Showing papers by "Corey T. Callaghan published in 2022"

Temporal trends in the spatial bias of species occurrence records

Abstract: Large-scale biodiversity databases have great potential for quantifying long-term trends of species, but they also bring many methodological challenges. Spatial bias of species occurrence records is well recognized. Yet, the dynamic nature of this spatial bias – how spatial bias has changed over time – has been largely overlooked. We examined the spatial bias of species occurrence records within multiple biodiversity databases in Germany and tested whether spatial bias in relation to land cover or land use (urban and protected areas) has changed over time. We focused our analyses on urban and protected areas as these represent two well-known correlates of sampling bias in biodiversity datasets. We found that the proportion of annual records from urban areas has increased over time while the proportion of annual records within protected areas has not consistently changed. Using simulations, we examined the implications of this changing sampling bias for estimation of long-term trends of species' distributions. When assessing biodiversity change, our findings suggest that the effects of spatial bias depend on how it affects sampling of the underlying land-use change drivers affecting species. Oversampling of regions undergoing the greatest degree of change, for instance near human settlements, might lead to overestimation of the trends of specialist species. For robust estimation of the long-term trends in species' distributions, analyses using species occurrence records may need to consider not only spatial bias, but also changes in the spatial bias through time.

Improving quantitative synthesis to achieve generality in ecology

Abstract: Synthesis of primary ecological data is often assumed to achieve a notion of 'generality', through the quantification of overall effect sizes and consistency among studies, and has become a dominant research approach in ecology. Unfortunately, ecologists rarely define either the generality of their findings, their estimand (the target of estimation) or the population of interest. Given that generality is fundamental to science, and the urgent need for scientific understanding to curb global scale ecological breakdown, loose usage of the term 'generality' is problematic. In other disciplines, generality is defined as comprising both generalizability-extending an inference about an estimand from the sample to the population-and transferability-the validity of estimand predictions in a different sampling unit or population. We review current practice in ecological synthesis and demonstrate that, when researchers fail to define the assumptions underpinning generalizations and transfers of effect sizes, generality often misses its target. We provide guidance for communicating nuanced inferences and maximizing the impact of syntheses both within and beyond academia. We propose pathways to generality applicable to ecological syntheses, including the development of quantitative and qualitative criteria with which to license the transfer of estimands from both primary and synthetic studies.

The benefits of contributing to the citizen science platform iNaturalist as an identifier

Abstract: As the number of observations submitted to the citizen science platform iNaturalist continues to grow, it is increasingly important that these observations can be identified to the finest taxonomic level, maximizing their value for biodiversity research. Here, we explore the benefits of acting as an identifier on iNaturalist.

Decision-making of citizen scientists when recording species observations

Abstract: Abstract Citizen scientists play an increasingly important role in biodiversity monitoring. Most of the data, however, are unstructured—collected by diverse methods that are not documented with the data. Insufficient understanding of the data collection processes presents a major barrier to the use of citizen science data in biodiversity research. We developed a questionnaire to ask citizen scientists about their decision-making before, during and after collecting and reporting species observations, using Germany as a case study. We quantified the greatest sources of variability among respondents and assessed whether motivations and experience related to any aspect of data collection. Our questionnaire was answered by almost 900 people, with varying taxonomic foci and expertise. Respondents were most often motivated by improving species knowledge and supporting conservation, but there were no linkages between motivations and data collection methods. By contrast, variables related to experience and knowledge, such as membership of a natural history society, were linked with a greater propensity to conduct planned searches, during which typically all species were reported. Our findings have implications for how citizen science data are analysed in statistical models; highlight the importance of natural history societies and provide pointers to where citizen science projects might be further developed.

Many cameras make light work: opportunistic photographs of rare species in iNaturalist complement structured surveys of reef fish to better understand species richness

Abstract: Abstract Citizen science is on the rise, with growing numbers of initiatives, participants and increasing interest from the broader scientific community. iNaturalist is an example of a successful citizen science platform that enables users to opportunistically capture and share biodiversity observations. Understanding how data from such opportunistic citizen science platforms compare with and complement data from structured surveys will improve their use in future biodiversity research. We compared the opportunistic fish photographs from iNaturalist to those obtained from structured surveys at eight study reefs in Sydney, Australia over twelve years. iNaturalist recorded 1.2 to 5.5 times more fish species than structured surveys resulting in significantly greater annual species richness at half of the reefs, with the remainder showing no significant difference. iNaturalist likely recorded more species due to having simple methods, which allowed for broad participation with substantially more iNaturalist observation events (e.g., dives) than structured surveys over the same period. These results demonstrate the value of opportunistic citizen science platforms for documenting fish species richness, particularly where access and use of the marine environment is common and communities have the time and resources for expensive recreational activities (i.e., underwater photography). The datasets also recorded different species composition with iNaturalist recording many rare, less abundant, or cryptic species while the structured surveys captured many common and abundant species. These results suggest that integrating data from both opportunistic and structured data sources is likely to have the best outcome for future biodiversity monitoring and conservation activities.

Detecting Thresholds of Ecological Change in the Anthropocene

Abstract: Ecological thresholds comprise relatively fast changes in ecological conditions, with respect to time or external drivers, and are an attractive concept in both scientific and policy arenas. However, there is considerable debate concerning the existence, underlying mechanisms, and generalizability of ecological thresholds across a range of ecological subdisciplines. Here, we use the general concept of scale as a unifying framework with which to systematically navigate the variability within ecological threshold research. We review the literature to show how the observational scale adopted in any one study, defined by its organizational level, spatiotemporal grain and extent, and analytical method, can influence threshold detection and magnitude. We highlight a need for nuance in synthetic studies of thresholds, which could improve our predictive understanding of thresholds. Nuance is also needed when translating threshold concepts into policies, including threshold contingencies and uncertainties. Expected final online publication date for the Annual Review of Environment and Resources, Volume 47 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Reply to Robinson et al.: Data integration will form the basis of future abundance estimates

Abstract: We thank Robinson et al. (1) for their interest in our paper quantifying the global species abundance distribution (gSAD) of birds (2). We agree with some of their points regarding uncertainty and bias. As mentioned in the original article, uncertainty for some species is very large, and we reiterate that for many species of conservation interest there are less uncertain datasets—usually derived from structured sampling—that should be used for conservationbased decisions. We do not suggest that our estimates should be used in place of better, high-quality data. However, this local-scale, highly structured data approach cannot be scaled up to all species. Consequently, data integration is a key frontier in ecology

Quantifying effort needed to estimate species diversity from citizen science data

Abstract: Broad-scale biodiversity monitoring relies, at least in part, on the efforts of citizen, or community, scientists. To ensure robust inferences from citizen science data, it is important to understand the spatial pattern of sampling effort by citizen scientists and how it deviates from an optimal pattern. Here, we develop a generalized workflow to estimate the optimal distribution of sampling effort for inference of species diversity (e.g., species richness, Shannon diversity, and Simpson's diversity) patterns using the relationship between species diversity and land cover. We used data from the eBird citizen science project that was collected across heterogeneous landscapes in Florida (USA) to illustrate this workflow across different grain sizes. We found that a relatively small number of samples are needed to meet 95% sampling completeness when diversity estimation is focused on dominant species: 43, 64, 96, 123, 172, and 176 for 5 × 5, 10 × 10, 15 × 15, 20 × 20, 25 × 25, and 30 × 30-km2 grain sizes, respectively. In contrast, three to five times more samples are necessary to infer species diversity when estimation is focused on rare species. However, in both cases, the optimal distribution of effort was spatially heterogeneous, with more effort needed in regions of higher diversity. Our results highlight the potential of citizen science data to make informed comparisons of species diversity in space and time, as well as how sampling effort inherently depends on monitoring goals, such as whether dominant or rare species are targeted. Our general workflow allows for the quantification of sampling effort needed to estimate species diversity with citizen science data and can guide future adaptive sampling by citizen science participants.

Large-scale spatial variability in urban tolerance of birds.

Abstract: Quantifying intraspecific and interspecific trait variability is critical to our understanding of biogeography, ecology and conservation. But quantifying such variability and understanding the importance of intraspecific and interspecific variability remain challenging. This is especially true of large geographic scales as this is where the differences between intraspecific and interspecific variability are likely to be greatest. Our goal is to address this research gap using broad-scale citizen science data to quantify intraspecific variability and compare it with interspecific variability, using the example of bird responses to urbanization across the continental United States. Using more than 100 million observations, we quantified urban tolerance for 338 species within randomly sampled spatial regions and then calculated the standard deviation of each species' urban tolerance. We found that species' spatial variability in urban tolerance (i.e. standard deviation) was largely explained by the variability of urban cover throughout a species' range (R2 = 0.70). Variability in urban tolerance was greater in species that were more tolerant of urban cover (i.e. the average urban tolerance throughout their range), suggesting that generalist life histories are better suited to adapt to novel anthropogenic environments. Overall, species differences explained most of the variability in urban tolerance across spatial regions. Together, our results indicate that (1) intraspecific variability is largely predicted by local environmental variability in urban cover at a large spatial scale and (2) interspecific variability is greater than intraspecific variability, supporting the common use of mean values (i.e. collapsing observations across a species' range) when assessing species-environment relationships. Further studies, across different taxa, traits and species-environment relationships are needed to test the role of intraspecific variability, but nevertheless, we recommend that when possible, ecologists should avoid using discrete categories to classify species in how they respond to the environment.

Anthropogenic habitat modification alters calling phenology of frogs

Abstract: Anthropogenic habitat modification significantly challenges biodiversity. With its intensification, understanding species' capacity to adapt is critical for conservation planning. However, little is known about whether and how different species are responding, particularly among frogs. We used a continental‐scale citizen science dataset of >226,000 audio recordings of 42 Australian frog species to investigate how calling—a proxy for breeding—phenology varied along an anthropogenic modification gradient. Calling started earlier and breeding seasons lengthened with increasing modification intensity. Breeding seasons averaged 22.9 ± 8.25 days (standard error) longer in the most modified compared to the least modified regions, suggesting that frog breeding activity was sensitive to habitat modification. We also examined whether calls varied along a modification gradient by analysing the temporal and spectral properties of advertisement calls from a subset of 441 audio recordings of three broadly distributed frog species. There was no appreciable effect of anthropogenic habitat modification on any of the measured call variables, although there was high variability. With continued habitat modification, species may shift towards earlier and longer breeding seasons, with largely unknown ecological consequences in terms of proximate and ultimate fitness.

Citizen science reveals meteorological determinants of frog calling at a continental scale

Abstract: Here we investigate the strength of the relationships between meteorological factors and calling behaviour of 100 Australian frog species using continent‐wide citizen science data. First, we use this dataset to quantify the meteorological factors that best predict frog calling. Second, we investigate the strength of interactions among predictor variables. Third, we assess whether frog species cluster into distinct groups based on shared drivers of calling.

Habitat associations of dryland avian communities during an extended dry period

Abstract: The influence of resource availability on ecosystem function varies spatially and temporally, among and within ecosystems. Dramatic shifts in moisture-driven resources can drive bottom-up effects on animal behaviours and distributions. Further, complexity arises when landscapes are influenced by large mammalian grazers and predator-induced trophic cascades, such as those mediated by the dingo (Canis familiaris (Dingo)) in the eastern arid Strzelecki Desert in Australia. During the driest two-year period on record for this region, we investigated the persistence of avian communities associated with structurally distinct dunes and swale habitats, and across two different land management regimes (pastoral land with livestock and dingoes, and Sturt National Park managed for conservation without these animals). We grouped all birds into dietary functional groups to infer patterns of habitat use associated with available resources. We also compared incidental observations of the ‘winter’ bird community in part of the study region between the extended dry period of 2018/2019 and wet period of 2020/2021. Despite habitat partitioning, the avian community did not differ between land management regimes except in species richness during the dry period, likely driven by the low numbers of birds present during the surveys. Incidental observations indicated that insectivorous and omnivorous species dominated the bird community in the dry period, with granivorous species forming a greater proportion of the bird community during wet times. Birds with completely or partially insectivorous diets dominated avian species composition on surveys in the dry period, but there were distinct structural vegetation associations among functional groups, indicating that heterogeneity in vegetation structure was likely important for the conservation of refuges, which enable the persistence of avifauna during extended dry periods. Distinct habitat type, structure and available resources shaped avian communities in this landscape, during the extremely resource-limited extended dry period, with implications for conservation and management, particularly given the increasing drying effects of climate change.