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Eppinga, M. B.

Publications and source records attributed to Eppinga, M. B..

3 recordsLinked to original sources

Causal discovery in biodiversity-mediated social-ecological systems

Global biodiversity loss and climate change exacerbate feedbacks within social-ecological systems, i.e., between ecosystems, their services and well-being of human societies. Our ability to mediate these feedbacks is hampered by incomplete understanding of the underlying causal links, which could benefit from interdisciplinary approaches to discover theoretical or empirical links from heterogeneous data characteristic of social-ecological studies. We propose a novel framework connecting literature-based causal knowledge with data-driven inference of causality. We test this framework for the highly biodiverse island of Borneo by conducting a systematic literature review of 7473 studies over 170 years, and a causal inference analysis for three conceptual causal diagrams connecting global change, socio-economics, ecosystem services, and biodiversity-ecosystem function using a set of 227 spatially explicit variables. We find that, while natural or social processes have been mostly studied independently, a set of studies already documents causal links across social-ecological domains for processes related to deforestation, food or energy. Causal discovery unveiled consistent negative causal links between global change, social-economic landscape, and biodiversity-ecosystem function, and positive causal links between global change and socio-economics, and these links were robust to indicator selection and addition. We detected few and weak links between social-economic landscape, global change, and ecosystem services. When comparing the data-driven inferred causal links to those documented by the literature, we find that links between biodiversity and ecosystem function with global change, and links between social-economic landscape and ecosystem services were also consistent, and causal analysis uncovered new (potential) causal links not yet described in the literature. Significance StatementAddressing climate change and biodiversity loss in the Anthropocene requires us to recognize that human societies and ecological systems are inherently interconnected in complex adaptive systems. Causal understanding in social-ecological systems enables understanding system dynamics and response to pressures and shocks. While promising, few studies have studied these systems using a combination of big literature which provides the state-of-the-knowledge and big data that provides the underlying information for causal discovery. With this framework, we can specify and rigorously test, causal links in biodiversity-mediated social-ecological processes under global change and examine potential interventions that lead to much needed sustainable outcomes.

ecology↗

Inferring genetic structure of European beech from observations of spectral phenotypes

Biodiversity loss presents a growing threat to the global environment, and systematic and spatially contiguous monitoring is needed to inform mitigation strategies. Monitoring of genetic diversity within species, a key factor when assessing biodiversity loss, is laborious and could be supported by scalable phenotypic observations allowing inferences about genetic variation. We studied genetic and phenotypic variation in one of Europes most prevalent forest-forming trees, the common beech Fagus sylvatica L., using whole-genome sequence data and spectral phenotypes from 219 individuals at 23 sites across the species natural range. Spectral phenotypes were collected under standardized illumination and observation conditions from the same top-of-canopy leaves used for nuclear DNA extraction. We found that spectral and environmental information accounted for 77% of the variance along the first two principal coordinates representing genetic structure among sampled individuals, where spectral phenotypes contributed 12% to the prediction of genetic structure. Further, we identified 14 SNPs (single nucleotide polymorphisms), of which two were located within annotated genes, that showed significant associations with variation in leaf reflectance. Our study demonstrates how linking spectral and genomic variation in tree species may be upscaled to the remote observations to support monitoring, understanding and mitigating loss of genetic diversity within species.

plant biology↗

Travelling waves due to negative plant-soil feedbacks in a model including tree life-stages

The emergence and maintenance of tree species diversity in tropical forests is commonly attributed to the Janzen-Connell (JC) hypothesis, which states that growth of seedlings is suppressed in the proximity of conspecific adult trees. As a result, a JC distribution due to a density-dependent negative feedback emerges in the form of a (transient) pattern where conspecific seedling density is highest at intermediate distances away from parent trees. Several studies suggest that the required density-dependent feedbacks behind this pattern could result from interactions between trees and soil-borne pathogens. However, negative plant-soil feedback may involve additional mechanisms, including the accumulation of autotoxic compounds generated through tree litter decomposition. An essential task therefore consists in constructing mathematical models incorporating both effects showing the ability to support the emergence of JC distributions. In this work, we develop and analyse a novel reaction-diffusion-ODE model, describing the interactions within tropical tree species across different life stages (seeds, seedlings, and adults) as driven by negative plant-soil feedback. In particular, we show that under strong negative plant-soil feedback travelling wave solutions exist, creating transient distributions of adult trees and seedlings that are in agreement with the Janzen-Connell hypothesis. Moreover, we show that these travelling wave solutions are pulled fronts and a robust feature as they occur over a broad parameter range. Finally, we calculate their linear spreading speed and show its (in)dependence on relevant nondimensional parameters. 2020 MSC35C07, 34C60, 34D05, 35K57, 37C25, 65M06, 92D40.

ecology↗