Ecological Implications Research Articles

Awareness and Understanding of Climate Change for Environmental Sustainability Using a Mix-Method Approach: A Study in the Kathmandu Valley

Climate change is a global phenomenon having wide-ranging social, economic, ecological, and environmental sustainability implications. This study assesses climate change awareness, understanding, causes, mitigation measures, and practices among residents of the Kathmandu Valley through a mixed-method approach. Quantitative surveys with 433 respondents and four Focus Group Discussions (FGDs) are conducted with diverse demographics. Descriptive statistics is used to summarize quantitative data, and the chi-square (χ2) test is used to measure the associations between awareness, understanding, causes, mitigation measures, and practices among various demographics. The analysis shows that respondents frequently link climate change to extreme weather events, particularly flooding, severe hot and cold waves, and changes in rain precipitation patterns. Furthermore, the respondents identify deforestation, industrialization, and fossil fuels as the primary causes, with mitigation strategies such as afforestation, recycling waste, and use of renewable energies for long-term environmental sustainability. Similarly, the survey analysis also revealed that greenhouse gases like carbon dioxide and methane are major drivers of climate change; individuals, industries, and governments are held accountable for climate change with industries as key polluters. Furthermore, individuals are self-aware to adopt sustainable practices, and the government can play a vital role through policies promoting renewable energy, afforestation, and waste management, alongside raising awareness. Other highlights of the analysis have been raising voices of collective action at all levels, which is crucial to mitigate the impact of climate change. The study also addresses the gaps in comprehensive climate literacy and underscores the need for targeted educational initiatives to foster informed climate actions within the community. Likewise, the study brings the findings that policymakers should prioritize inclusive engagement strategies, ensuring that climate policies and adaptation programs are accessible, particularly to those who are less represented in environmental discourse, such as older adults and unschooled individuals.

Type IV Pili in Thermophilic Bacteria: Mechanisms and Ecological Implications.

Type IV pili (T4P) machinery is critical for bacterial surface motility, protein secretion, and DNA uptake. This review highlights the ecological significance of T4P-dependent motility in Thermus thermophilus, a thermophilic bacterium isolated from hot springs. Unlike swimming motility, the T4P machinery enables bacteria to move over two-dimensional surfaces through repeated cycles of extension and retraction of pilus filaments. Notably, T. thermophilus exhibits upstream-directed migration under shear stress, known as rheotaxis, which appears to represent an adaptive strategy unique to thermophilic bacteria thriving in rapid water flows. Furthermore, T4P contributes to the capture of DNA and phages, indicating their multifunctionality in natural environments. Understanding the T4P dynamics provides insights into bacterial survival and evolution in extreme habitats.

Extreme heat prediction through deep learning and explainable AI.

Extreme heat waves are causing widespread concern for comprehensive studies on their ecological and societal implications. With the ongoing rise in global temperatures, precise forecasting of heatwaves becomes increasingly crucial for proactive planning and ensuring safety. This study investigates the efficacy of deep learning (DL) models, including Artificial Neural Network (ANN), Conolutional Neural Network (CNN) and Long-Short Term Memory (LSTM), using five years of meteorological data from Pakistan Meteorological Department (PMD), by integrating Explainable AI (XAI) techniques to enhance the interpretability of models. Although Weather forecasting has advanced in predicting sunshine, rain, clouds, and general weather patterns, the study of extreme heat, particularly using advanced computer models, remains largely unexplored, overlooking this gap risks significant disruptions in daily life. Our study addresses this gap by collecting five years of weather dataset and developing a comprehensive framework integrating DL and XAI models for extreme heat prediction. Key variables such as temperature, pressure, humidity, wind, and precipitation are examined. Our findings demonstrate that the LSTM model outperforms others with a lead time of 1-3 days and minimal error metrics, achieving an accuracy of 96.2%. Through the utilization of SHAP and LIME XAI methods, we elucidate the significance of humidity and maximum temperature in accurately predicting extreme heat events. Overall, this study emphasizes how important it is to investigate intricate DL models that integrate XAI for the prediction of extreme heat. Making these models understood allows us to identify important parameters, improving heatwave forecasting accuracy and guiding risk-reduction strategies.

Industrial development and benefit sharing of mountain agriculture: The Tartary buckwheat (Fagopyrum tataricum Gaertn.) industry in Southwest China

In the context of corporate-led agricultural industrialization, the agricultural systems in the mountainous areas of Southwest China are undergoing significant transformations, profoundly impacting the local agroecological environment and farmers’ livelihoods. This study aims to investigate how the “company + farmer” model influences the cultivation of buckwheat in the Liangshan Yi region in Southwest China. The study hypothesizes that while this model provides market opportunities for farmers, it also marginalizes them from equitably benefiting from industrial growth, leading to the abandonment of traditional crop production and negative impacts on the local agroecological environment and food culture. Drawing on anthropological fieldwork, this study gathers qualitative data from participant observation and interviews to analyze the socioeconomic and ecological implications of these changes. The findings revealed that the push for agricultural industrialization has resulted in the replacement of traditional food crops, including buckwheat, with cash crops, fostering a monoculture system that undermines biodiversity and local food security. The study concludes that future rural development efforts must prioritize the cultural and ecological roles of traditional farming communities and promote a farmer-centered, diversified agricultural production system.

Microbial community structure is affected by phage-resistance associated increases in host density

Lytic bacteriophages (‘phages’) can limit bacterial densities and shape community structure, either directly through lysis or indirectly through costs to resistance. However, phages have also been reported to have no, and in some cases even positive, effects on host densities. Here, we investigate the mechanisms behind an increase in host density in Variovorax sp. populations following a fixation of resistance that was maintained after phage extinction. Our results demonstrate that the density increase was a genetic trait coinciding with resistance emergence. Growth curves showed that phage resistance shifted population growth curves such that density was higher in the death phase. This density-increasing effect of resistance had important implications for community structure with phage-resistant Variovorax decreasing the density of a conspecific. That resistance to lytic phage can increase host densities has implications for wider ecology and phage therapy, where lytic phages are presumed to have negative effects on their hosts.

Advancing the Spatiotemporal Dimension of Wildlife-Pollution Interactions.

Chemical pollution is one of the fastest-growing agents of global change. Numerous pollutants are known to disrupt animal behavior, alter ecological interactions, and shift evolutionary trajectories. Crucially, both chemical pollutants and individual organisms are nonrandomly distributed throughout the environment. Despite this fact, the current evidence for chemical-induced impacts on wildlife largely stems from tests that restrict organism movement and force homogeneous exposures. While such approaches have provided pivotal ecotoxicological insights, they overlook the dynamic spatiotemporal interactions that shape wildlife-pollution relationships in nature. Indeed, the seemingly simple notion that pollutants and animals move nonrandomly in the environment creates a complex of dynamic interactions, many of which have never been theoretically modeled or experimentally tested. Here, we conceptualize dynamic interactions between spatiotemporal variation in pollutants and organisms and highlight their ecological and evolutionary implications. We propose a three-pronged approach-integrating in silico modeling, laboratory experiments that allow movement, and field-based tracking of free-ranging animals-to bridge the gap between controlled ecotoxicological studies and real-world wildlife exposures. Advances in telemetry, remote sensing, and computational models provide the necessary tools to quantify these interactions, paving the way for a new era of ecotoxicology that accounts for spatiotemporal complexity.

First Evidence-Based Record of Common Pandora Pagellus erythrinus on the Turkish Coast of the Black Sea

This paper documents the first evidence-based record of the common pandora (Pagellus erythrinus) from the Turkish coast of the Black Sea, with specimens sampled during 2024. The samples were collected from four locations along the Black Sea coast, from Şile in the west to Perşembe in the east, at depths of 10–17 m in rocky habitats. The study suggests that the common pandora likely entered the Black Sea via the Bosphorus, a natural biological corridor linking the Sea of Marmara and the Black Sea. The recent warming of Black Sea waters and the ongoing process of Mediterraneanization, which facilitates the northward spread of species, are additional contributing factors. Biometric analysis of the specimens revealed total lengths ranging from 20.7 cm to 26.4 cm and body weights between 101.7 g and 248.5 g, confirming that all individuals were mature adults. With their reproductive maturity and high fecundity, the species is well-positioned for successful establishment and expansion in the Black Sea. Proactive monitoring and conservation strategies are recommended to assess the ecological and socio-economic implications of this species, including its potential as a commercially valuable fishery resource in the Black Sea.

Change in sea ice in Hudson Bay, Canada since 2000: An analysis on ice-free periods and maximum concentrations

Sea ice is a climate indicator because of its sensitivity to climate change. This study aims to acknowledge and understand the influence of climate variations on the Hudson Bay area and its possible ecological implications. Results using remote sensing data from ECCC Ice Forecasts and Observations show a continuous decline in yearly average sea ice concentration, accompanied by variations in seasonal ice-free patterns. Intra-year viability has also increased, reflecting a greater instability of annual ice cycles. These findings represent the changes in Hudson Bay’s cryosphere and also help to address the need for consistent monitoring of sea ice and the development of climate change mitigation strategies. This study analyzed changes in patterns of Hudson Bay, Canada’s sea ice concentration variability in relation to temperature fluctuation from the year 2000 onward up to August 2024.

Morphology, development and ecological implications of the dentition of Bajadasaurus pronuspinax

ABSTRACT The associated preservation between dentitions and dentigerous elements is crucial for understanding diverse biological features. Notwithstanding, their fossil record in Sauropoda is relatively seldom, compared to other skeletal elements. Here, the first partially complete dentition including upper and lower teeth in Dicraeosauridae is described, based on Bajadasaurus pronuspinax. This dentition lacks only one upper and two lower functional teeth. The dentigerous elements preserved replacement teeth, which reduce in length and number caudally. Tooth formation times and rates vary within the different elements, with a total mean replacement time of 40.7 days. The functional dentition shows three caudally directed patterns: reduction in size, reduction in curvature, and reduction in the occurrence of wear facets. The functional teeth number mirrors in the occlusal and sagittal planes. The replacement teeth count in Bajadasaurus is lower than the same for other diplodocoids. In this taxon, the tooth-replacement process fits the Zahnreihen with a Z-space-of-two model on the lower dentition, but this model results in a chaotic arrangement of the developmental pattern dorsally, probably due to a replacement mechanism of the whole upper dentition similar to Dicraeosaurus and Apatosaurus. Overall, the dental traits of Bajadasaurus suggest a plausible low-level specialist-feeding ecological niche for this taxon.

Toxicity of Four Commercial Fungicides, Alone and in Combination, on the Earthworm Eisenia fetida: A Field Experiment.

This study investigated the sub-lethal effects of four commercial fungicides-two foliar (Amistar®Xtra and Mirador®) and two ear fungicides (Prosaro® and Icarus®)-applied alone and in combination to wheat crops on caged earthworms (Eisenia fetida). We measured biomarkers that included detoxification responses (glutathione S-transferase, GST), oxidative stress levels (lipid peroxidation, LPO, and catalase, CAT), DNA damage (comet assay), energy reserves (lactate dehydrogenase, LDH), and immune response (lysozyme activity, LYS). The absence of significant differences in catalase and lipid peroxidation levels suggested no oxidative stress due to fungicide exposure. However, the foliar fungicide Amistar®Xtra induced the highest GST activity and DNA fragmentation, suggesting synergistic effects between its active ingredients and undisclosed co-formulants. Similar effects observed with the Amistar®Xtra-Prosaro® mixture confirmed the greater toxicity of Amistar®Xtra. This study provides novel insights into the sub-lethal effects of single and combined commercial fungicides on a standard toxicity test organism, shedding light on the ecological implications of fungicide use in agroecosystems and reinforcing the need for pesticide reduction.

Balancing Poverty Alleviation and Ecosystem Vulnerability Reduction: Implication from China’s Targeted Interventions

The coordination between poverty alleviation and ecological protection is both a crucial requirement and a long-standing challenge for sustainable development. China’s implementation of a targeted poverty alleviation strategy has completed the task of eliminating extreme poverty. However, the evaluation of the corresponding ecosystem changes in the entire poverty-alleviated areas is still insufficient. This study investigated the spatiotemporal changes in ecosystem vulnerability across China’s 832 national poverty-stricken counties from 2005 to 2020. A habitat–structure–function framework was applied to develop an evaluation index, along with a factor analysis of environmental and socio-economic indicators conducted through the Geodetector model. Finally, the implications of China’s practices to balance poverty alleviation and ecological protection were explored. The results show that ecosystem vulnerability decreased from 2005 to 2020, with an even greater decrease observed after 2013, which was twice the amount of the decrease seen before 2013. The post-2013 changes were mainly brought about by the enhancement of the ecosystem function in critical zones such as the Qinghai–Tibet Plateau Ecoregion, Yangtze River and Sichuan–Yunnan Key Ecoregion, and Yellow River Key Ecoregion. From 2013 to 2020, the influence of the gross domestic product (GDP) surpassed that of other factors, playing a significant positive role in diminishing ecosystem vulnerability in the three regions mentioned. The results suggest that China’s poverty-alleviated areas have found a “win–win” solution for poverty alleviation and ecological protection, that is, they have built a synergistic mechanism that combines government financial support with strict protection policies (e.g., more ecological compensation, eco-jobs, and ecological public welfare positions for poor areas or the poor). These findings elucidate the mechanisms behind China’s targeted poverty alleviation outcomes and their ecological implications, establishing a practical framework for coordinated development and environmental stewardship in comparable regions.

Ecological, evolutionary, and management implications of sugarbeet cropping systems with three transgenic herbicide resistance traits

Abstract A three-way transgenic sugarbeet cultivar, engineered for resistance to glyphosate, glufosinate, and dicamba (referred to as ‘triple-stacked,’ henceforth), is anticipated to be commercialized by mid-2020s. While offering potential benefits for growers facing glyphosate resistance, two of three herbicides (dicamba and glyphosate) to be utilized with triple-stacked sugarbeet (Beta vulgaris L.) have previously been used on major weeds in western United States cropping systems, raising concerns about pre-existing resistance to these active ingredients. We conducted a field survey in sugarbeet-growing counties of South-East Montana and North-West Wyoming in fall 2021, prior to the sugarbeet harvest. We collected kochia [Bassia scoparia (L.) A. J. Scott], redroot pigweed (Amaranthus retroflexus L.), and common lambsquarters (Chenopodium album L.) populations and screened them for glyphosate, glufosinate, and dicamba resistance in greenhouse conditions. Our results showed two-way resistance (glyphosate and dicamba) in 32% of B. scoparia populations and 78% populations of C. album with reduced susceptibility to glyphosate. Additionally, we conducted a greenhouse experiment to assess the emergence patterns of collected populations. Phylogenetically closely related B. scoparia and C. album showed higher resemblance in emergence pattern than distant relative A. retroflexus. While the majority of B. scoparia and C. album populations emerged in <20 day(s) (d) [time required to reach 90% emergence (E 90 ) < 20 d], A. retroflexus populations required >30 d to reach E 90 . Widespread glyphosate and dicamba resistance in B. scoparia populations raises concerns about the long-term feasibility of a triple-stacked sugarbeet cultivar. Furthermore, the delayed emergence of A. retroflexus may enable it to evade early-season weed management.

The role of algae in structuring reef communities: innovative monitoring and ecological insights within a Mediterranean conservation priority area

The Mediterranean Sea is a “sea under siege”, facing numerous anthropogenic pressures leading to the spread of invasive species and the degradation of reefs, particularly the reduction of habitat-forming macroalgae to turf algae or sea urchin barrens. The coastal waters of Corsica, often considered as a “reference state” due to their lower human impact, have not been thoroughly studied with regard to infralittoral reef communities. This study aimed to characterize these communities and identify their biotic and abiotic drivers through an innovative monitoring protocol (VIT-Reef). From 2019 to 2021, we monitored infralittoral reef communities at 59 sites between 15 and 35 m depth within and adjacent to three MPAs, using innovative rapid assessment dive surveys for 74 benthic taxa. Our results highlighted vertical zonation in reef communities, in particular the depth extent of photophilic algae and the emergence of pre-coralligenous communities. Important ecological implications of taxa covariation were discussed, such as the negative relationship between canopy-forming macroalgae and the invasive algae, Caulerpa cylindracea. Notably, geographical contrasts were observed along northern, southern and western MPAs, primarily influenced by algal community changes. Cystoseira (sensu lato) forests were identified as the climax state on western reefs, while northern and southern reefs showed significant cover of Dictyota spp. and crustose corallines respectively, with concerning levels of Caulerpa cylindracea in deeper southern reefs. Our results underscored the structuring role of Cystoseira spp. forests and the effects of light, nutrients and Posidonia oceanica meadows extending into the reefs. This study highlighted the role of algae in structuring reef communities and will contribute to establish a baseline for conservation planning and predicting future changes in these high priority infralittoral communities.

YOLOv8 forestry pest recognition based on improved re-parametric convolution.

The ecological and economic impacts of forest pests have intensified, particularly in remote areas. Traditional pest detection methods are often inefficient and inaccurate in complex environments, posing significant challenges for effective pest management. Enhancing the efficiency and accuracy of pest detection under resource-limited conditions has thus become a critical issue. This study aims to address these challenges by proposing an improved lightweight forestry pest detection algorithm, RSD-YOLOv8, based on YOLOv8. To improve the performance of pest detection, we introduced several modifications to the YOLOv8 architecture. First, we proposed RepLightConv to replace conventional convolution in HGNetV2, forming the Rep-HGNetV2 backbone, which significantly reduces the number of model parameters. Additionally, the neck of the model was enhanced by integrating a slim-neck structure and adding a Dyhead module before the output layer. Further optimization was achieved through model pruning, which contributed to additional lightweighting of the model. These improvements were designed to balance detection accuracy with computational efficiency, particularly for deployment in resource-constrained environments. The experimental results demonstrate the effectiveness of the proposed RSD-YOLOv8 model. The model achieved a Map@0.5:0.95(%) of 88.6%, representing a 4.2% improvement over the original YOLOv8 model. Furthermore, the number of parameters was reduced by approximately 36%, the number of operations decreased by 36%, and the model size was reduced by 33%. These improvements indicate that the RSD-YOLOv8 model not only enhances detection accuracy but also significantly reduces computational burden and resource consumption. The lightweight technology and architectural improvements introduced in this study have proven effective in enhancing pest detection accuracy while minimizing resource requirements. The RSD-YOLOv8 model's ability to operate efficiently in remote areas with limited resources makes it highly practical for real-world applications. This advancement holds positive implications for agroforestry ecology and supports the broader goals of intelligent and sustainable development. Future work could explore further optimization techniques and the application of this model to other domains requiring lightweight and accurate detection systems.

Differentiated fatty acid allocation of Daphnia magna helped to maintain their population under food quality deterioration.

Polyunsaturated fatty acids (PUFAs) are vital to the physiological functioning of crustacean zooplankton. However, cyanobacteria blooms frequently lead to PUFA deficiencies, which poses a substantial challenge to population fitness. Therefore, we hypothesize that D. magna adapt to PUFA-deficient conditions by prioritizing PUFA allocation to somatic growth, and then to offspring during reproduction to ensure population persistence. To test this hypothesis, we applied (compound-specific) 13C labeling to compare the turnover of total carbon and certain groups of fatty acids in Daphnia magna fed with Scenedesmus bijuba for 6 days and then switching to a diet of 13C labeled Microcystis wesenbergii for 6 days (with food quality deterioration) or to a diet of 13C-labeled Scenedesmus (without food quality deterioration), respectively. Fatty acid profiles of D. magna mothers and offspring were also analyzed to reveal their PUFA allocation strategies. Life table parameters from D. magna-feeding Scenedesmus switching to Microcystis were compared with D. magna fed with only Scenedesmus or Microcystis to reveal the effect of PUFA allocation on D. magna performance. Our results showed that with food quality deterioration, D. magna exhibited a significantly lower PUFA and carbon turnover and higher offspring: mother ratios in their PUFA contents. Despite this reduced reproduction, the D. magna switching diets showed no significant different intrinsic increasing rate of populations with those fed only Scenedesmus. Meanwhile, the D. magna switching diets performed significantly better than D. magna fed only Microcystis. These results suggest that differential fatty acid allocation of consumers may serve as an adaptive strategy for population maintenance in food quality deterioration and provide ecological implications with cyanobacterial bloom management and Daphnia reproductive plasticity, which needs further explorations.

Impacts of Mechanical Injury on Volatile Emission Rate and Composition in 45 Subtropical Woody Broad-Leaved Storage and Non-Storage Emitters.

Biogenic volatile organic compounds (BVOCs) significantly impact air quality and climate. Mechanical injury is a common stressor affecting plants in both natural and urban environments, and it has potentially large influences on BVOC emissions. However, the interspecific variability in wounding-induced BVOC emissions remains poorly understood, particularly for subtropical trees and shrubs. In this study, we investigated the effects of controlled mechanical injury on isoprenoid and aromatic compound emissions in a taxonomically diverse set of 45 subtropical broad-leaved woody species, 26 species without and in 19 species with BVOC storage structures (oil glands, resin ducts and glandular trichomes for volatile compound storage). Emissions of light-weight non-stored isoprene and monoterpenes and aromatic compounds in non-storage species showed moderate and variable emission increases after mechanical injury, likely reflecting the wounding impacts on leaf physiology. In storage species, mechanical injury triggered a substantial release of monoterpenes and aromatic compounds due to the rupture of storage structures. Across species, the proportion of monoterpenes in total emissions increased from 40.9% to 85.4% after mechanical injury, with 32.2% of this increase attributed to newly released compounds not detected in emissions from intact leaves. Sesquiterpene emissions, in contrast, were generally low and decreased after mechanical injury. Furthermore, wounding responses varied among plant functional groups, with evergreen species and those adapted to high temperatures and shade exhibiting stronger damage-induced BVOC emissions than deciduous species and those adapted to dry or cold environments. These findings suggest that mechanical disturbances such as pruning can significantly enhance BVOC emissions in subtropical urban forests and should be considered when modeling BVOC fluxes in both natural and managed ecosystems. Further research is needed to elucidate the relationship between storage structure characteristics and BVOC emissions, as well as their broader ecological and atmospheric implications.

Examining the Spatiotemporal Evolution of Land Use Conflicts from an Ecological Security Perspective: A Case Study of Tianshui City, China

Land use conflicts represent an increasing challenge to sustainable development, particularly in regions undergoing rapid urbanization. This study investigated the spatiotemporal dynamics of land use conflicts and their ecological implications in Tianshui City from 1980 to 2020. The main objectives were to identify patterns of spatial heterogeneity, explore the driving factors behind these conflicts, and analyze their relationship with the ecological risks. The results indicate the following findings. In terms of spatiotemporal heterogeneity, early land use changes were primarily driven by structural factors, such as topography and climate, with a Nugget/Still ratio of <0.30 observed from 1980 to 2000. After 2000, however, stochastic factors, including an average annual urbanization rate increase of 5.2% and a GDP growth rate of 9.1%, emerged as the dominant drivers, as reflected in a Nugget/Still ratio > 0.36. Regarding conflict intensity, high-conflict areas expanded by approximately 1110 square kilometers between 1980 and 2020, predominantly concentrated in fertile agricultural regions such as the Weihe River Basin and urban core areas. Conversely, non-conflict zones decreased by 38.7%. In terms of ecological risk correlation, bivariate LISA cluster analysis revealed a significant spatial autocorrelation between severe land use conflicts and ecological risks (Moran’s I = 0.62, p < 0.01). High-risk clusters in areas transitioning from arable land to built-up land increased by 23% after 2000. Predictions based on the future land-use simulation (FLUS) model suggest that by 2030, high-intensity conflict areas will expand by an additional 16%, leading to intensified competition for land resources. Therefore, incorporating ecological safety thresholds into land spatial planning policies is essential for reconciling the conflicts between development and conservation, thereby promoting sustainable land use transitions.

NDVI-Based Geospatial Analysis of Forest Cover Alterations in Daldali Reserve Forest, Assam, India

Geospatial analytics integrates spatial as well as temporal data with conventional datasets, enabling for the blossoming of visual representations of the data. A Geospatial tool serves a key function in analysing the shifts in land use and land cover (LULC). The study conducts a comprehensive comparative and analytical analysis of Land Use and Land Cover (LULC) changes in Daldali Reserve Forest (RF) from 1994 to 2024 using the Normalized Difference Vegetation Index (NDVI) method. The investigation focuses on the transformation of vegetation cover over three decades, with NDVI maps from 1994, 2009, and 2024 serving as the primary data sources. The NDVI range was classified into five threshold values: below 0 for water bodies, 0 to 0.2 for bare soil, rock, sand, and cloud, 0.2 to 0.3 for shrubs and grassland, 0.3 to 0.5 for sparse vegetation, and above 0.5 for dense vegetation. The analysis reveals significant trends, including a marked decline in dense vegetation, an increase in sparse vegetation and shrub/grassland, and a troubling expansion of bare soil and degraded land. The study identifies both anthropogenic and natural factors as drivers of these LULC changes. Deforestation and land use change, forest fires, climate change, and soil erosion are highlighted as key contributors to the observed degradation. The ecological implications are profound, with potential consequences including biodiversity loss, disruption of ecosystem services, and reduced resilience to climate change. In response to these findings, the study recommends a multifaceted approach to conservation and restoration, including sustainable forest management, reforestation, fire prevention, soil conservation, and the restoration of hydrological balance. Strengthening legal and institutional frameworks, promoting alternative livelihoods for villagers, and enhancing biodiversity conservation efforts are also critical. The study underscores the urgency of collective action by government agencies, non-governmental organizations, research institutions, and local communities to restore the health and vitality of Daldali RF, ensuring its long-term sustainability and continued provision of ecological, economic, and cultural benefits.

Bioconvection in Microalgae: Review of Mathematical Models

Bioconvection can be defined as an aggregation pattern-generating phenomenon characterized by the collective behavior of swimming microorganisms in response to external influences and self-induced fluid flow, and it has attracted significant interest in the study of microalgae. This review aims to provide a comprehensive examination of this phenomenon in a concentrated population of suspended microalgae definable as nonlinear dynamical systems (i.e., generators of spatial and temporal patterns), describing and clarifying the underlying mechanisms, ecological implications, and possible biotechnological applications in different fields for the improvement of bioreactor design for biomass cultivation, wastewater treatment, or bioremediation. The most influential models used to capture the complexity of bioconvection are perused in order to explore the intricate interplay of internal and external influences (biological, physical, and environmental) governing pattern formation dynamics alongside recent advancements in modeling techniques and experimental approaches.

Transformative Climate and Environmental Education for a Just Future

ABSTRACTThis commentary highlights the urgent need to re‐envision climate and environmental education in response to the escalating climate crisis and its far‐reaching social, ecological, and political implications. As young people increasingly express concern for their futures, the authors call for a transformational change in science education that engages with climate change as a complex and pressing issue. To support such transformation, the commentary introduces a new section in the journal Science Education titled “Climate Change and Environmental Education,” providing a platform for empirical research, conceptual inquiries, and policy discourse on education's role in addressing planetary change. This section invites scholarship that expands our understanding of climate change and environmental education through transdisciplinary and justice‐oriented approaches. Key areas of inquiry include learning across spaces, disciplines, and epistemologies, action‐oriented learning through community‐based and participatory approaches, and attending to emotional well‐being while using action to cultivate hope. By advancing these conversations, researchers can critically examine how education fosters the knowledge, agency, and ethical commitments necessary for engaging with the complexities of climate change.