An official website of the United States government
Understanding global patterns of genetic diversity (GD) is essential to describe, monitor, and preserve the processes giving rise to life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrate groups that comprise a small fraction of Earth’s biodiversity. Here, we construct the first global map of predicted insect genetic diversity. We calculate the global distribution of GD mean (GDM) and evenness (GDE) of insect assemblages, identify the global environmental correlates of insect GD, and make predictions for undersampled regions. Based on the largest and most species-rich single-locus genetic dataset assembled to date, we find that both GD metrics follow a bimodal latitudinal gradient, where GDM and GDE correlate with contemporary climate variation. Our models explain 1/4 and 1/3 of the observed variation in GDM and GDE in insects, respectively, making an important step towards describing global biodiversity patterns in the most diverse animal taxon.
more »
« less
A working guide to harnessing generalized dissimilarity modelling for biodiversity analysis and conservation assessment
Abstract AimGeneralized dissimilarity modelling (GDM) is a powerful and unique method for characterizing and predicting beta diversity, the change in biodiversity over space, time and environmental gradients. The number of studies applying GDM is expanding, with increasing recognition of its value in improving our understanding of the drivers of biodiversity patterns and in implementing a wide variety of spatial assessments relevant to biodiversity conservation. However, apart from the original presentation of the GDM technique, there has been little guidance available to users on applying GDM to different situations or on the key modelling decisions required. InnovationWe present an accessible working guide to GDM. We describe the context for the development of GDM, present a simple statistical explanation of how model fitting works, and step through key considerations involved in data preparation, model fitting, refinement and assessment. We then describe how several novel spatial biodiversity analyses can be implemented using GDM, with code to support broader implementation. We conclude by providing an overview of the range of GDM‐based analyses that have been undertaken to date and identify priority areas for future research and development. Main conclusionsOur vision is that this working guide will facilitate greater and more rigorous use of GDM as a powerful tool for undertaking biodiversity analyses and assessments.
more »
« less
- Award ID(s):
- 1655344
- PAR ID:
- 10443345
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Ecology and Biogeography
- Volume:
- 31
- Issue:
- 4
- ISSN:
- 1466-822X
- Page Range / eLocation ID:
- p. 802-821
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract IssueGeodiversity (i.e., the variation in Earth's abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. EvidenceWe show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA's Shuttle Radar Topography Mission (SRTM) andc. 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. ConclusionWith the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature.more » « less
-
Abstract AimThe accumulation of functional diversity in communities is poorly understood. Conveniently, the general dynamic model of island biogeography (GDM) makes predictions for how such diversity might accumulate over time. In this multiscale study of land snail communities on 10 oceanic archipelagos located in various regions of the globe, we test hypotheses of community assembly in systems where islands serve as chronosequences along island ontogeny. LocationTen volcanic archipelagos. Time periodFrom 23 Ma to the present. Major taxa studiedEndemic land snails. MethodsInitially, we assembled geological island characteristics of area, isolation and ontogeny for all studied islands. We then characterized island‐scale biotic variables, including the species diversity and functional diversity of snail communities. From these data, we assessed relationships between island and snail community variables as predicted by the GDM, focusing initially on the islands of the Galápagos archipelago and thereafter with a broader analysis of 10 archipelagoes. ResultsAs in other studies of island assemblages, in Galápagos we find a hump‐shaped curve of species richness, with depauperate snail faunas on early‐ontogeny islands, increasing species richness on mid‐ontogeny islands and low species richness on islands in late ontogeny. We find exceptionally low functional diversity on early‐ontogeny islands that increases through mid‐ontogeny, whereas late‐ontogeny islands exhibit a range of functional diversity. The analysis including all 10 archipelagos indicates a major role of archipelago‐specific factors. In both sets of analyses, functional diversity is exceptionally low on early‐ontogeny islands, and island ontogeny is a significant predictor of morphology. Main conclusionsConsistent patterns of functional diversity across island ontogeny on all examined archipelagos indicate a common role for habitat filtering, ecological opportunity and competition in a diversity of systems, leading to predictable changes in functional diversity and average morphology through island ontogeny, whereas patterns of species richness appear subject to archipelago‐specific factors.more » « less
-
Abstract Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.more » « less
-
Abstract This paper outlines the potential gains for Constructionist research and praxis in modelling that might be obtained by recognising the power of the Patch—a humble computational being in the NetLogo modelling environment that has been overshadowed by its more popular fellow agent, the Turtle. To contextualise this opportunity, I describe how Constructionist modelling has thrived by promoting forms of learning that rely on learners’ identifying with agents. I argue that patches are a neglected agent type in this multi‐agent modelling tradition, and that the possibilities for learners to adopt the patch perspective in support of exploratory forms of modelling and aesthetic expression have been under‐researched. Nevertheless, I show there are a variety of powerful ways for learners––both individually and in groups––to identify with patches. I describe ongoing research showing how taking an aesthetic approach to patches has the potential to support individuals and groups in powerful forms of learning with and about multi‐agent modelling. Practitioner notesWhat is already known about this topicTurtles (movable agents in Logo and Constructionist environments descended from Logo) can be ‘transitional objects’ that provide learners a way to make powerful ideas their own.These agents can be powerful ‘objects‐to‐think‐with’ in large part because they encourage learners to identify with them in a form of learning known as ‘syntonic learning’.Expressive activities that draw on learners’aestheticinterests can support their learning with and about computational representations.Multi‐agent modelling is a powerful extension of Logo‐based learning environments that provides access to powerful ideas about complex systems and their emergent properties.In the multi‐agent setting, individual learners and/or groups of learners can identify syntonically with agents to provide entry points for reasoning about complexity.What this paper addsPatches (non‐movable agents in the NetLogo modelling environment) are under‐represented in the research on multi‐agent modelling, and the potential for learners to adopt the patches’ perspective has been neglected.An aesthetically driven approach to patches can ground students’ understanding of their expressive value.Participatory activities in which learners play the role of patches (called ‘Stadium Card’ activities) can ground the patch perspective, so that learners can achieve a form of syntonicity and/or collectively adopt the perspective of patches in the aggregate.Participatory activities that blend intrinsic and extrinsic perspectives on the patch grid can further enhance learners’ facility with programming for patches and their understanding of patches’ collective expressive power.Implications for practice and/or policyBalancing the focus between turtles and patches can enrich the modelling toolbox of learners new to agent‐based modelling.Patchesdocapture important aspects of individual and collective experience, and so can be good objects‐to‐think‐with, especially when conceptualising phenomena at a larger scale.The expressive potential of the patch grid is an important topic for computer science as well (eg, through 2D cellular automata). This is a rich context for learning in itself, which can be made accessible to groups of learners through physical or virtual participatory role‐play.Moreover, physical or virtual grids of people‐patches may exhibit novel aggregate computational properties that could in turn become interesting areas for research in computer science.more » « less
