Identifying which ecological and life history traits influence a species’ tolerance to urbanization is critical to understanding the trajectory of biodiversity in an increasingly urbanizing world. There is evidence for a wide array of contrasting patterns for single trait associations with urbanization. In a continental‐scale analysis, incorporating 477 species and >5 000 000 bird observations, we developed a novel and scalable methodology that evaluated the ecological and life history traits which most influence a species’ adaptability to persist in urban environments. Specifically, we assigned species‐specific scores based on continuous measures of response to urbanization, using VIIRS night‐time light values (i.e. radiance) as a proxy for urbanization. We identified generalized, phylogenetically controlled patterns: bird species which are generalists (i.e. large niche breadth), with large clutch size, and large residual brain size are among the most urban‐tolerant bird species. Conversely, specialized feeding strategies (i.e. insectivores and granivores) were negatively associated with urbanization. Enhancement and persistence of avian biodiversity in urban environments probably relies on protecting, maintaining and restoring diverse habitats serving a range of life history strategies.

Recent advances in drone technology have rapidly led to their use for monitoring and managing wildlife populations but a broad and generalised framework for their application to complex wildlife aggregations is still lacking. We present a generalised semi‐automated approach where machine learning can map targets of interest in drone imagery, supported by predictive modelling for estimating wildlife aggregation populations. We demonstrated this application on four large spatially complex breeding waterbird colonies on floodplains, ranging from c. 20,000 to c. 250,000 birds, providing estimates of bird nests. Our mapping and modelling approach was applicable to all four colonies, without any modification, effectively dealing with variation in nest size, shape, colour and density and considerable background variation (vegetation, water, sand, soil, etc.). Our semi‐automated approach was between three and eight times faster than manually counting nests from imagery at the same level of accuracy. This approach is a significant improvement for monitoring large and complex aggregations of wildlife, offering an innovative solution where ground counts are costly, difficult or not possible. Our framework requires minimal technical ability, is open‐source (Google Earth Engine and R), and easy to apply to other surveys.

Citizen science is fundamentally shifting the future of biodiversity research. But although citizen science observations are contributing an increasingly large proportion of biodiversity data, they only feature in a relatively small percentage of research papers on biodiversity. We provide our perspective on three frontiers of citizen science research, areas that we feel to date have had minimal scientific exploration but that we believe deserve greater attention as they present substantial opportunities for the future of biodiversity research: sampling the undersampled, capitalizing on citizen science's unique ability to sample poorly sampled taxa and regions of the world, reducing taxonomic and spatial biases in global biodiversity data sets; estimating abundance and density in space and time, develop techniques to derive taxon-specific densities from presence or absence and presence-only data; and capitalizing on secondary data collection, moving beyond data on the occurrence of single species and gain further understanding of ecological interactions among species or habitats. The contribution of citizen science to understanding the important biodiversity questions of our time should be more fully realized.

1. Habitat fragmentation and land degradation, directly and indirectly caused by urbanization, are drastically altering the world's ecosystems and are therefore driving an imperative for ecological restoration within the world's cities. Current methods for the implementation and monitoring of restoration are limited. Restoration ecology needs cost-effective and repeatable tools for tracking changes at global scales, but with local relevance. 2. We propose the Urban Greenspace Integrity Index-a locally relevant measure of an urban greenspace's response to urbanization, derived from widely accessible citizen science data. Unlike classical measurements of biodiversity (e.g. species richness, species diversity), this index measures species-specific responses to continuous measures of urbanization. 3. Increases in this index are evidence of a successful urban restoration project; that is, restoration results in a community shift that favours urban-sensitive species. Importantly, data for this index are easily and efficiently collected by citizen scientists, providing long-term repeatable data. This urban index, calculated from greenspace surveys, correlates with and complements traditional biodiversity metrics. 4. Synthesis and applications. Policymakers and practitioners can use the index-a measure of the urbanness of the local bird community-to define and track restoration of urban ecosystems, effectively measuring changes in biodiversity in response to urbanization: measuring whether the urbanness of the bird community changes through time. Importantly, this index can be calculated using citizen science data, providing a potentially long-term monitoring effort of restoration projects. K E Y W O R D S alpha diversity, beta diversity, bird surveys, citizen science, gamma diversity, restoration, urban birds, urbanization | 1999 Journal of Applied Ecology CALLAGHAN et AL.