Collaborative Research: Biodiversity Dynamics: Linking Broad Scale Remote Sensing with Arthropod Metabarcoding Across a Geological Age Gradient in the Hawaiian Islands

The global biodiversity crisis is a central problem facing humanity, yet we lack the means to assess biodiversity at the pace of the Earth's changing environment. For this project, rapid assessment technologies will be integrated at the landscape and island level to forecast unseen change in high-impact insect and spider populations tracked by their DNA.

The project goal is to infer processes that shape biodiversity and its decline, and how these processes might be captured remotely across different scales and degrees of human impact. In the Hawaiian Islands, the velocity and extent of non-native plant invasions in ecological landscapes will be measured using satellite, helicopter, drone, and ground-based monitoring systems.

Those metrics will be combined with assessments of insect biodiversity at the same sites generated from rapid, high-throughput environmental genomic analyses. Outcomes will aid land managers with actionable solutions, building on the ongoing activities of the research team and working with the Pacific Regional Invasive Species and Climate Change (Pacific RISCC) Management Network.

Results will be translated for the general public through the web-based ESRI ArcGIS StoryMap. The researchers will provide mentoring for undergraduates, graduate students and a postdoc at the University of California Berkeley, the University of Maryland, and the University of Hawaii Hilo, the latter of which is a primarily undergraduate serving institution that helps meet the needs of Pacific Islanders.

Products will include the development of a learning module and toolkit for students to adopt new skills of data analysis and visualization for communicating biodiversity and remote sensing data.

Using the model system of the Hawaiian Islands, the project will couple high-throughput arthropod biodiversity sequencing and remote sensing imagery to examine correlated shifts across two orthogonal gradients set within the same native forest type. The first gradient is a geological chronosequence, from 0-5 million years, across which arthropod communities increase in diversity and become more ecologically specialized.

The second, intersecting, gradient is composed of a landscape matrix that runs from native to heavily invaded forest habitats on each island. At plot scales, whole arthropod communities will be sampled using genetic signatures from high-throughput sequencing to test models of community assembly over extended ecological-to-evolutionary time, and hence infer the changing roles of key processes of filtering, competition, and neutrality, through time.

The models will predict trajectories of disassembly in the face of rapid biotic change. Arthropod community analyses will be coupled with remote sensing imagery at scales ranging from regional (archipelago; satellites), to area (leeward slope of one mountain; helicopter), to plots within heterogeneous landscapes (drone imagery and airborne and ground lidar).

The different remote indicators of change in the ecosystem (spectral properties, leaf and water content, nitrogen content, plant stress) will be integrated by using structural equation models (SEMs) to identify candidate parameters that reflect arthropod community dynamics in rapidly changing island forest systems. Joint species distribution models will be used to integrate data across scales.

This research will test the predictability of remote sensing data for explaining the spatio-temporal variability of biodiversity and its resilience to anthropogenic modification. In addition to training at the undergraduate, graduate and postdoctoral levels, products will include the development of a learning module and toolkit for students to adopt new skills of data analysis and visualization for communicating biodiversity and remote sensing data.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.