan et al. 2018; https://doi.org/10.5061/dryad.v5051j2), as are data from Procapra gutturosa (Fleming et al. 2014a; https://doi.org/10.5061/dryad.45157). Data on Panthera onca were taken from (Morato et al. 2018). Additional data are publicly archived in the Movebank repository under the following identifiers: Canis latrans, 8159699; Canis lupus, 8159399; Chrysocyon brachyurus, 18156143; Felis silvestris, 40386102; Gyps africanus, 2919708; Lepus europaeus, 25727477; Martes pennanti, 2964494; Panthera leo, 220229; Papio cynocephalus, 222027; Syncerus caffer, 1764627; Tapirus terrestris, 443607536; Torgos tracheliotus, 2919708; and Ursus americanus, 8170674.

ecology↗

How to resolve conflicting conservation objectives: A decision support tool for the global selection of multi-purpose protected areas

The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.

ecology↗

The geography of the Anthropocene differs between the land and the sea

O_LIClimate change and other anthropogenic drivers of biodiversity change are unequally distributed across the world. The geographic patterns of different drivers, and the spatial overlap among these drivers, have important implications for the direction and pace of biodiversity change, yet are not well documented. Moreover, it is unknown if the geographic patterns of drivers differ between the terrestrial and marine realm, as expected due to marked differences in how humans interact with the land and ocean. C_LIO_LIWe compiled global gridded datasets on climate change, land-use, resource exploitation, pollution, species invasions, and human population density. We used multivariate statistics to examine the spatial relationships among the datasets and to characterize the typical combinations of drivers experienced by different parts of the world. C_LIO_LIWe found stronger positive correlations among drivers in the terrestrial than in the marine realm, leading to areas of high intensities of multiple drivers on land. Climate change tended to be negatively correlated with other drivers in the terrestrial realm (e.g., in the tundra and boreal forest with high climate change but low human use and pollution) whereas the opposite was true in the marine realm (e.g., in the Indo-Pacific with high climate change and high fishing). C_LIO_LIWe show that different regions of the world can be defined by anthropogenic threat complexes (ATCs), distinguished by different sets of drivers with varying intensities. The ATCs can be used to test hypothesis about the pattern of biodiversity change, especially the joint effects of multiple drivers. More generally, our global analysis highlights the broad conservation priorities needed to mitigate the effects of anthropogenic change on biodiversity responses, with different priorities emerging on land and in the ocean, and in different parts of the world. C_LI

ecology↗