Ecological Science Research Articles

Beyond guides, protocols and acronyms: Adoption of good modelling practices depends on challenging academia's status quo in ecology

Implementing good modelling practices (GMP) in ecological sciences is key to improving scientific reliability. Despite the increased availability of guidelines and protocols detailing how principles such as FAIR and PERFICT can be implemented to improve good modelling practices, the sharing of code which can reproduce results and workflows remains remarkably low. In this work, we explore potential root causes of this discrepancy. We identify three key factors inherent to the current academic structure that, in our experience, might play a role in hindering a wider adoption of GMP: (1) acknowledgment of the time required to implement GMP in projects, (2) the lack of GMP and software development training among ecologists, and (3) perception of GMP as unrewarding in the short-term. We argue that there is an urgent need for systemic changes. Such changes include (1) a cultural shift to value the incorporation of GMP across projects, emphasising the need for explicit budget allocation and careful scheduling of its implementation, (2) redesigning academic curricula to explicitly include GMP and software development as fundamental disciplines in ecology, and (3) an increase in recognition of open and functional code and workflows for career advancement. We call for concerted efforts for bridging this gap, and propose a hopeful outlook emphasising the role of a new generation of scientists and tools committed to good science. Proposing concrete actions, we aim to start a discussion on challenging academia's status quo in ecology and support scientists in bringing a significant paradigm shift to ecological modelling.

The path to scientifically sound biodiversity valuation in the context of the Global Biodiversity Framework

Successful implementation of the Kunming-Montreal Global Biodiversity Framework requires identifying a process for measuring and valuing changes in biodiversity that build on the recognition that economics and valuation must play a key role in “halting and reversing” biodiversity loss. Here, we discuss considerations for a practical path to valuing changes in biodiversity. Framing changes in the value of biodiversity as a summary of changes in certain natural assets enables leveraging existing approaches and international standards associated with environmental-economic accounting. We discuss why an approach that builds from individual species, evolutionary groups, or functional groups into a practical, hierarchical statistical classification system is better than the development of any one biodiversity index. We merge techniques from ecology and other natural sciences, national and environmental-economic accounting, and economics, which are all on the cusp of making measurement of the change in the value of biodiversity possible. The focus should be on scaling and integrating these approaches. The path forward appears to begin with imperfect but useful measures, grounded in robust concepts, while establishing ambition to further scale-up measurements—just like the past evolution of many other official statistical series.

A low-cost UAV survey can unravel Baird's Tapir (Tapirus bairdii) trail network dynamics in a neotropical highland forest

UAV technology has transformed spatial data collection and high-spatial resolution analysis of diverse environments around the world. Its role within geosciences, ecology, engineering, and other sciences has been increasing withing the last decade. In ecological and geomorphological aspects, it offers a powerful tool for studying landforms, surface processes, vegetation, and animal behavior globally. Our study employs high-resolution UAV surveys to analyze Tapirus bairdii trail networks and their connection to the landscape in a Costa Rican highland paramo-forest national park. Using a DJI Phantom 4 V.2 UAV, we conducted a photogrammetric flight over 3.19 ha, producing datasets with a spatial resolution of 2.99 cm/pixel. These datasets facilitated geostatistical analysis of Tapirus bairdii trails, revealing their complexity and hotspots near lagoons. We investigated lagoon characteristics, finding that finer sediments spatially correspond with higher trail activity. This suggests that sediment types in lagoons influence Tapirus bairdii navigation, impacting trail network composition. Our findings highlight UAV technology's role in advancing ecological and geomorphological research in protected areas, providing insights into Tapirus bairdii behavior within highland ecosystems. Overall, to the date this is the first high-resolution UAV survey of Tapirus bairdii within these types of highland tropical environments.

The use of conceptual models to structure stock assessments: A tool for collaboration and for “modelling what to model”

Conceptual models are simplified representations of the main components and processes of a dynamic system, the mechanisms by which they are related, and the ways they are observed (i.e., the data generating processes). Constructing a conceptual model (CM) should be the first step when planning a new stock assessment or updating previous assessments, because it can improve the modelling process by guiding the workflow and “modelling what to model”. CMs should be built by summarizing information about a system while also proposing hypotheses or assumptions about the uncertainties and unknown aspects. Several steps are necessary to build a CM: 1) gather known information about the species and the fisheries that interact with it, 2) state the objectives of the stock assessment, 3) define the spatial scale, 4) define the temporal scale, and 5) outline components and processes of the system (biological, fisheries and observation processes) and what drives them. Initial draft CMs should be based on the best available science and constructed using the fundamental principles of ecology, socioecology, fisheries and other relevant sciences. CMs offer a framework for integrating knowledge across domains, and benefit from an elicitation process. The elicitation process is a set of deliberate activities (e.g., workshops) that allow other experts and relevant parties to contribute with their knowledge to enrich draft CMs. CMs are not static entities but rather dynamic constructs that can identify future research directions and evolve to incorporate new insights and knowledge. Fisheries systems for highly migratory pelagic species in the Pacific Ocean (north Pacific Albacore tuna, eastern Pacific Dorado, and south Pacific Swordfish) are used as examples to illustrate how to develop CMs, and demonstrate improvements to the subsequent assessment models following development of the CMs.

The trade-offs effect of ecosystem health and socio-economic development on tea production

Ecosystem health (EH) maintenance and improvement are important goals in environmental and ecological management, and help realize regional sustainable development goals. EH assessment and the regulatory mechanism have remained popular research fields in landscape ecology science. However, the improvement in EH assessment methods is ongoing, the influences of EH and socioeconomic development on agricultural production remain unclear. In this study, we chose Fujian Province in China as the study area, first quantitatively assess EH based on the Vigor–Organization–Resilience–Services (VORS) model, and thereafter explore the response of tea production to EH and socioeconomic development using the structural equation model (SEM). We found that the mean EH value in Fujian Province was 0.52 in 2010, which was 6.12% and 10.64% higher than that in 2000 and 2020, respectively. The high-EH-value regions were distributed in the northwest, while the southeastern regions exhibited low-EH-value agglomerations. According to the temporal evolution characteristics of EH, the kernel density curve patterns exhibited single peaks, and the curves shifted from a broad to a narrow peak from 2000 to 2020, indicating a trend toward a more balanced distribution of EH spatially. SEM results showed a significant positive effect of EH on tea production with a coefficient of 0.86. However, there is a significant trade-off between EH and economic development, as indicated by a coefficient of −0.6. There are also negative indirect effects on tea development when mediated by economic development. However, the overall effect of EH on tea production is 0.8, indicating that EH is still effective in promoting tea production. The results of this study have implications for the integration of ecosystem management and agricultural production management in the region.

Artificial Intelligence for Climate Change Biology: From Data Collection to Predictions.

In the era of big data, ecological research is experiencing a transformative shift, yet big-data advancements in thermal ecology and the study of animal responses to climate conditions remain limited. This review discusses how big data analytics and artificial intelligence (AI) can significantly enhance our understanding of microclimates and animal behaviors under changing climatic conditions. We explore AI's potential to refine microclimate models and analyze data from advanced sensors and camera technologies, which capture detailed, high-resolution information. This integration can allow researchers to dissect complex ecological and physiological processes with unprecedented precision. We describe how AI can enhance microclimate modeling through improved bias correction and downscaling techniques, providing more accurate estimates of the conditions that animals face under various climate scenarios. Additionally, we explore AI's capabilities in tracking animal responses to these conditions, particularly through innovative classification models that utilize sensors such as accelerometers and acoustic loggers. For example, the widespread usage of camera traps can benefit from AI-driven image classification models to accurately identify thermoregulatory responses, such as shade usage and panting. AI is therefore instrumental in monitoring how animals interact with their environments, offering vital insights into their adaptive behaviors. Finally, we discuss how these advanced data-driven approaches can inform and enhance conservation strategies. In particular, detailed mapping of microhabitats essential for species survival under adverse conditions can guide the design of climate-resilient conservation and restoration programs that prioritize habitat features crucial for biodiversity resilience. In conclusion, the convergence of AI, big data, and ecological science heralds a new era of precision conservation, essential for addressing the global environmental challenges of the 21st century.

Genome-wide identification, phylogenetic, structural and functional evolution of thecore components of ABA signaling in plant species: a focus on rice.

A genome-wide analysis had identified 642 ABA core component genes from 20 plant species, which were further categorized into three distinct subfamilies. The gene structures and evolutionary relationships of these genes had been characterized. PP2C_1, PP2C_2, and SnRK2_1 had emerged as key players in mediating the ABA signaling transduction pathway, specifically in rice, in response to abiotic stresses. The plant hormone abscisic acid (ABA) is essential for growth, development, and stress response, relying on its core components, pyrabactin resistance, pyrabactin resistance-like, and the regulatory component of ABA receptor (PYR/PYL/RCAR), 2C protein phosphatase (PP2C), sucrose non-fermenting-1-related protein kinase 2 (SnRK2). However, there's a lack of research on their structural evolution and functional differentiation across plants. Our study analyzed the phylogenetic, gene structure, homology, and duplication evolution of this complex in 20 plant species. We found conserved patterns in copy number and homology across subfamilies. Segmental and tandem duplications drove the evolution of these genes, while whole-genome duplication (WGD) expanded PYR/PYL/RCAR and PP2C subfamilies, enhancing environmental adaptation. In rice and Arabidopsis, the PYR/PYL/RCAR, PP2C, and SnRK2 genes showed distinct tissue-specific expression and responded to various stresses. Notably, PP2C_1 and PP2C_2 interacted with SnRK2_1 and were crucial for ABA signaling in rice. These findings offered new insights into ABA signaling evolution, interactions, and integration in green plants, benefiting future research in agriculture, evolutionary biology, ecology, and environmental science.

Assessing black soldier fly pupation and survival in lunar regolith simulant: Implications for sustainable controlled habitats on the Moon

Bioregenerative life-support systems (BLSSs) will be crucial for extended space missions and extraterrestrial habitats. The black soldier fly, Hermetia illucens, is recognized for its efficient organic waste consumption, making it well-suited for closed environments like spacecraft. Our study assessed H. illucens adaptability to different substrates, including a lunar regolith simulant, pertinent to future lunar colonization. Remarkably resilient, H. illucens prepupal larvae successfully pupated in all tested substrates, but pupation timing varied, with no-substrate larvae pupating later. Pupal stage duration also differed, particularly with lunar regolith simulant and sand treatments resulting in longer durations. Substrate treatments significantly influenced the number of emerged adults, with lunar regolith simulant yielding more adults than the no-substrate treatment. Additionally, sand and wood shavings treatments produced more adults, highlighting H. illucens adaptability to various substrates, including lunar regolith. These findings are crucial for future BLSSs design. Additionally, H. illucens adaptability to lunar regolith provides insights into life's adaptability in space environments, guiding future experiments on celestial bodies. This study provides critical data on how different substrates, including lunar regolith simulants, influence H. illucens development and survival, advancing BLSSs and ecological science in both space and terrestrial contexts.

Annual Review of Environment and Resources, Volume 48

The Annual Review of Environment and Resources, in publication since 1976, provides authoritative reviews of significant topics within environmental science and engineering, including ecology and conservation science, water and energy resources, atmosphere, oceans, climate change, agriculture and living resources, and human dimensions of resource use and global change. There are 30 articles.

EARTH AND PLANETARY INSIGHTS FOR HUMAN SUSTAINABILITY

Among different human activities having the goal to increase humanity’s quality of life as industrial, agricultural, commercial, transport, touristic ones, also activities connected to Earth and Planetary Insights must be mentioned. In this regard Earth and Planetary Insights especially by exploration, analysis and assessment encompass several scientific fields being an inter-, multi- and transdisciplinary task. The multitude of available approaches and existing applications of mentioned insights are covering almost all human activity fields ranging from main branches of Earth & Planetary Sciences such as for instance Surveying, Geology, in all its aspects, naming here hydrogeology, geotechnics, geophysics etc., Ecology and Environmental Sciences by considering relevant environmental elements such as air, water, soil, oceans, forests, as well as potential environmental impacts because of human activities such as environmental pollution and climate change, coming to Green, Nano- and Space Technologies, as well as to the use of renewable energy resources, all of them being interconnected by modern Management Tools. Space activities must be mentioned in the context of designing new technologies for researching our planet and Outer Space with its many celestial bodies, what means activities for planetary exploration. On the other side using space activities for getting human sustainability also means setting up regional and global emergency programs to support disaster response operations through the provision of satellite data being oriented to reduce disaster risks. With the vision of getting Earth and Planetary Insights for improving humanity quality of life, holistic thinking is per-se required, and in this context connected chances and challenges will be debated with the goal of assuring human sustainability. Developments on global level have emphasized that it depends on our mutual work and cooperation to prevent the increasing processes of current resources consumption from compromising the ability of future generations to meet their own needs.

A fRAmework of the DetermInants of Arts aNd Cultural Engagement (RADIANCE): integrated insights from ecological, behavioural and complex adaptive systems theories.

Arts and cultural engagement (ACEng) is ubiquitous across every human culture since palaeolithic times, but in contemporary society, ACEng is unevenly distributed, demographically, socio-economically, geographically and politically. But what are the "determinants" of ACEng (i.e., the facilitators or barriers to people's engagement) and how can they be optimised? Despite a large body of theory and evidence on individual determinants, this work has largely occurred in disciplinary silos, which has led variously to contrasting discourses and approaches, criticism, and inconsistent findings. What we lack is a rigorous comprehensive understanding of these determinants (both those already theorised and those that have been little recognised as determinants to date) that goes beyond descriptively showing inequalities, instead explaining why these inequalities exist and how they can be overcome. This paper explores the currently recognised determinants of ACEng, and existing theoretical approaches to these determinants. Drawing on the theoretical bases of ecological systems theory, ecosocial theory and complex adaptive systems science, we conducted a review and iterative theorising process. We propose a new theoretical framework of the determinants of arts and cultural engagement (RADIANCE) developed through cross-disciplinary literature reviewing, domain mapping, and consensus building. Overall, we identified 35 different factors that can act as determinants of ACEng across micro, meso, exo, macro and chrono levels. We broadly categorised these as social (i.e. a primary feature being the interaction of people), tangible (i.e. a primary feature involving physical assets or resources or the production of physical assets), and intangible (i.e. constructs that do not have a primary physical basis but instead have a virtual or imaginary basis). The relevance and implications of this framework for broader research, policy, and practice and case studies of it in use are presented.

Understanding the roles of economy and society in the relative risks of zoonosis emergence from livestock.

The emergence of zoonotic infections that can develop into pathogens of pandemic potential is a major concern for public health. The risks of emergence and transmission relate to multiple factors that range from land use to human-non-human animal contacts. Livestock agriculture plays a potentially significant role in those risks, shaping landscapes and providing hosts that can act as the source or amplifiers of emergent pathogens. The relative risks will be contingent upon the nature of those systems, with comparisons often made between intensive, indoor, biosecure systems and more extensive, outdoor, insecure systems. Microbiological, ecological and veterinary sciences provide useful entry points in specifying and modelling some of the relative risks. Yet, they often do so with little regard for social science inputs and by making assumptions about social and economic conditions. In this article, we respond to recent analyses of relative risks by raising the importance of social and economic drivers of risk. We chart social science insights and research that materially alter the zoonotic risks associated with livestock production. Our purpose is to emphasize the requirement for full appreciation of the social, economic and political components of zoonotic and pandemic risk.

Razumijevanje vedske ekoduhovnosti kroz prizmu etike okoliša

Eco–spiritualism is not a new idea; in fact, it has a long history in the Vedic tradition. ‘Vasudhaiva Kuṭumbakam’ in the mantra of Mahā–Upaniṣad of the Sāmaveda tradition presents us with a thought–provoking message, namely, that every being or entity on this earth is one family [अयं बन्धुरयं नेति गणना लघुचेतसाम् ।उदारचरितानां तु वसुधैव कुटुम्बकम् ॥७१॥]. In the Vedic civilization the realm of ethical thinking was extensive. The Vedic science of ecology addresses eco–spiritualism from the perspective of the cosmological and the ontological unity of nature. However, the ethics of natural laws, such as ṛta, satya and dharma, plays a very vital role in the human being’s environmental actions. Firstly, this paper intends to trace and identify the ecological divinity of the Vedas. Secondly, the paper shall endeavour to apply and evaluate ancient scriptures and their understanding of the environment in terms of its intrinsic value and its relation to human beings. We conclude with the discussion on the problems of eco–spiritualism in the contemporary world.

A dataset of vegetation net primary productivity at 250-meter spatial resolution in the Three-River Headwaters Region of Qinghai Province from 2000 to 2018

Net primary productivity (NPP) is a fundamental indicator quantifying photosynthetic production in ecology. With the development of ecosystem process simulation and satellite remote sensing technology, NPP is widely applied to exploring long-term spatiotemporal dynamics and underlying mechanism in terrestrial ecosystems with high spatial heterogeneity. Using the remote sensing ecological process coupling model GLOPEM-CEVSA and incorporating meteorological data interpolated from 2000 to 2018 the remote sensing-based vegetation photosynthetically active radiation absorption (FPAR) data, we obtained a dataset of vegetation net primary productivity at 250-meter spatial resolution for the Three-River Headwaters Region of Qinghai Province from 2000 to 2018. The dataset was made accessible to the public through the National Data Center for Ecological Sciences. The data sharing is expected to provide reliable scientific data to support for the study of spatial and temporal changes and the decision making related to sustainable development in the region.

Similarity network aggregation for the analysis of glacier ecosystems

AbstractThe synthesis of information deriving from complex networks is a topic receiving increasing relevance in ecology and environmental sciences. In particular, the aggregation of multilayer networks, that is, network structures formed by multiple interacting networks (the layers), constitutes a fast‐growing field. In several environmental applications, the layers of a multilayer network are modeled as a collection of similarity matrices describing how similar pairs of biological entities are, based on different types of features (e.g., biological traits). The present paper first discusses two main techniques for combining the multi‐layered information into a single network (the so‐called monoplex), that is, similarity network fusion and similarity matrix average (SMA). Then, the effectiveness of the two methods is tested on a real‐world dataset of the relative abundance of microbial species in the ecosystems of nine glaciers (four glaciers in the Alps and five in the Andes). A preliminary clustering analysis on the monoplexes obtained with different methods shows the emergence of a tightly connected community formed by species that are typical of cryoconite holes worldwide. Moreover, the weights assigned to different layers by the SMA algorithm suggest that two large South American glaciers (Exploradores and Perito Moreno) are structurally different from the smaller glaciers in both Europe and South America. Overall, these results highlight the importance of integration methods in the discovery of the underlying organizational structure of biological entities in multilayer ecological networks.

Mechanistic exploration of Perfluorooctanoic Acid-Induced Hen egg white lysozyme aggregation at physiological Conditions: Spectroscopic and thermodynamic insights

Perfluoroalkyl substances (PFASs) have garnered attention in various scientific fields for their harmful effects on biological systems, including the endocrine, immune, and nervous systems. While research has delved into PFAS-protein binding, their impact on protein aggregation remains uncharted. In this study, we investigated the effect of perfluorooctanoic acid (PFOA) on the aggregation of Hen Egg White Lysozyme (HEWL), a model protein known to aggregate under harsh conditions. We uncovered compelling insights by employing an array of spectroscopic, computational and thermal techniques. Isothermal titration calorimetry (ITC), molecular docking, and fluorescence spectroscopy reveal strong PFOA-HEWL interactions via hydrogen bonding, hydrophobic forces, and ionic interactions. Moreover, techniques like synchronous fluorescence spectroscopy, circular dichroism, and FTIR demonstrates that PFOA induces substantial conformational changes in HEWL, profoundly affecting its secondary structure. Increased PFOA concentrations have been observed to lead to HEWL aggregation under physiological conditions (pH 7.4 and room temperature), verified through various assays and imaging techniques. This is the first comprehensive exploration of PFOA’s influence on protein aggregation. Our findings provide valuable insights into the health risks of PFOA exposure from a protein aggregation perspective, advancing our knowledge in environmental ecology, toxicology, pathology, and life sciences.

Long-term memory on popularity dynamics: insights from the Billboard Hot 100 chart

This study delves into the dynamics of popularity as a crucial aspect of population dynamics, drawing from ecology and social science literature. The focus is on constructing an accurate model for understanding the spread of novelty, memes, and influences within human society, particularly through online platforms such as YouTube, Twitter, and Amazon. Traditional models, based on logistic and similar nonlinear differential equations, have shown limitations in long-term prediction accuracy, partially due to unexplained deviations. Recent research suggests the significance of long-term memory effects on popularity, characterized by a power-law response function, a phenomenon particularly evident in the realm of online mass media. Our research analyzes the Billboard Hot 100 chart, a comprehensive dataset of music popularity spanning several decades, to examine these dynamics. By integrating logistic growth with a power-law decaying long-term memory model, we demonstrate that the trajectory of popularity rankings is predominantly influenced by initial popularity levels and the strength of memory effects. Our findings reveal the pivotal role of long-term memory and the extent of initial popularity in shaping popularity dynamics over time. The study underscores the impact of mass media evolution and the differential effects of spreading mechanisms and accumulated popularity on these dynamics, particularly when long-term memory is a factor. This work contributes to a deeper understanding of the mechanisms driving popularity and its long-term trends in the digital age.

Study of Using a Phyto-nanosynthesis of Silver and Portulaca Oleracea Plant Extracts in Petroleum Spots Treatment

Petroleum spots has become a major global problem not only in terms of its increase, but also how it is treated, recycled or utilized. It contains suspended and dissolved solids, hydrocarbons and many types of organic matter and heavy metals. The reuse of petroleum spots faces the problem of removing organic pollutant compounds before discharging them into any natural stream. in this study, natural nano –coagulant material was used and their efficiency in removing turbidity, Total Organic Carbon (TOC) and Chemical Oxygen Demand (COD) from petroleum spots were compared. The study was conducted in the laboratories of the Ecology Sciences Department, University of Kufa, Iraq in 2022. By synthesizing Phyto-nanosilver as a Phyto-nano silver from Leaves of Portulaca oleracea plant extracts used to reduce turbidity and organic pollutants of the petroleum spots. Jar test experiments showed that 0.5 mg / L Phyto-nanosilver dose can remove 95.5 % of (COD), 87.3% of TOC and 85.2 % from turbidity. Also, removal of P. oleracea plant extracts in the 1 and 0.5 mg/L dose can removed turbidity, COD and TOC content of 91.9%, 87.5 % and 82.4% respectively of the petroleum spots. Moreover, when using the nano-sliver only, removal of TOC, COD, and turbidity would reach 75.3%, 80.4%, and 81.3 %, respectively. The results of the research showed the efficiency of Phyto-nano silver materials in treating and depositing pollutants without harming the environment.

Spatial distribution patterns and drivers of above- and below- biomass in Chinese terrestrial ecosystems

Unraveling the dynamics of the global carbon cycle and assessing the sustainability of terrestrial ecosystems are critically dependent on a comprehensive understanding of vegetation biomass. This exploration delves into the pivotal role of biomass within vegetation communities, emphasizing its impact on ecosystem health, productivity, and community structure development. These insights are invaluable for advancing ecological science and conservation efforts. The synthesis of aboveground (AGB) and belowground (BGB) biomass data from 4485 and 3442 locations across China, respectively, collates a wide range of published sources. Integrating this extensive dataset with environmental parameters and applying advanced machine learning techniques facilitated an in-depth analysis of AGB and BGB spatial patterns within China. Techniques such as variance decomposition analysis and piecewise structural equation modeling were employed to dissect the factors contributing to the spatial variability of vegetation biomass. Significant spatial heterogeneity in biomass distribution was uncovered, with vegetation biomass in the northwest markedly lower than in the southern and northeastern regions. It was observed that AGB consistently surpassed BGB. Climatic conditions, soil characteristics, and soil nutrients were found to significantly explain 53 % and 48 % of the total variance in AGB and BGB, respectively. Specifically, solar radiation and soil total nitrogen were identified as critical factors influencing variations in AGB and BGB. The findings offer profound contributions to the understanding of the global carbon balance and the evaluation of terrestrial ecosystems sustainability. Moreover, they provide essential insights into the ecosystems' response mechanisms to global changes, serving as a fundamental reference for future studies on terrestrial ecosystem carbon cycling and carbon sequestration potentials.

Socio-environmental balance: How environmental conflicts can support the climate-security nexus

This article relies on interdisciplinary debates in geography, political ecology and political sciences in order to explore how interpretative analyses of environmental conflict can support the climate and security nexus debate. It analyses mining and environmental conflicts in Burkina Faso and mobilises a framework highlighting the co-constitutive relationship between the environment and human societies. From this perspective, environmental alterations are considered a central and multicausal factor that can lead to a profound change in social and political structures and thus lead to conflicts. This article will first contextualise mining development, environmental conservation and armed conflict in Burkina Faso before reviewing the literature on climate change, environment and conflicts and describing the conceptual and methodological framework. Then, it addresses the case study of four large-scale mining sites in Burkina Faso. Finally, the last subsection explains how this case study can enrich the climate and security debate with an interpretative understanding.