Ecological Biodiversity Research Articles

Incorporating Heterogeneous Interactions for Ecological Biodiversity.

Understanding the behaviors of ecological systems is challenging given their multifaceted complexity. To proceed, theoretical models such as Lotka-Volterra dynamics with random interactions have been investigated by the dynamical mean-field theory to provide insights into underlying principles such as how biodiversity and stability depend on the randomness in interaction strength. Yet the fully connected structures assumed in these previous studies are not realistic, as revealed by a vast amount of empirical data. We derive a generic formula for the abundance distribution under an arbitrary distribution of degree, the number of interacting neighbors, which leads to degree-dependent abundance patterns of species. Notably, in contrast to the fully interacting systems, the number of surviving species can be reduced as the community becomes cooperative in heterogeneous interaction structures. Our study, therefore, demonstrates that properly taking into account heterogeneity in the interspecific interaction structure is indispensable to understanding the diversity in large ecosystems, and our general theoretical framework can apply to a much wider range of interacting many-body systems.

Biodiversity and anthropogenic disturbances predominantly drive carbon sequestration rates across temporal scales in temperate forests

Addressing the escalating challenges of climate change necessitates a comprehensive understanding of the factors influencing carbon sequestration rates (CSRs) in forest ecosystems. Although the impact of various biotic factors, environmental, and anthropogenic factors on CSRs over different time scales is well recognized, their precise roles remain poorly defined. This study aims to clarify the mechanistic relationships between CSRs and these factors in large-scale natural temperate forests in northeastern China. We employed linear mixed-effects models and piecewise structural equation models were to analyze data from 310 vegetation plots, assessing the effects of biotic factors (including multidimensional diversity, structural diversity, and community-weighted mean (CWM) trait values) and abiotic factors (climate, topography, and anthropogenic disturbances) across different forest types and successional stages. Our analysis tested a series of hypotheses to identify the principal drivers of forest CSRs. The results indicate that while functional composition and standard environmental factors such as mean annual temperature and slope are significant, their influence is markedly less than that of biodiversity (encompassing multidimensional and structural diversity) and anthropogenic disturbance (as measured by the Human Modification Index). These findings support the dominance of the niche complementarity theory and the moderate disturbance hypothesis, with their importance increasing over time. Furthermore, this study advocates for forest management strategies that are specifically tailored to the unique characteristics of mixed and dense forests at different stages of succession. By elucidating the complex relationships between ecological variables and CSRs, our findings provide critical insights for the development of effective strategies aimed at optimizing forest carbon sequestration. This study underscores the necessity of integrating sustainable forest management with the conservation of ecological biodiversity.

Functional and phylogenetic β diversities and their link with clustering/overdispersion and uniqueness/redundancy

AbstractIn recent decades, research on biodiversity in community ecology has been marked by the consideration of species' evolutionary histories and functional traits. Among the different spatial levels at which functional or phylogenetic (hereafter FP) diversity can be quantified, the definition of the general concept of between‐community (β) diversity has been given less attention than that of local, within‐community (α) and regional, merged‐community (γ) diversities. Here, we develop a new method for partitioning FP β diversity into elementary components to determine how and why FP β diversity differs from species β diversity, with the latter reflecting only differences in species' abundances between communities. As a reference example, we consider two distinct measures of FP β diversity: Rao's dissimilarity coefficient (Qβ), which expresses the average FP dissimilarity between communities, and its transformation (Eβ), which expresses the effective number of distinct communities. Through analytical partitioning and simulations, we show that Qβ and Eβ are connected differently to typical patterns of community structure. The search for the ecological and evolutionary processes that drive community assembly and the assessment of community resilience and stability have indeed revealed typical community structures: the local clustering of species with similar traits or shared evolutionary histories and the local (α) or regional (γ) presence of functionally or phylogenetically redundant versus unique species. We show that while Qβ and Eβ are both increasing functions of species β diversity and FP γ uniqueness, Qβ increases with FP clustering, while Eβ increases with FP α redundancy. We also show that the component of FP clustering included in Qβ partitioning formula allows the detection of an overall trend of overdispersion or clustering in a dataset without the need to use null models. To facilitate and secure the selection of an index of β diversity for a given study, we call, through our study, for the development of formal and precise definitions for FP β diversity in light of the concepts of clustering versus overdispersion and redundancy versus uniqueness. In particular, we call for further research on when and why FP β diversity should increase with FP clustering.

Source-specific ecological and human health risk analysis of topsoil heavy metals in urban greenspace: a case study from Tianshui City, northwest China.

Soil contamination of heavy metals in urban greenspaces can exert detrimental impacts on ecological biodiversity and the health of inhabitants through cross-media migration-induced risks. Here, a total of 72 topsoil samples were collected from greenspaces in the popular tourist city of Tianshui, ranging from areas with parks, residential, road, industrial and educational soils. The study aimed to evaluate an integrated source-specific ecological and human health risk assessment of heavy metals. Among the analyzed heavy metals, except Cr (mean), all exceeded the local background values by 1.30-5.67-fold, and Hg, Cd, Pb and As were the metals with large CV values. The Igeo and CF results showed Hg, Cd, As and Pb exhibited significantly high pollution levels and were the primary pollution factors. The mean PLI values indicated moderate pollution in educational (2.21), industrial (2.07), and road (2.02) soils but slight pollution in park (1.84) and residential (1.39) greenspaces. The Igeo, CF, and PLI results also revealing that these heavy metals are more likely to be affected by human activity. Four primary source factors were identified based on PMF model: coal combustion (25.57%), agricultural sources (14.49%), atmospheric deposition (20.44%) and mixed sources (39.50%). In terms of ecological risk, the mean IRI values showed considerable risks in educational soils (287.52) and moderate risks in road (215.09), park (151.27) and residential (136.71) soils. And the contribution ratio of atmospheric deposition for park, residential, road, industrial and educational greenspaces were 57.72%, 65.41%, 67.69%, 59.60% and 75.76%, respectively. In terms of human health risk, the HI (below 1) and CR (below 1.00E-04) for adults from soils of all land use types was negligible. However, children have more significant non-carcinogenic and carcinogenic hazards especially in residential soils, the HI (above 1) and CR (above 1.00E-04) revealed the significance of regarding legacy As contamination from coal combustion when formulating risk mitigation strategies in this area. The proposed method for source and risk identification makes the multifaceted concerns of pollution and the different relevant risks into a concrete decision-making process, providing robust support for soil contamination control.

Caracterización de experiencias significativas de educación ambiental en Colombia: Un análisis descriptivo de la identificación de tendencias para el desarrollo sustentable

The current environmental crisis, resulting from humanity's subjugation and domination of nature, has significantly contributed to the decline of ecological biodiversity worldwide. In the case of Colombia, the main causes of biodiversity loss include land-use changes, urbanization, among others. This underscores the urgent need to strengthen environmental education (EE) in the country to promote a sustainable environmental culture in harmony with nature. Accordingly, this research aims to characterize environmental education experiences in Colombia based on the database "Experiencias significativas de Educación Ambiental – Listado Minambiente" Data processing was conducted using the statistical software STATA, with the goal of identifying educational trends related to environmental issues at the national level. The results reveal progress in the field of EE, highlighting a higher proportion of initiatives that adopt a naturalistic teaching model. Likewise, there is a prevalence of institutional initiatives over community ones. The results suggest that community initiatives tend to align with a systemic teaching model, while institutional initiatives prioritize the naturalistic perspective. Additionally, it was observed that community participation is sometimes conditioned by sectoral and non-sectoral entities in the country. Finally, the conclusions reaffirm the need for Colombian institutions to continue working on appropriate environmental education indicators that allow for the measurement and dissemination of EE experiences at the national level. Furthermore, the importance of strengthening systemic EE models is emphasized, as they promote the social re-appropriation of the environment through cultural changes.

Uncovering the effect of waterlogging stress on plant microbiome and disease development: current knowledge and future perspectives.

Waterlogging is a constant threat to crop productivity and ecological biodiversity. Plants face multiple challenges during waterlogging stress like metabolic reprogramming, hypoxia, nutritional depletion, reduction in gaseous exchange, pH modifications, microbiome alterations and disease promotion all of which threaten plants survival. Due to global warming and climatic change, the occurrence, frequency and severity of flooding has dramatically increased posing a severe threat to food security. Thus, developing innovative crop management technologies is critical for ensuring food security under changing climatic conditions. At present, the top priority among scientists is to find nature-based solutions to tackle abiotic or biotic stressors in sustainable agriculture in order to reduce climate change hazards to the environment. In this regard, utilizing plant beneficial microbiome is one of the viable nature based remedial tool for mitigating abiotic stressors like waterlogging. Beneficial microbiota provides plants multifaceted benefits which improves their growth and stress resilience. Plants recruit unique microbial communities to shield themselves against the deleterious effects of biotic and abiotic stress. In comparison to other stressors, there has been limited studies on how waterlogging stress affects plant microbiome structure and their functional traits. Therefore, it is important to understand and explore how waterlogging alters plant microbiome structure and its implications on plant survival. Here, we discussed the effect of waterlogging stress in plants and its microbiome. We also highlighted how waterlogging stress promotes pathogen occurrence and disease development in plants. Finally, we highlight the knowledge gaps and areas for future research directions on unwiring how waterlogging affects plant microbiome and its functional traits. This will pave the way for identifying resilient microbiota that can be engineered to promote their positive interactions with plants during waterlogging stress.

Water properties and bottom water patterns in hadal trench environments

Abstract. We examine baseline water properties and bottom water patterns in hadal trench environments across the Southern Ocean, Indian Ocean, and western Pacific. Significant differences are identified in the South Fiji Basin and surrounding the Philippine Sea, primarily due to the movement of cold Lower Circumpolar Deep Water along topographic features, highlighting the importance of a trench's geospatial position. We present the first hydrographic profiles in the Java Trench, warranting further research. Salinity increases with increasing depth for profiles over 10 000 dbar, with potential causes including instrumentation error, internal mixing, and saline pore water expulsion. These hadopelagic variations are crucial for assessing climate change impacts, especially regarding Antarctic Bottom Water. The study underscores the importance of incorporating these adiabatic conditions to gain insights into ecological biodiversity, alongside the indispensable baseline conditions presented, which are crucial for future oceanographic research across multiple disciplines.

Turbulent Characteristics of a Submerged Reef under Various Current and Submergence Conditions

Submerged Reefs (SRs) are a kind of artificial fish habitat that can protect coasts and maintain ecological biodiversity. In this study, the flow field of the SR is simulated by solving a Reynolds-averaged Navier–Stokes equation closed with the Realizable k-ε model based on the finite volume method. The turbulent characteristics of SRs under different inflow velocities and submergences in the vicinity of the SR are analyzed. The wake vorticities are the primary turbulent pattern within and around the SR. The back wake and vorticity are chosen as critical indicators to quantitatively assess the hydrodynamic characteristics induced by the SR. The results show: (1) as the main flow passes through the SR, the upwelling is produced in front of the SR and a large-scale wake region is formed behind the SR which contains a clockwise vortex; (2) the length of the wake region formed behind the SR is positively and linearly correlated with both the inflow velocity and submergence; (3) the dipole-type vorticity patterns are induced within the compartment of the SR, where the area and average value of high vorticity have a positive correlation with the flow velocity and a negative correlation with the submergence, respectively.

Pathogen perception and signaling in plant immunity.

Plant diseases are a constant and serious threat to agriculture and ecological biodiversity. Plants possess a sophisticated innate immunity system capable of detecting and responding to pathogen infection to prevent disease. Our understanding of this system has grown enormously over the past century. Early genetic descriptions of plant disease resistance and pathogen virulence were embodied in the gene-for-gene hypothesis, while physiological studies identified pathogen-derived elicitors that could trigger defense responses in plant cells and tissues. Molecular studies of these phenomena have now coalesced into an integrated model of plant immunity involving cell surface and intracellular detection of specific pathogen-derived molecules and proteins culminating in the induction of various cellular responses. Extracellular and intracellular receptors engage distinct signaling processes but converge on many similar outputs with substantial evidence now for integration of these pathways into interdependent networks controlling disease outcomes. Many of the molecular details of pathogen recognition and signaling processes are now known, providing opportunities for bioengineering to enhance plant protection from disease. Here we provide an overview of the current understanding of the main principles of plant immunity, with an emphasis on the key scientific milestones leading to these insights.

Impact of current anthropogenic activities on Blesbokspruit wetland microbiome and functions

Till present, natural wetlands have been continuously subjected to intensive pollution stress in recent years, mainly because of the rapidly growing industrialization and urbanization that are associated with a myriad of anthropogenic activities and land use practices. These man-made sources of pollution change the chemical properties of the natural wetlands, which in turn alter their microbial ecological biodiversity and functions. For the first time, the impact of the current anthropogenic activities and land use practices on the Blesbokspruit wetland chemical status and their consequential effect on the microbial structure and functions were investigated. Sites of high pollution intensity were identified using geographic information systems mapping (GISMapping) and the wetland microbiome and functional profile were studied through the use of high throughput shotgun metagenomics sequencing analysis. The predominant phyla that stemmed along the Blesbokspruit wetland were found to be Proteobacteria which was more dominant in water (93 %) than in the sediments (89 %), followed by firmicutes which was more abundant in sediments (9 %) than in water (6 %), and Bacteroidetes were relatively low in abundance within both the sediments (2 %) and the overlying water (1 %). The genera Klebsiella (70.4 %–28.2 %), Citrobacter (52.0 %–30.6 %), Escherichia (51.0 %–8.4 %), and Lynsinibacillus (9.3 %–1.5 %) were observed in most water and sediment samples. Within the six polluted sites, Site 2 was found to be the most highly polluted site in the Blesbokspruit wetland with very high COD (900 mg/L), TOC (11.60 mg/L), NO3− (39.74 mg/L), NO2− (12.64 mg/L), PO43 (4.14 mg/L), Fl− (143.88 mg/L), Cl− (145.95 mg/L) concentrations recorded in the water and high levels of TOC (0.37 mg/L), TC (6.92 %), TN (1.82 %), TS (0.53 %) in sediments. The microbial community structure and functions were found to be strongly influenced by the high organic content from the intense agricultural activities and sewage spillages and heavy metals from the mining activities nearby.

EVALUATION OF SPECTRAL INDICES FOR DETECTION OF BURNED AREAS IN AN ENVIRONMENTAL PROTECTION AREA USING SPOT-5 IMAGES

The Cerrado biome has great importance in ecological biodiversity, but deforestation has accelerated in recent decades. The Rio Preto-BA Environmental Preservation Area, known for the high agricultural activity of grains, continually suffers from forest fires and loss of native vegetation. Satellite remote sensing is proposed as an alternative to accurately locate and quantify fire-affected surfaces and their impacts on the landscape. With the recent free availability of SPOT-5 images, it has made it possible to detect burned areas with considerable spatial and spectral resolution. The objective of the present study was to determine the ideal spectral index for detection of the burned area inserted in the APA Rio Preto through two SPOT-5 scenes and the application of the Support Vector Machines (SVM) model. The burned areas detected were submitted to the calculation of five spectral indices, BAI, BAIM, NBR, NDVI and EVI2. The ability of each index to discriminate burned areas was estimated by comparing them with each other using a statistical separability index, SVM regression and accuracy analysis. BAIM was identified as the index with the greatest potential for discriminating burnt areas with maximum separability and classification accuracy above 90%, while the NDVI and EVI2 indices had low performance. It is hoped that these results can be used to evaluate and prioritize monitoring areas, contribute to the implementation of a fire management plan in the APA and to support subsequent studies on fire dynamics in forest systems integrated with advanced computational technologies.

Efficiency of birds as bioindicators for other taxa in mountain farmlands

Biodiversity loss is a global issue, particularly in mountain regions, where land-use/land-cover and climate change dramatically impact on species and communities. Sound ecological research and up-to-date information on biodiversity are needed to support conservation efforts. However, this information is often difficult and costly to obtain. Therefore, bioindicators serve as surrogates to provide information on the entire biocenosis. Birds are considered excellent bioindicators as they occupy different ecological niches and trait spaces.We present a study about the efficiency of birds as bioindicators for the diversity of other taxa in a mountain region in the Central Alps. We surveyed bird communities at 115 sites across a gradient of different grasslands and crops and compared them with the diversity of other taxa (bats, butterflies, grasshoppers, arachnids, and vascular plants). We aimed to identify indicator bird species for grasslands and crops, to assess cross-community concordance between birds and other taxa, and to model the efficiency of bird indices and indicator species as bioindicators of the diversity across habitat types and taxa.We identified indicator bird species for different grassland and crop types and found that efficiency of bird indices and single species varied for habitat types and taxa. We highlight the importance of using carefully selected bioindicators in biodiversity monitoring and conservation planning, and the need for an integrated and interdisciplinary approach for biodiversity research. Moreover, by looking at a combination of different indices we can gain a more comprehensive understanding of ecosystem functioning. We also provide a framework for the use of bird-based monitoring programs and bird-derived indices to guide biodiversity conservation, and emphasise the importance of incorporating different bioindicators into biodiversity research and monitoring to provide a more comprehensive understanding of ecological biodiversity patterns and trends.

Application of a structured decision‐making process in cryospheric hazard planning: Case study of Bering Glacier surges on local state planning in Alaska

AbstractSurging glaciers are glaciers that experience rapidly accelerated glacier flow over a comparatively short period of time. Though relatively rare worldwide, Alaska is home to the largest number of surge‐type glaciers globally. However, their impact on the broader socioecological system in the state is both poorly understood and under‐researched, which poses a challenge in developing appropriate sustainability decisions in Alaska. We investigated how the surge patterns of the Bering Glacier in Alaska have potentially devastating effects on the local ecological biodiversity of its watershed via a structured decision‐making analysis of the different possible consequences. Specifically, this analysis was conducted to explore the various outcomes of a Bering Glacier surge particularly if humans have an increased presence near the glacier due to the area potentially becoming a state park. This work explored the benefits of applying a risk and decision analytical framework in a cryosphere context, to better understand the socioeconomic impact of glacier surges. This is a novel approach in which a decision analysis tool was used to better understand an environmental sustainability challenge, offering an innovative method to support the achievement of the United Nations Sustainability Development Goals in Alaska. We therefore emphasise the need for integrated biophysical and socioeconomic analyses when it comes to understanding glacier hazards. Our research highlights the importance of understanding and researching biophysical changes as well as using a structured decision‐making process for complicated hazard planning scenarios, exemplified via glaciated regions in Alaska, in order to create adaptation strategies that are sustainable and encompass the range of possible outcomes.

Nanotechnology, Water Remediation and Sustainability- A Far-Reaching Review and a Broad Scientific and Technological Perspective

The world of science and engineering of sustainability and nanotechnology are in today’s scientific fabric are in the aisles of newer scientific divination. Environmental, energy and socio-economic sustainability are the utmost needs of the hour. In the similar vision, nanotechnology needs to be aligned with diverse areas of natural sciences, applied sciences and engineering sciences. The definition of “sustainability” as described by Dr Gro Harlem Brundtland, former Prime Minister of Norway needs to be re-envisioned, rethought and rejuvenated with the passage of scientific history and time. Human struggles, human scientific and engineering challenges and human impact needs to be rethought as environmental protection and environmental disasters are in the path of immense scientific contemplation. In this paper, the author deeply discusses with verve and validation the integration of nanotechnology and sustainability. Human race today stands in the middle of deep scientific disaster and also scientific contemplation. Loss of ecological biodiversity and frequent environmental disasters are urging the scientific and engineering community to move towards newer scientific innovations and newer environmental engineering tools. Thus the need of a comprehensive treatise in the field of nanotechnology and sustainable development. Nanotechnology has vast and varied applications in the field of environmental pollution control. The author deeply targets these areas of scientific and engineering research endeavor. A newer era in the field of nanotechnology, nano-engineering and sustainability will surely usher in if a concerted effort is taken in the proper implementation of United Nations Sustainable Development Goals and the vision of Brundtland Commission Report. A new generation of scientists and engineers will move towards positive research directions if man and mankind innovates and envisions the basics and fundamentals of environmental engineering science, chemical process engineering, sustainable engineering and nanotechnology.

Predicting land use/land cover changes in the Santchou Wildlife Reserve (Santchou, West-Cameroon) using a CA-Markov model

Over the last three decades, the Santchou Wildlife Reserve (SWR) located in the West region of Cameroon has experienced rapid degradation. Land reclamation and population growth have significantly contributed to meeting the increasing demands for foods and urban development. In this study, Landsat 4–5 Thematic Mapper (TM) images of 1988 and 2005, and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) image of 2022 are firstly used for calculating and analysing area changes and then spatial distribution of land use/land cover changes (LULCC) in the SWR for a time span 1988–2005–2022. Secondly, the spatial distribution of LULCC from 2022 to 2027 and from 2027 to 2032 was simulated using a Cellular Automata (CA)-Markov model that allows to predict future changes and identify the possible patterns of evolution. Results exhibit six major LULC classes including Mountain Forest, Degraded Lowland Forest, Lowland Forest, Degraded Mountain Forest, Built-up Area and Cultivated Land. The overall accuracies of LULC classification reached 89.71‒92.24 %, with Kappa coefficients of 0.87‒0.92. However, the prediction model was validated with an overall good agreement of 90.51 %. In general, two significant patterns of change were evidenced and characterized by the rapid expansion of Cultivated Land from 158.6 to 736.4 ha between 1988 and 2022, and could reach 809.0 ha in 2032, while Built-up Area displays a surface change from 12.4 to 29.3 ha, which is expected to attend 67.3 ha in 2032. Change patterns from the past to the future are also marked by a decline of Mountain Forest (2107.4 to 1594.4 ha), Degraded Lowland Forest (1450.1 to 1024.5 ha) and Degraded Mountain Forest (954.6 to 860.6 ha) at the expense of Lowland Forest (2332.5 to 2659.8 ha). Human activities influenced by socio-economic issues remain the main factor of changes in the SWR. Despite the limitations of the CA-Markov model due to the non-consideration of socio-economic factors, this study appears as a new opportunity to develop effective strategies for managing LULCC and protecting ecological biodiversity in the SWR.

The Entropy of Entropy: Are We Talking about the Same Thing?

In the last few decades, the number of published papers that include search terms such as thermodynamics, entropy, ecology, and ecosystems has grown rapidly. Recently, background research carried out during the development of a paper on "thermodynamics in ecology" revealed huge variation in the understanding of the meaning and the use of some of the central terms in this field-in particular, entropy. This variation seems to be based primarily on the differing educational and scientific backgrounds of the researchers responsible for contributions to this field. Secondly, some ecological subdisciplines also seem to be better suited and applicable to certain interpretations of the concept than others. The most well-known seems to be the use of the Boltzmann-Gibbs equation in the guise of the Shannon-Weaver/Wiener index when applied to the estimation of biodiversity in ecology. Thirdly, this tendency also revealed that the use of entropy-like functions could be diverted into an area of statistical and distributional analyses as opposed to real thermodynamic approaches, which explicitly aim to describe and account for the energy fluxes and dissipations in the systems. Fourthly, these different ways of usage contribute to an increased confusion in discussions about efficiency and possible telos in nature, whether at the developmental level of the organism, a population, or an entire ecosystem. All the papers, in general, suffer from a lack of clear definitions of the thermodynamic functions used, and we, therefore, recommend that future publications in this area endeavor to achieve a more precise use of language. Only by increasing such efforts it is possible to understand and resolve some of the significant and possibly misleading discussions in this area.

Evaluating Informal Science Education Centers in the Southern Appalachians

abstract: The southern Appalachian region is a hotspot of ecological biodiversity that is under increasing threat from climate change and rapid population growth. We posit that informal science education is uniquely adapted to foster environmental stewardship in the region, but the current state of informal science education within the southern Appalachians is poorly understood. We reviewed current informal science education centers (ISECs), which we define as centers for science learning outside of structured curriculum ( n = 166). For each of these centers, we compiled information on geographical location, programs offered, and funding sources. We found large geographic gaps in ISEC coverage that often aligned with low-population, low-income counties. The most common program type in our dataset was field trips, followed by public programming, while research and virtual programming were the least often offered. ISECs that had funding from multiple organizations generally had the most diverse and robust programming.

Real-time biodiversity analysis using deep-learning algorithms on mobile robotic platforms.

Ecological biodiversity is declining at an unprecedented rate. To combat such irreversible changes in natural ecosystems, biodiversity conservation initiatives are being conducted globally. However, the lack of a feasible methodology to quantify biodiversity in real-time and investigate population dynamics in spatiotemporal scales prevents the use of ecological data in environmental planning. Traditionally, ecological studies rely on the census of an animal population by the "capture, mark and recapture" technique. In this technique, human field workers manually count, tag and observe tagged individuals, making it time-consuming, expensive, and cumbersome to patrol the entire area. Recent research has also demonstrated the potential for inexpensive and accessible sensors for ecological data monitoring. However, stationary sensors collect localised data which is highly specific on the placement of the setup. In this research, we propose the methodology for biodiversity monitoring utilising state-of-the-art deep learning (DL) methods operating in real-time on sample payloads of mobile robots. Such trained DL algorithms demonstrate a mean average precision (mAP) of 90.51% in an average inference time of 67.62 milliseconds within 6,000 training epochs. We claim that the use of such mobile platform setups inferring real-time ecological data can help us achieve our goal of quick and effective biodiversity surveys. An experimental test payload is fabricated, and online as well as offline field surveys are conducted, validating the proposed methodology for species identification that can be further extended to geo-localisation of flora and fauna in any ecosystem.

More-than-Human Wellbeing

More-than-Human Wellbeing

Environmental Crimes and Judicial Response in the Context of Bangladesh

The environmental spectrum in Bangladesh is exceedingly vulnerable. The norm of environmental crimes in this country is prolific. Environmental crimes have skyrocketed over the decades and it is an area of increasing concern. This concern is not owing to its globalized nature but these green criminal activities have extensive impacts that are beyond the capacity of the justice system that comprehend and address accordingly. Hence, a question can be raised, How would criminal justice agencies, specifically the global South mitigate these alarming environmental threats? This paper takes Bangladesh's case into account and illustrates a range of examples of anthropogenic activities that are horrendously destroying ecological biodiversity and polluting the green landscape in this country. This paper also reviews these prolific crimes and environmental harms in line with the environmental law, and activities of the law enforcement agencies and environmental agencies in Bangladesh.