Biology subjects

Guralnick, R.

Publications and source records attributed to Guralnick, R..

12 recordsLinked to original sources

bioRxiv2026

Regional trait-threat interactions determine extinction risk in plants.

Global plant biodiversity and associated ecosystem services are being severely threatened by human activities and land-use change. This has led to an immense effort to assess the extinction risk of individual species and associated drivers to inform conservation actions and priorities. However, we lack a more general understanding of the processes that determine variation in vulnerability and resilience among plant taxa facing the same threats in the same or similar ecological conditions and geographic regions. This research helps identify these generalities and determines species and traits that are at disproportionate risk of extinction. Given Floridas high levels of biodiversity and endemism, coupled with ongoing rapid and extensive human development, we use the states native flora as our model system. By combining data on extinction risk, human-induced threats, and plant functional traits, our results show that species threatened with extinction cluster within trait space, with smaller herbaceous species at greater risk than larger woody species. We also find that all categories of threat considered in our study (Development and Infrastructure; Environmental Change and Modification; Natural Hazards and Climate Change; and Resource Extraction) increase extinction risk except for the Invasive Species, Pests, and Diseases threat category. Generalised linear mixed-effect models show differing responses of species to environmental change, habitat loss, and fragmentation, driven by differences in life-history strategies and dispersal capabilities and mechanisms. The varied responses of species facing the same threats uncovered here highlight that plant functional traits in the context of regional ecosystem processes can be used to predict species-specific responses to threats and land-use change, providing a valuable resource for conservation management and prioritisation. Article impact statementPlant functional traits can be used to estimate species-specific responses to human-induced threats and predict overall extinction risk.

ecology↗

bioRxiv2024

The Blueprint for Survival: The Blue Dasher Dragonfly as a Model for Urban Adaptation

Human alteration of natural environments and habitats is a major driver of species decline. However, a handful of species thrive in human altered environments. The biology, distribution, population structure, and molecular adaptations enabling certain species to thrive in human-altered habitats are not well understood. Here, we evaluate the population and functional genomics, ecological niche and distributions, and geometric morphometrics of the blue dasher (Pachydiplax longipennis), one of the most ubiquitously observed insects in human altered habitats. Using resequencing data we identify a number of genes involved with the success of the blue dasher in human altered habitats, including loci contributing to immune function and response to oxidative stress. Some genes related to these functions are found in regions of strong population structure, while others are not, potentially indicating both regional and widespread adaptations to urban environments within this species. Using one of the most robust locality datasets for any species to date, we also generate habitat suitability predictions which show that P. longipennis has spread with urbanization, suggesting humans have created suitable habitat for this species. These results complement morphological and genomic data showing P. longipennis (particularly East of the Rocky Mountains) has the capacity to rapidly disperse to newly suitable habitats. Given the shared barriers to colonizing an urban habitat, we expect that many of the adaptations we have identified in P. longipennis can be used for predicting what animals might succeed in urban habitats more generally.

evolutionary biology↗

bioRxiv2024

Precipitation tolerance determines elevational migration strategies of resident birds of the Western Ghats of India.

O_LIAvian elevational migration is a common but often overlooked form of short-distance migration. Numerous hypotheses have been proposed to explain this behavior, yet few studies have tested those comprehensively. We examine the climatic constraint hypothesis - a key hypothesis explaining elevational migration - to evaluate its predictions for avian elevational migration in the monsoon-dominated Western Ghats of India. C_LIO_LIWe used citizen science data from eBird to quantify elevational migration patterns of resident birds of the region. Using robust data curation protocols and new bias correction methods, we modeled migration patterns of 164 species across summer, monsoon and winter seasons. To formally test the climatic constraint hypothesis, we modeled the likelihood and distance of migration against body size and environmental niche breadths, using phylogenetically informed logistic regression and Bayesian generalized linear mixed models. C_LIO_LIOur results show that 43% of resident birds exhibited elevational migration in at least one season. Most species migrated between winter and summer (57), followed by migrations between summer and monsoon (39) and then monsoon and winter (38). Species predominantly moved upslope in summer (82%) and downslope in monsoon (87%), with no discernible pattern of direction in winter. Species with broader temperature tolerances were more likely to migrate across all seasons. Additionally, species with broader precipitation niches and larger body sizes moved further downslope during the monsoon and winter, respectively. C_LIO_LIWe found that species with broader tolerances to environmental conditions were more likely to be migratory and moved further along the elevational gradient, contradictory to the expectations of the climatic constraint hypothesis. Our analyses suggest that elevational migrants of the Western Ghats are not climatically limited but likely possess flexibility to track ecological resources that vary with season and elevation. C_LI

ecology↗

bioRxiv2024

Elevational and Oceanic Barriers Shape the Distribution, Dispersal and Diversity of Aotearoa's Kapokapowai (Uropetala) Dragonflies

Mountains and islands provide an opportunity for studying the biogeography of diversification and population fragmentation. Aotearoa (New Zealand) is an excellent location to investigate both phenomena due to alpine emergence and oceanic separation. While it would be expected that separation across oceanic and elevation gradients are major barriers to gene flow in animals, including aquatic insects, such hypotheses have not been thoroughly tested in these taxa. By integrating population genomic from sub-genomic Anchored-Hybrid Enrichment sequencing, ecological niche modeling, and morphological analyses from scanning-electron microscopy, we show that tectonic uplift and oceanic vicariance are implicated in speciation and population structure in Kapokapowai (Uropetala) dragonflies. Although Te Moana o Raukawa (Cook Strait), is likely responsible for some of the genetic structure observed, speciation has not yet occurred in populations separated by the strait. We find that the altitudinal gradient across K[a] Tiritiri-o-te-Moana (the Southern Alps) is not impervious but it significantly restricts gene flow between aforementioned species. Our data support the hypothesis of an active colonization of K[a] Tiritiri-o-te-Moana by the ancestral population of Kapokapowai, followed by a recolonization of the lowlands. These findings provide key foundations for the study of lineages endemic to Aotearoa.

evolutionary biology↗

bioRxiv2024

PhenoVision: A framework for automating and delivering research-ready plant phenology data from field images

Plant phenology plays a fundamental role in shaping ecosystems, and global change-induced shifts in phenology have cascading impacts on species interactions and ecosystem structure and function. Detailed, high-quality observations of when plants undergo seasonal transitions such as leaf-out, flowering, and fruiting are critical for tracking causes and consequences of phenology shifts, but these data are often sparse and biased globally. These data gaps limit broader generalizations and forecasting improvements in the face of continuing disturbance. One solution to closing such gaps is to document phenology on field images taken by public participants. iNaturalist, in particular, provides global scale research-grade data and is expanding rapidly. Here we utilize over 53 million field images of plants and millions of human annotations from iNaturalist - data spanning all angiosperms and drawn from across the globe - to train a computer vision model (PhenoVision) to detect the presence of fruits and flowers. PhenoVision utilizes a vision transformer architecture pretrained with a masked autoencoder to improve classification success, and it achieves high accuracy for flower (98.5%) and fruit presence (95%). Key to producing research-ready phenology data is post-calibration tuning and validation focused on reducing noise inherent in field photographs, and maximizing the true positive rate. We also develop a standardized set of quality metrics and metadata so that results can be used effectively by the community. Finally, we showcase how this effort vastly increases phenology data coverage, including regions of the globe where data have been limited before. Our end products are tuned models, new data resources, and an application streamlining discovery and use of those data for the broader research and management community. We close by discussing next steps, including automating phenology annotations, adding new phenology targets, e.g., leaf phenology, and further integration with other resources to form a global central database integrating all in-situ plant phenology resources.

ecology↗

bioRxiv2024

Unusual migratory strategy a key factor driving interactions at wind energy facilities in at-risk bats

Seasonal movement strategies are poorly understood for most animals, impeding broader understanding of processes underlying migration and limiting practical conservation needs. Here we develop and implement a framework for integrating multiple sources of endogenous markers, in particular stable hydrogen isotope data, that capture and scale dynamics from the movements of individuals to that of continental migration. We assembled and integrated thousands of new isotopic measurements from bat fur with existing datasets and applied this framework to reveal migratory patterns of three broadly distributed bat species most at risk for fatalities at wind energy facilities. Our findings show that the species comprising the lowest proportion of wind turbine fatalities (silver-haired bats) exhibits expected movements to lower latitudes in autumn and higher latitudes in spring. Surprisingly, the two species with higher wind turbine fatality rates (hoary and eastern red bats) have more complex movements, including significant movement to higher latitudes during autumn. We term this unique strategy "pell-mell" migration, during which some individuals are as likely to move to higher latitudes as lower latitudes, relative to their individual summering grounds, in early autumn, after which they move to similar or lower latitudes to overwinter. The pell-mell migratory period corresponds with peak fatalities at wind energy facilities, and bats moving northward during autumn are associated with mortality at those facilities. Our results provide direct support for the hypothesis that bat fatalities at wind energy facilities are related to migration and highlight the importance of migratory distance as an ultimate driver of increased interactions with wind energy facilities, which appears significantly greater for species that travel widely across latitudes in the autumn.

ecology↗

bioRxiv2023

Rising minimum temperatures contribute to 50 years of shifting Arctic and boreal butterfly communities in North America

AbstractGlobal climate change has been identified as a major driver of observed insect declines, yet in many regions there are critical knowledge gaps for how communities are responding to climate. Poleward regions are of particular interest because warming is most rapid while biodiversity data are most sparse. Building on recent advances in occupancy modeling of presence-only data, we reconstructed 50 years (1970-2019) of butterfly population trends in response to rising minimum temperatures in one of the most under sampled regions of the continent. Among 90 modeled species, we found that cold-adapted species are far more often in decline compared to their warm-adapted, more southerly distributed counterparts. Further, in a post-hoc analysis using species traits, we find that species range-wide average annual temperature and wingspan are a consistent predictor of occupancy changes. Species with warmer ranges and larger wingspans were most likely to be increasing in occupancy. Our results provide the first look at macroscale butterfly biodiversity shifts in a critically under sampled region of North America. Further, these results highlight the potential of leveraging the wealth of presence only data, the most abundant source of historical insect biodiversity. New approaches to the modeling of presence only data will match recent increases in community science participation with sparse historical records to reconstruct trends even in poorly sampled regions.

ecology↗

bioRxiv2021

A community-developed extension to Darwin Core for reporting the chronometric age of specimens

Darwin Core, the data standard used for sharing modern biodiversity and paleodiversity occurrence records, has previously lacked proper mechanisms for reporting what is known about the estimated age range of specimens from deep time. This has led to data providers putting these data in fields where they cannot easily be found by users, which impedes the reuse and improvement of these data by other researchers. Here we describe the development of the Chronometric Age Extension to Darwin Core, a ratified, community-developed extension that enables the reporting of ages of specimens from deeper time and the evidence supporting these estimates. The extension standardizes reporting about the methods or assays used to determine an age and other critical information like uncertainty. It gives data providers flexibility about the level of detail reported, focusing on the minimum information needed for reuse while still allowing for significant detail if providers have it. Providing a standardized format for reporting these data will make them easier to find and search and enable researchers to pinpoint specimens of interest for data improvement or accumulate more data for broad temporal studies. The Chronometric Age Extension was also the first community-managed vocabulary to undergo the new Biodiversity Informatics Standards (TDWG) review and ratification process, thus providing a blueprint for future Darwin Core extension development.

paleontology↗

bioRxiv2020

Closing Gaps But Increasing Bias In North American Butterfly Inventory Completeness

Aggregate biodiversity data from museum specimens and community observations have promise for macroscale ecological analyses. Despite this, many groups are under-sampled, and sampling is not homogeneous across space. Here we used butterflies, the best documented group of insects, to examine inventory completeness across North America. We separated digitally accessible butterfly records into those from natural history collections and burgeoning community science observations to determine if these data sources have differential spatio-taxonomic biases. When we combined all data, we found startling under-sampling in regions with the most dramatic trajectories of climate change and across biomes. We also found support for the hypothesis that community science observations are filling more gaps in sampling but are more biased towards areas with the highest human footprint. Finally, we found that both types of occurrences have familial-level taxonomic completeness biases, in contrast to the hypothesis of less taxonomic bias in natural history collections data. These results suggest that higher inventory completeness, driven by rapid growth of community science observations, is partially offset by higher spatio-taxonomic biases. We use the findings here to provide recommendations on how to alleviate some of these gaps in the context of prioritizing global change research.

ecology↗

bioRxiv2019

Research applications of primary biodiversity databases in the digital age

We are in the midst of unprecedented change--climate shifts and sustained, widespread habitat degradation have led to dramatic declines in biodiversity rivaling historical extinction events. At the same time, new approaches to publishing and integrating previously disconnected data resources promise to help provide the evidence needed for more efficient and effective conservation and management. Stakeholders have invested considerable resources to contribute to online databases of species occurrences and genetic barcodes. However, estimates suggest that only 10% of biocollections are available in digital form. The biocollections community must therefore continue to promote digitization efforts, which in part requires demonstrating compelling applications of the data. Our overarching goal is therefore to determine trends in use of mobilized species occurrence data since 2010, as online systems have grown and now provide over one billion records. To do this, we characterized 501 papers that use openly accessible biodiversity databases. Our standardized tagging protocol was based on key topics of interest, including: database(s) used, taxa addressed, general uses of data, other data types linked to species occurrence data, and data quality issues addressed. We found that the most common uses of online biodiversity databases have been to estimate species distribution and richness, to outline data compilation and publication, and to assist in developing species checklists or describing new species. Only 69% of papers in our dataset addressed one or more aspects of data quality, which is low considering common errors and biases known to exist in opportunistic datasets. Globally, we find that biodiversity databases are still in the initial stages of data compilation. Novel and integrative applications are restricted to certain taxonomic groups and regions with higher numbers of quality records. Continued data digitization, publication, enhancement, and quality control efforts are necessary to make biodiversity science more efficient and relevant in our fast-changing world.

zoology↗

bioRxiv2018

Finding the signal in the noise of Citizen Science Observations

While many observations of species are being collected by citizen science projects worldwide, it can be challenging to identify projects collecting data that effectively monitor biodiversity. Over the past several years the allure of taking a \"Big Data\" approach has provided the opportunity to gather massive quantities of observations via the Internet, too often with insufficient information to describe how the observations were made. Information about species populations -- where and when they occur and how many of them are there -- (i.e., the signal) can be lost because insufficient information is gathered to account for the inherent biases in data collection (i.e., the noise). Here we suggest that citizen science projects that have succeeded in motivating large numbers of participants, must consider factors that influence the ecological process that affect species populations as well as the observation process that determines how observations are made. Those citizen science projects that collect sufficient contextual information describing the observation process can be used to generate increasingly accurate information about the distribution and abundance of organisms. We illustrate this using eBird as a case study, describing how this citizen science platform is able to collect vital contextual information on the observation process while maintaining a broad global constituency of participants. We highlight how eBird provides information with which to generate biodiversity indicators -- specifically distribution, abundance, and habitat associations -- across the entire annual cycle, even for populations of long distance migratory birds, a highly challenging taxon.

ecology↗

bioRxiv2017

No general relationship between mass and temperature in endotherm species

Bergmanns rule is a widely-accepted biogeographic rule stating that individuals within a species are smaller in warmer environments. While there are many single-species studies and integrative reviews documenting this pattern, a data-intensive approach has not been used yet to determine the generality of this pattern. We assessed the strength and direction of the intraspecific relationship between temperature and individual mass for 952 bird and mammal species. For eighty-seven percent of species, temperature explained less than 10% of variation in mass, and for 79% of species the correlation was not statistically significant. These results suggest that Bergmanns rule is not general and temperature is not a dominant driver of biogeographic variation in mass. Further understanding of size variation will require integrating multiple processes that influence size. The lack of dominant temperature forcing weakens the justification for the hypothesis that global warming could result in widespread decreases in body size.

ecology↗