Persistence and habitat associations of Purple Martin roosts quantified via weather surveillance radar

Bridge, Eli S.; Pletschet, Sandra M.; Fagin, Todd; Chilson, Phillip B.; Horton, Kyle G.; Broadfoot, Kyle R.; Kelly, Jeffrey F.

doi:10.1007/s10980-015-0279-0

Cited by 33 publications

(51 citation statements)

References 19 publications

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“…We believe the most promising near‐term applications will be recognition of specific patterns in radar data such as bat and bird roosts or mayfly hatches, where humans can judge with reasonable certainty the identity of the scatterers and therefore assemble evaluation and training sets using available radar and geospatial data. For example, Chilson et al () recently trained a deep learning model using large human‐labelled datasets to find radar scans containing swallow roosts (Bridge et al, ; Kelly & Pletschet, ; Laughlin et al, ). Detailed analyses of other specific patterns in radar data (Van Den Broeke, ) and cross‐calibration with other sensors (Liechti et al, ; Nilsson, Dokter, Schmid, et al, ) may reveal over time the ability to distinguish other biological phenomena.…”

Section: Discussionmentioning

confidence: 99%

MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

et al. 2019

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Large networks of weather radars are comprehensive instruments for studying bird migration. For example, the US WSR‐88D network covers the entire continental US and has archived data since the 1990s. The data can quantify both broad and fine‐scale bird movements to address a range of migration ecology questions. However, the problem of automatically discriminating precipitation from biology has significantly limited the ability to conduct biological analyses with historical radar data. We develop MistNet, a deep convolutional neural network to discriminate precipitation from biology in radar scans. Unlike prior machine learning approaches, MistNet makes fine‐scaled predictions and can collect biological information from radar scans that also contain precipitation. MistNet is based on neural networks for images, and includes several architecture components tailored to the unique characteristics of radar data. To avoid a massive human labelling effort, we train MistNet using abundant noisy labels obtained from dual polarization radar data. In historical and contemporary WSR‐88D data, MistNet identifies at least 95.9% of all biomass with a false discovery rate of 1.3%. Dual polarization training data and our radar‐specific architecture components are effective. By retaining biomass that co‐occurs with precipitation in a single radar scan, MistNet retains 15% more biomass than traditional whole‐scan approaches to screening. MistNet is fully automated and can be applied to datasets of millions of radar scans to produce fine‐grained predictions that enable a range of applications, from continent‐scale mapping to local analysis of airspace usage. Radar ornithology is advancing rapidly and leading to significant discoveries about continent‐scale patterns of bird movements. General‐purpose and empirically validated methods to quantify biological signals in radar data are essential to the future development of this field. MistNet can enable large‐scale, long‐term, and reproducible measurements of whole migration systems.

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Section: Discussionmentioning

confidence: 99%

MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

et al. 2019

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“…To address data related challenges in macrosystem studies, (Bridge et al 2015) Soranno and Schimel (2014), and 6 this special issue approach using weather surveillance radar (WSR) to monitor (and to quantify) roosts of a wildlife species, the purple martin, at a regional scale. They also described specific features encountered at visited roost sites where exact coordinates were verified.…”

Section: Novel Tools and Methodsmentioning

confidence: 99%

Macrosystems ecology: novel methods and new understanding of multi-scale patterns and processes

2015

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As the global biomes are increasingly threatened by human activities, understanding of macroscale patterns and processes is pressingly needed for effective management and policy making. Macrosystems ecology, which studies multiscale ecological patterns and processes, has gained growing interest in the research community. However, as a relatively new field in ecology, research in macrosystems ecology is facing various challenges. In this special issue, we highlight the following two latest exciting developments in this thriving field: (1) novel tools and methods and (2) new understandings on macroscale patterns and processes. While we believe that the contributions featured in this issue provide promising advancements in macrosystems ecology, we also see multiple challenges for future research including (1) multidisciplinary approaches for longterm and multiscale studies and (2) scaling local patterns and processes to broader scales.Keywords Macrosystems ecology Á Macroecology Á Macroscale Á Scaling Á Heterogeneity Macrosystems ecology, the study of ecological patterns and processes across multiple spatial and temporal scales, is a topic of growing interest. Macrosystems ecology has strong connections with landscape ecology, which also has deep emphases on spatial and temporal patterns, heterogeneity, and scale multiplicity (Forman 1995;Turner 2005;Wu 2013). Since the publication of the foundational paper by Brown and Maurer (1989), which coined the term of ''macroecology'', the field has experienced a rapid growth (Fig. 1). Macroecology is principally concerned with finding patterns in large-scale abundances and distributions and theorizing the reasons why these patterns exist (Brown 1995). It seeks generalized patterns at large spatial and temporal scales and statistical relationships that explain the distribution of biodiversity from a historical and geographical perspective

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“…4), wintering sites for waterfowl (Buler et al 2012), and key roost sites for birds (e.g. purple martins Progne subis; Russell and Gauthreaux 1998, Bridge et al 2016 and bats (Horn andKunz 2008, Stepanian andWainwright 2018). Given the high risk to many key stopover sites for threatened migratory species globally (for example tidal mudflats along the Yellow Sea; Studds et al 2017), radar will play an increasingly important role in assessing the value of these areas for the species they support.…”

Section: Identification and Management Of Conservation Areasmentioning

confidence: 99%

“…By means of an airport surveillance radar, Jänicke and Stork (1979) Fireworks and other methods such as water cannons are also used, sometimes illegally, to disperse roosts or breeding colonies of bird species that establish in locations where they can become a nuisance, and (near) real-time radar monitoring may provide an alert of such activities. When persistent roosting sites are known for birds (Bridge et al 2016) or bats (Horn andKunz 2008, Stepanian andWainwright 2018), flights from these sites can be monitored by radar to establish baselines of population size, distribution and persistence. Subsequent measurements that deviate from these patterns, such as a sudden change in roost location or size, can be indicative of adverse disturbances or varying environmental conditions, although day-to-day roost locations for some species can be quite variable.…”

Section: Effects Of Disturbance Artificial Light and Anthropogenic Omentioning

confidence: 99%

Perspectives and challenges for the use of radar in biological conservation

et al. 2019

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Radar is at the forefront for the study of broad‐scale aerial movements of birds, bats and insects and related issues in biological conservation. Radar techniques are especially useful for investigating species which fly at high altitudes, in darkness, or which are too small for applying electronic tags. Here, we present an overview of radar applications in biological conservation and highlight its future possibilities. Depending on the type of radar, information can be gathered on local‐ to continental‐scale movements of airborne organisms and their behaviour. Such data can quantify flyway usage, biomass and nutrient transport (bioflow), population sizes, dynamics and distributions, times and dimensions of movements, areas and times of mass emergence and swarming, habitat use and activity ranges. Radar also captures behavioural responses to anthropogenic disturbances, artificial light and man‐made structures. Weather surveillance and other long‐range radar networks allow spatially broad overviews of important stopover areas, songbird mass roosts and emergences from bat caves. Mobile radars, including repurposed marine radars and commercially dedicated ‘bird radars’, offer the ability to track and monitor the local movements of individuals or groups of flying animals. Harmonic radar techniques have been used for tracking short‐range movements of insects and other small animals of conservation interest. However, a major challenge in aeroecology is determining the taxonomic identity of the targets, which often requires ancillary data obtained from other methods. Radar data have become a global source of information on ecosystem structure, composition, services and function and will play an increasing role in the monitoring and conservation of flying animals and threatened habitats worldwide.

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Persistence and habitat associations of Purple Martin roosts quantified via weather surveillance radar

Cited by 33 publications

References 19 publications

MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

Macrosystems ecology: novel methods and new understanding of multi-scale patterns and processes

Perspectives and challenges for the use of radar in biological conservation

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