The power to detect regional declines in common bird populations using continental monitoring data

Sampling re-design increases power to detect change in the Great Barrier Reef's inshore water quality

Monitoring programs are fundamental to understanding the state and trend of aquatic ecosystems. Sampling designs are a crucial component of monitoring programs and ensure that measurements evaluate progress toward clearly stated management objectives, which provides a mechanism for adaptive management. Here, we use a well-established marine monitoring program for inshore water quality in the Great Barrier Reef (GBR), Australia to investigate whether a sampling re-design has increased the program's capacity to meet its primary objectives. Specifically, we use bootstrap resampling to assess the change in statistical power to detect temporal water quality trends in a 15-year inshore marine water quality data set that includes data from both before and after the sampling re-design. We perform a comprehensive power analysis for six water quality analytes at four separate study areas in the GBR Marine Park and find that the sampling re-design (i) increased power to detect trends in 23 of the 24 analyte-study area combinations, and (ii) resulted in an average increase in power of 34% to detect increasing or decreasing trends in water quality analytes. This increase in power is attributed more to the addition of sampling locations than increasing the sampling rate. Therefore, the sampling re-design has substantially increased the capacity of the program to detect temporal trends in inshore marine water quality. Further improvements in sampling design need to focus on the program's capability to reliably detect trends within realistic timeframes where inshore improvements to water quality can be expected to occur.

Modeling avian full annual cycle distribution and population trends with citizen science data

Information on species' distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale processes that affect populations vary throughout the year and across species' ranges, requiring high-resolution, year-round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intra-annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non-breeding seasons. The range-wide population trajectories for Wood Thrush show a close correspondence between breeding and non-breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range-wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non-breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra- and interannual distributional dynamics for broadly distributed, highly mobile species.