Geology topics

Lucas N. Joppa

Publications and source records attributed to Lucas N. Joppa.

4 recordsLinked to original sources

USGS2020

The IPBES global assessment: Pathways to action

The first Global Assessment of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services found widespread, accelerating declines in Earth’s biodiversity and associated benefits to people from nature. Addressing these trends will require science-based policy responses to reduce impacts, especially at national to local scales. Effective scaling of science-policy efforts driven by global and national assessments is a major challenge for turning assessment into action, and will require unprecedented commitments on the part of scientists to engage with communities of policy and practice. Fulfillment of science’s social contract with society, and with nature, will require strong institutional support for scientists’ participation in activities that transcend conventional research and publication.

Trends in Ecology and Evolution↗

USGS2015

Detecting the influence of rare stressors on rare species in Yosemite National Park using a novel stratified permutation test

Statistical models often use observational data to predict phenomena; however, interpreting model terms to understand their influence can be problematic. This issue poses a challenge in species conservation where setting priorities requires estimating influences of potential stressors using observational data. We present a novel approach for inferring influence of a rare stressor on a rare species by blending predictive models with nonparametric permutation tests. We illustrate the approach with two case studies involving rare amphibians in Yosemite National Park, USA. The endangered frog, Rana sierrae , is known to be negatively impacted by non-native fish, while the threatened toad, Anaxyrus canorus , is potentially affected by packstock. Both stressors and amphibians are rare, occurring in ~10% of potential habitat patches. We first predict amphibian occupancy with a statistical model that includes all predictors but the stressor to stratify potential habitat by predicted suitability. A stratified permutation test then evaluates the association between stressor and amphibian, all else equal. Our approach confirms the known negative relationship between fish and R. sierrae , but finds no evidence of a negative relationship between current packstock use and A. canorus breeding. Our statistical approach has potential broad application for deriving understanding (not just prediction) from observational data.

California↗

USGS2015

Emerging technologies to conserve biodiversity

Technologies to identify individual animals, follow their movements, identify and locate animal and plant species, and assess the status of their habitats remotely have become better, faster, and cheaper as threats to the survival of species are increasing. New technologies alone do not save species, and new data create new problems. For example, improving technologies alone cannot prevent poaching: solutions require providing appropriate tools to the right people. Habitat loss is another driver: the challenge here is to connect existing sophisticated remote sensing with species occurrence data to predict where species remain. Other challenges include assembling a wider public to crowdsource data, managing the massive quantities of data generated, and developing solutions to rapidly emerging threats.

Trends in Ecology and Evolution↗

USGS2012

More than a meal: integrating non-feeding interactions into food webs

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Ecology Letters↗