A new roadmap for quantitative methodologies of Environmental Impact Assessment (EIA) is proposed, using an ecosystem-based approach. EIA recommendations are currently based on case-by-case rankings, distant from statistical methodologies, and ecological ideas that lack proof of generality or predictive capacities. These qualitative approaches ignore process dynamics, scales of variations and interdependencies and are unable to address societal demands to link socio-economic and ecological processes (e.g. population dynamics). We propose to re-focus EIA around the systemic formulation of interactions between organisms (organized in populations and communities) and their environments but inserted within a strict statistical framework. A systemic formulation allows scenarios to be built that simulate impacts on chosen receptors. To illustrate the approach, we design a minimum ecosystem model that demonstrates nontrivial effects and complex responses to environmental changes and validated with case study. We suggest that an Ecosystem-Based EIA—in which the socio-economic system is an evolving driver of the ecological one—is more promising than a socio-economic-ecological system where all variables are treated as equal. This refocuses the debate on cause-and-effect, processes, identification of essential portable variables, and allows for quantitative comparisons between projects, which is critical in cumulative effects determinations.
In this review, the use of environmental DNA (eDNA) within Environmental Impact Assessment (EIA) is evaluated. EIA documents provide information required by regulators to evaluate the potential impact of a development project. Currently eDNA is being incorporated into biodiversity assessments as a complementary method for detecting rare, endangered or invasive species. However, questions have been raised regarding the maturity of the field and the suitability of eDNA information as evidence for EIA. Several key issues are identified for eDNA information within a generic EIA framework for marine environments. First, it is challenging to define the sampling unit and optimal sampling strategy for eDNA with respect to the project area and potential impact receptor. Second, eDNA assay validation protocols are preliminary at this time. Third, there are statistical issues around the probability of obtaining both false positives (identification of taxa that are not present) and false negatives (non-detection of taxa that are present) in results. At a minimum, an EIA must quantify the uncertainty in presence/absence estimates by combining series of Bernoulli trials with ad hoc occupancy models. Finally, the fate and transport of DNA fragments is largely unknown in environmental systems. Shedding dynamics, biogeochemical and physical processes that influence DNA fragments must be better understood to be able to link an eDNA signal with the receptor’s state. The biggest challenge is that eDNA is a proxy for the receptor and not a direct measure of presence. Nonetheless, as more actors enter the field, technological solutions are likely to emerge for these issues. Environmental DNA already shows great promise for baseline descriptions of the presence of species surrounding a project and can aid in the identification of potential receptors for EIA monitoring using other methods.
This viewpoint article examines Environmental Impact Assessment (EIA) practices in developed and transitioning nations, identifies weaknesses, and proposes a new quantitative approach. The literature indicates that there exists little to no standardization in EIA practice, transitioning nations rely on weak scientific impact analyses, and the establishment of baseline conditions is generally missing. The more fundamental issue is that the "receptor"-based approach leads to a qualitative and subjective EIA, as it does not adequately integrate the full measure of the complexity of ecosystems, ongoing project risks, and cumulative impacts. We propose the application of a new framework that aims to ensure full life cycle assessment of impacts applicable to any EIA process, within any jurisdictional context. System-Based EIA (SBEIA) is based on modeling to predict changes and rests on data analysis with a statistically rigorous approach to assess impacts. This global approach uses technologies and methodologies that are typically applied to characterize ecosystem structure and functioning, including remote sensing, modeling, and in situ monitoring. The aim of this approach is to provide a method that can produce quantifiable reproducible values of impact and risk and move EIA towards its substantive goal of sustainable development. The adoption of this approach would provide a better evaluation of economic costs and benefits for all stakeholders.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.