Essential biodiversity variables for mapping and monitoring species populations

Jetz, Walter; McGeoch, Mélodie A.; Guralnick, Robert; Ferrier, Simon; Beck, Jan; Costello, Mark J.; Fernández, Miguel; Geller, Gary N.; Keil, Petr; Merow, Cory; Meyer, Carsten; Muller‐Karger, Frank E.; Pereira, Henrique M.; Regan, Eugenie; Schmeller, Dirk S.; Turak, Eren

doi:10.1038/s41559-019-0826-1

Cited by 332 publications

(346 citation statements)

References 124 publications

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“…, Jetz et al. ). However, we are not suggesting that citizen science data can or should supplant data collected using more formal sampling protocols.…”

Section: Discussionmentioning

confidence: 99%

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

Fink

Auer

Johnston

et al. 2020

Ecological Applications

132

176

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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.

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“…, Jetz et al. ). However, we are not suggesting that citizen science data can or should supplant data collected using more formal sampling protocols.…”

Section: Discussionmentioning

confidence: 99%

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

Fink

Auer

Johnston

et al. 2020

Ecological Applications

132

176

View full text Add to dashboard Cite

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“…) and is integral to biodiversity monitoring across the globe (Jetz et al. ). The components of the simulation are described in the subsections ‘Simulating virtual species and trends' and ‘Simulating monitoring' (see Data for code examples).…”

Section: Methodsmentioning

confidence: 99%

“…, Jetz et al. ). The development of analytical approaches to minimize the effects of such biases when estimating population trends has been the focus of considerable research (Kéry et al.…”

Section: Introductionmentioning

confidence: 99%

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

Baker

Clarke

McGeoch

2019

Ecological Applications

Self Cite

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Anthropogenic environmental change is driving the rapid loss of biodiversity. Large declines in the abundance of historically common species are now emerging as a major concern. Identifying declining populations through long‐term biodiversity monitoring is vital for implementing timely conservation measures. It is, therefore, critical to evaluate the likelihood that persistent long‐term population trends of a given size could be detected using existing monitoring data and methods. Here, we test the power to detect declines in Australia's common landbirds using long‐term citizen science monitoring. We use spatially explicit simulations of occupancy dynamics and virtual sampling, designed to mimic bird monitoring in better‐sampled regions of Australia, to assess likely power in these data to detect trends relevant for conservation. We predict the statistical power for 326 common species that meet minimum requirements for monitoring data across 10 regions of Australia, estimating the number of species for which we would have a high (≥80%) chance of detecting declines of different sizes. The power to detect declines of ≥30% per decade was predicted to be high for at least one‐third of the common species in 7 of 10 regions, with a total of 103 (32% of 326) unique species sufficiently monitored in at least one region. These species spanned 12 taxonomic orders, four orders of magnitude in body mass, and a broad diversity of dietary guilds, suggesting the current species pool will likely serve as robust indicators for a broad range of environmental states and pressures. Power was strongly affected by species' detectability, and power to detect even large declines was negligible when species are detected on ≤50% of visits to an occupied site. Predicted power for many species fell just short of the 80% threshold in one or more regions, which suggests an increase in effort targeting these species could greatly enhance the species and regional representation of these data. Against the backdrop of unprecedented biodiversity losses, this study shows how critical evaluation of existing monitoring schemes is valuable both for assessing the contribution of citizen science schemes to biodiversity monitoring and for designing strategic monitoring to significantly improve the knowledge these schemes provide.

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“…; Jetz et al. ). Moreover, habitat suitability maps often are the basis for downstream‐analyses, such as modeling population dynamics or assessing landscape fragmentation and connectivity (Larson et al.…”

Section: Introductionmentioning

confidence: 98%

Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

Oeser

Heurich

Senf

et al. 2019

Remote Sens Ecol Conserv

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Up‐to‐date and fine‐scale habitat information is essential for managing and conserving wildlife. Studies assessing wildlife habitat commonly rely on categorical land‐cover maps as predictors in habitat models. However, broad land‐cover categories often do not adequately capture key habitat features and generating robust land‐cover maps is challenging and laborious. Continuous variables derived directly from satellite imagery provide an alternative for capturing land‐cover characteristics in habitat models. Improved data availability and processing capacities now allow integrating all available images from medium‐resolution sensors in compositing approaches that derive spectral‐temporal metrics at the pixel level, summarizing spectral responses over time. In this study, we assessed the usefulness of such metrics derived from Landsat imagery for mapping wildlife habitat. We categorize spectral‐temporal metrics into habitat metrics characterizing different aspects of wildlife habitat. Comparing the performance of these metrics against categorical land‐cover maps in habitat models for lynx, red deer and roe deer, we found that models using habitat metrics consistently outperformed models based on categorical land‐cover maps, with average improvements of 13.7% in model AUC and 9.7% in the Continuous Boyce Index. Performance increases were larger for seasonal habitat models, indicating that the habitat metrics capture intra‐annual variability in habitat conditions better than land‐cover maps. Comparing suitability maps to ancillary data further revealed that our habitat metrics were sensitive to fine‐scale heterogeneity in habitat associated with forest structure. Overall, our study highlights the considerable potential of Landsat‐based spectral temporal metrics for assessing wildlife habitat. Given these metrics can be derived directly and in an automatized fashion from globally and freely available Landsat imagery, they open up new possibilities for monitoring habitat dynamics in space and time.

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Essential biodiversity variables for mapping and monitoring species populations

Cited by 332 publications

References 124 publications

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

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

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

Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

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