22 Jan 2026

Guideposts and Guardrails for Biodiversity Accounting in the 21st Century

Abstract: The new Kunming-Montreal Post-2020 Global Biodiversity Framework (GBF) calls for transformative change to integrate biodiversity and conservation goals into decision-making across public and private sectors. As a result, biodiversity accounting approaches, which reduce the multifaceted complexity of nature to quantitative metrics for practical applications, are proliferating rapidly. These approaches will be essential for implementing growing practices like nature-based solutions, corporate biodiversity stewardship, no net loss policies, and sustainable infrastructure development. In this perspectives article, we identify ten considerations for biodiversity accounting to ground ongoing discourse in sound ecological science and to better integrate biodiversity into societal decision-making. These considerations pertain to three processes within biodiversity accounting: (1) selecting biodiversity targets, facets, indicators, and metrics, (2) tool and framework design, and (3) implementation. For each consideration, we highlight desirable attributes or practices, which we call “guideposts”, and cautionary notes demarcating problems to be avoided, or “guardrails”. These help to delineate the safe design space for creators and users of biodiversity accounting systems to avoid unintended consequences and reduce risks of failing to achieve conservation objectives via misuse or ineffective approaches. Major considerations include the need for careful disclosure of effort and statistical uncertainty, interoperability and flexibility of frameworks, careful justification and explanation of selected facets, metrics, and indicators, and attention to local social and ecological context. Consideration of these guideposts and guardrails could help avoid unintended consequences like accelerated biodiversity loss and exacerbated environmental injustice while providing a practical basis for achieving the sustainable futures envisioned in the GBF.

21 May 2021

Effect of Individual Differences in Predicting Engineering Students' Performance: A Case of Education for Sustainable Development

Abstract: The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.