Search Results (72)

Long-term sedimentation patterns influence the ecological succession of shallow lakes. However, human-induced impacts can disrupt these processes, leading to prolonged hysteresis. Using historical sedimentation data, we simulated the future terrestrialization of Lake Izunuma-Uchinuma, a Ramsar-listed wetland in Japan. The results indicated that ecotone recovery would take over 150 years, highlighting the strong legacy effects of shoreline vegetation loss. To accelerate restoration, we implemented an integrated approach that combined water-level management with sediment stabilization structures, including fences and coconut mat rolls. Over three years, these interventions successfully restored shoreline sediment accumulation, facilitated the re-establishment of Zizania latifolia (from 328 m² to 1537 m² in Ecotone 1), and improved water quality and waterbird use. Waterbird abundance significantly increased (p < 0.05) in the treated zones, and sediment exposure led to a reduction in COD release, indicating improved substrate conditions. Our results suggest that proactive ecotone restoration strategies, including hydrological regulation and sediment management, are essential in lakes where natural recovery is hindered by long-term sedimentation deficits and water-level changes. This study highlights the importance of integrating these measures to mitigate hysteresis and enhance ecosystem resilience in degraded shallow lakes. Full article

Carbon (C), nitrogen (N), and phosphorus (P) act as pivotal regulators of biogeochemical cycles, steering organic matter decomposition and carbon sequestration in terrestrial ecosystems through the stoichiometric properties of photosynthetic organs. Deciphering their multi-scale spatiotemporal dynamics is central to unraveling plant nutrient strategies and their coupling mechanisms with global element cycling. In the current study, we modeled biogeochemical parameters (C/N/P contents, stoichiometry, and pools) in plant aboveground parts by using the growing mean temperature, total precipitation, total radiation, and maximum normalized difference vegetation index (NDVImax) across nine models (i.e., random forest model, generalized boosting regression model, multiple linear regression model, artificial neural network model, generalized linear regression model, conditional inference tree model, extreme gradient boosting model, support vector machine model, and recursive regression tree) in Xizang grasslands. The results showed that the random forest model had the highest predictive accuracy for nitrogen content, C:P, and N:P ratios under both grazing and fencing conditions (training R² ≥ 0.61, validation R² ≥ 0.95). Additionally, the random forest model had the highest predictive accuracy for C:N ratios under fencing conditions (training R² = 0.84, validation R² = 1.00), as well as for C pool and P content and pool under grazing conditions (training R² ≥ 0.62, validation R² ≥ 0.90). Therefore, the random forest algorithm based on climate data and/or the NDVImax demonstrated superior predictive performance in modeling these biogeochemical parameters. Full article

Salt marshes are vital coastal ecosystems, increasingly threatened by rising sea level and human pressures, that provide essential services, including coastal protection, habitat support, and carbon sequestration. This study examines the effectiveness of different eco-engineering structures in restoring salt marshes in the Mondego Estuary, Portugal, by assessing their impacts on benthic macroinvertebrate communities as bioindicators of ecosystem health. The experimental design included five experimental cells: wood palisade (Fence), geotextile fabric (Geotextile), geotextile bags filled with sand (Bags), a cell with autochthonous vegetation (Plants), and a Control cell with bare soil. Monitoring took place from 2019 to 2021, with both before and after intervention sampling to evaluate species composition, biomass, and density. Key ecological indices, such as the AZTI’s Marine Biotic Index (AMBI), Shannon-Wiener Diversity, and Pielou’s Evenness, were calculated alongside measurements of environmental variables. The results indicated minimal impacts on biodiversity, with observed variations primarily attributed to seasonal dynamics. While the wood palisade enhanced species richness and density, geotextile provided better community stability. The findings emphasize the importance of long-term monitoring, stakeholder engagement, and sustainable use of materials to optimize restoration efforts and better inform coastal management strategies in the face of climate change. Full article

The traditional ecological reclamation measurements and assessments for the grassland areas damaged by open-pit mining often fall short in revealing the dynamics of plant communities affected by environmental filters during reconstruction, making reclamation efforts crucial. The trait-based community framework has been widely applied due to its great potential to predict the restoration process and provide insight into its mechanisms, but how the traits and environmental factors interact to form communities over time is still uncertain. Therefore, to make this process clear, we used the trait-based community framework, defining target species, non-target species, and common grass species, examining how the mix seed sowing and environment (two surface-covering materials applied to mine dump) affect re-vegetation composition, diversity, and functional traits in 14 years. Four treatments were tested: bio-fence surface-covering materials + sowing (BFS), plant-barrier surface-covering materials + sowing (PBS), sowing without any surface-covering materials (SOW), and a control without seeding and covering (CK). Natural grassland sites were regarded as reference (REF). Our findings indicated that the mix seed sowing and the interaction of surface-covering and time were primarily driving the dynamics of the plant community, affecting composition, the value of diversity, coverage, numbers, richness, and functional traits, such as the community-weighted mean (CWM) and functional diversity (FD), which increased and approached the sites REF. There were significant differences between the treatments and CK for the most traits. Although several results in the treatments approached the REF, significant differences still remained in the last observation year. With the sowing and surface-covering treatment, the re-built communities became more resource-acquisitive in terms of the CWM traits; even the value of the specific leaf area (SLA) exceed the REF after 14 years reclamation. We found those communities were dominated by target species that had a higher traits value than the non-target species, while the CK treatment became more resource-conservative over time due to non-target species dominating. The CWM in treatments tended toward reference levels for specific leaf area (SLA), leaf dry matter content (LDMC), and root dry matter content (RDMC), but not for seed mass (SM), thereby indicating that the above- and below-ground productivity of restored sites gradually overcame abiotic (surface-covering) and biotic (sowing) filters and approached target values. The functional diversity (FD) generally increased, with higher multivariate functional dispersion in the treatments containing more target species, suggesting that re-built communities achieve more resistance to invasion and disturbance over time. Hence, the trajectory of species and communities changing highlights the effectiveness of a trait-based approach in identifying better reclamation treatments and candidate species and provides a positive outlook for future re-vegetation community succession. Full article

Old growth forests are increasingly rare but important carbon sinks which harbour rich biodiversity. Chronic browsing by the white-tailed deer (Odocoileus virginianus) is a threat to the sustainability of the services provided by these forests, particularly in northern temperate forests where deer numbers have increased in recent decades (driven by stricter hunting rules and reduced predation) and necessitating local monitoring of vegetation responses. The objective of this study was to determine the effects of deer exclusion on tree regeneration dynamics and soil nutrients in an old growth Carolinian forest. This was performed using exclusion fencing and tip-up mounds at McMaster Forest Nature Preserve and the Sheelah Dunn Dooley Nature Sanctuary in Hamilton Ontario. Tree regeneration was surveyed from thirty 1 m × 1 m quadrats within exclusion plots and another thirty quadrats from deer-browsed areas adjacent to the exclusion plots. Soil samples were taken from each quadrat to analyze browsing impacts on nitrate, phosphate and soil organic matter. Red oak (Quercus rubra) was planted at the top and base of tip-up mounds of varying heights and widths and monitored for deer access and browsing activity. Results show a significantly higher density of woody plants within exclosures compared to non-exclosures (p = 0.0089) and twice more abundance of highly palatable species within the exclosures. However, species richness (p > 0.05) and diversity (p > 0.05) were minimally impacted by deer browsing, showing a resilient old growth forest. Soil nitrate was consistently higher in the non-exclosures, while phosphate was consistently higher within deer exclosures. Finally, more seedlings survived at the top of mounds than the bases, showing the potential of tip-up mounds to be a natural method of deer exclusion and a critical avenue for restoring over-browsed forests. Full article

Herbivory by ungulates is a seminal driving force in Mediterranean landscapes, where habitat diversity contributes to supporting high population densities. We investigated the influence of grazing and browsing, primarily by red deer (Cervus elaphus), on herbaceous and woody plant species, using a twin-plot design with herbivory exclusion. The prompt detection of herbivory cessation in vegetation was measured in multiscale plots by calculating Hill’s numbers (0, 1, and 2) as diversity indices over two years. The results revealed an increased diversity gradient by habitats (Pine reforestation→Mediterranean woodland→dehesas of Quercus spp.) with an initial increase in overall species and herbaceous species richness in the fenced plots. Woody vegetation did not change significantly in species richness, or typical or dominant ones. In addition to the early changes detected in the richness of herbaceous species (⁰D_her), medium–long term variations in woody species (presence and abundance) would represent good indicators of herbivory pressure for a diverse array of Mediterranean habitats. Full article

As street imagery and big data techniques evolve, opportunities for refined urban governance emerge. This study delves into effective methods for urban perception evaluation and street refinement governance by using street view data and deep learning. Employing DeepLabV3+ and VGGNet models, we analyzed street view images from Nanshan District, Shenzhen, identifying critical factors that shape residents’ spatial perceptions, such as urban greenery, road quality, and infrastructure. The findings indicate that robust vegetation, well-maintained roads, and well-designed buildings significantly enhance positive perceptions, whereas detractors like fences reduce quality. Furthermore, Moran’s I statistical analysis and multi-scale geographically weighted regression (MGWR) models highlight spatial heterogeneity and the clustering of perceptions, underscoring the need for location-specific planning. The study also points out that complex street networks in accessible areas enhance living convenience and environmental satisfaction. This research shows that integrating street view data with deep learning provides valuable tools for urban planners and policymakers, aiding in the development of more precise and effective urban governance strategies to foster more livable, resilient, and responsive urban environments. Full article

Fenced enclosures, a proven strategy for restoring degraded grassland, have been widely implemented. However, recent climate trends of warming and drying, accompanied by increased extreme rainfall, have heightened soil erosion risks. It is crucial to assess the long-term effectiveness of fenced enclosures on grassland restoration and their impact on soil physicochemical properties and water infiltration capacity. This study investigated the effects of enclosure duration on soil organic matter, aggregate composition and stability, and infiltration capacity in Yunwu Mountain Grassland Nature Reserve, comparing grasslands with enclosure durations of 2, 14, 30, and 39 years. Results showed that grasslands enclosed for 14, 30, and 39 years had infiltration rates increased by 20.66%, 152.03%, and 61.19%, respectively, compared to those enclosed for only 2 years. After 30 years of enclosure, soil quality reached its optimum, with the highest root biomass, soil organic matter, aggregate stability, and a notably superior infiltration rate. The findings suggest that long-term fenced enclosures facilitate grassland vegetation restoration and enhance soil infiltration capacity, with the most significant improvement observed at the 30-year enclosure milestone, followed by a gradual decline in this effect. Full article

Historical sheep farming in the Patagonian drylands has led to reduced grass cover, soil erosion, and shrub encroachment, compromising ecosystem function. Effective restoration requires managing shrub cover, bare soil, and patch connectivity through various strategies. This study evaluates rehabilitation interventions in a grass-steppe ecosystem, comparing grazed and ungrazed areas. Over three years, we tested the following: (a) mechanical shrub cutting with biomass redistribution, and (b) enhancing patch connectivity with Pinus spp. branch piles, alongside controls, in eighteen 5 m × 5 m plots invaded by Mulinum spinosum. Half of the plots were fenced to exclude grazing, resulting in six treatment combinations. We monitored soil properties, vegetation cover, and species composition. The treatments explained twice as much of the variation in community composition as the annual climatic variations (0.26 vs. 0.13). Livestock exclusion increased perennial grass cover more than the grazed plots did (2.14 vs. 1.42 times the initial measure). All treatments reduced the amount of bare soil except the grazed controls. Shrub cutting, especially with grazing, increased the lasting litter coverage by 5–10% and decreased the bare soil equivalently. Organic matter increased except in the non-intervened interpatches (0.95 times). The enclosures with cut shrubs trapped erodible particles, showing a 5% increase. Our study highlights that grazing destabilizes communities, while enclosures stabilize them, with interventions improving soil fertility and mitigating erosion. Full article

The aim of this article is to assess which elements of street design impact subjective well-being in the central area of a city in southern Chile, based on residents’ perceptions. Fifty-six semi-structured walking interviews were conducted to obtain records of pedestrians’ self-reported perceptions of their environment. To categorize the emotions reported in the interviews, the Circumplex Model of Affect was used to organize and classify the declared emotions. The results revealed that street design elements such as heritage buildings with well-maintained facades with intense colors in their coatings, spacious front gardens, wooden facades, low fences, wide sidewalks, soft or rubberized floors, and trees with colorful fruits and leaves promote a greater dominance of high-intensity positive emotions such as enjoyment, joy, happiness, liking, and pleasure. In contrast, neglected or abandoned building facades, blind fronts with graffiti or murals, high fences, tall buildings, treeless or vegetation-free sidewalks, untrimmed bushes, and narrow and poorly maintained sidewalks promote negative emotions of both high and low activation such as fear, anger, dislike, rage, unsafety, discomfort, and stress. The article concludes with the development of an emotional map of momentary experiences, identifying places of well-being and discomfort in public spaces. The value of this map is discussed as a tool to inform urban design in the promotion of healthier pedestrian environments in Latin American cities. Full article

The effective management of at-risk species often requires fine-scale actions by natural resource managers. However, balancing these actions with concurrent land uses is challenging, particularly when compounded by the interplay of climate shifts, and escalating wildland–urban interface conflicts. We used spatial prioritization tools designed for biodiversity conservation to help resource managers on the Island of Lānaʻi prioritize mutually exclusive land use objectives: endangered species recovery and subsistence and recreational hunting. We weighed the current and anticipated future distributions of threatened and endangered plant species against the distribution of non-native game mammals to plan for species recovery more effectively. Prioritization results identified multiple footprints that could support recovery of all endangered species targets in climate resilient areas while retaining the majority of existing hunting areas. However, very little native vegetation was retained in conservation footprints without deliberate inclusion, which increased footprint area by 268%. Scenarios which prioritized contiguous conservation areas also dramatically increased conservation footprint area, although these scenarios may reduce associated fencing costs. This work demonstrates how spatial prioritization may guide localized species recovery efforts by supporting long-term conservation planning that addresses anticipated climate-driven increases in conflict between conservation and other land uses, with clear applicability beyond Lānaʻi. Full article

Food insecurity remains a pressing issue globally, exacerbated in regions like sub-Saharan Africa, where rural communities face significant challenges in accessing nutritious food. The Eastern Cape Province of South Africa is particularly vulnerable, with high levels of poverty and limited infrastructure contributing to food insecurity among its rural households. In response to these challenges, family food gardens have emerged as a promising strategy to enhance local food production, improve dietary diversity, and foster economic resilience within these communities. Despite the potential benefits of family food gardens, empirical evidence of their effectiveness in mitigating food insecurity at the household level in the Eastern Cape Province is scarce and remains limited. Understanding the factors that influence the success of these gardens, including socio-economic, environmental, and institutional determinants, is crucial for optimizing their impact and scalability. Hence, this study sought to comprehensively explore and investigate the role of family food gardens in improving food security within rural households in the Eastern Cape Province. It seeks to identify the determinants that contribute to the success of these gardens and their potential to alleviate food insecurity. The study made use of a descriptive research design, and the study utilized purposive sampling to gather data from 130 rural households via structured questionnaires. Data analyses incorporated in the study included the Household Dietary Diversity Score and logit regression model to explore the impacts and determinants of family food gardens on food security. The study findings underscore the significant positive contributions of family food gardens to rural communities. They serve as vital sources of fresh crops and vegetables, supplementing household nutrition and providing temporary employment. Constraints identified in the study include financial limitations, theft, water scarcity, inadequate fencing, and limited market access. The study insights highlight the fact that socio-economic and institutional factors such as age, gender, household income, and access to credit are critical influencers of family food garden success. These empirical results offer practical implications for policymakers, governmental agencies, and local communities seeking to promote sustainable agricultural practices and alleviate food insecurity. The research highlights how essential family food gardens are for improving food security among rural families in the Eastern Cape Province. The findings suggest that a joint effort is needed from the government, policymakers, NGOs, and local communities to overcome challenges and make the most of social and economic resources. By working together, these groups can enhance the role of family food gardens, making them a more effective solution for local food production and a stronger defence against food insecurity in the region. Full article

Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability. Full article

The utilization of street view big data is increasingly being used to uncover visual characteristics and spatial perceptions of urban streets. However, there is a lack of studies that combine street view big data for perceptual evaluation in underdeveloped ethnic areas and better street quality. This study integrates deep learning methods to create a human–computer confrontational model for perception score, with a focus on the central city of Lhasa in Tibet. Pearson correlation analysis was conducted on six dimensions of perception data (beautiful, wealthy, safe, lively, boring and depressing) and visual elements. The streets in the top 20% for both visual elements and perceptual scores were identified to reveal areas with high visual element proportions and high perceptual scores. The spatial distribution characteristics and correlation between visual elements and street perceptions were thoroughly analyzed. The findings of this study reveal that the central city of Lhasa exhibited high percentages of visual elements in buildings (88.23%), vegetation (89.52%), and poles (3.14%). Out of the six perceptions examined, the highest scores were for boring (69.70) and depressing (67.76) perceptions, followed by beautiful (60.66) and wealthy (59.91) perceptions, with lively (56.68) and safe (50.64) perceptions receiving the lowest scores. Visual components like roads (−0.094), sidewalks (−0.031), fences (−0.036), terrain (−0.020), sky (−0.098), cars (−0.016), and poles (−0.075) were observed to have a significant deterring effect on the boring perception, while other visual elements showed a positive influence. This investigation seeks to provide valuable insights for the design and advancement of urban streets in marginalized ethnic localities, addressing a void in perception research of urban streets in such areas. Full article

There is still a lack of high-precision and large-scale soil ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃⁻-N) and available phosphorus (AP) in alpine grasslands at least on the Qinghai–Xizang Plateau, which may limit our understanding of the sustainability of alpine grassland ecosystems (e.g., changes in soil NH₄⁺-N, NO₃⁻-N and AP can affect the sustainability of grassland productivity, which in turn may alter the sustainability of livestock development), given that nitrogen and phosphorus are important limiting factors in alpine regions. The construction of big data mining models is the key to solving the problem mentioned above. Therefore, observed soil NH₄⁺-N, NO₃⁻-N and AP at 0–10 cm and 10–20 cm, climate data (air temperature, precipitation and radiation) and/or normalized vegetation index (NDVI) data were used to model NH₄⁺-N, NO₃⁻-N and AP in alpine grasslands of Xizang under fencing and grazing conditions. Nine algorithms, including random forest algorithm (RFA), generalized boosted regression algorithm (GBRA), multiple linear regression algorithm (MLRA), support vector machine algorithm (SVMA), recursive regression tree algorithm (RRTA), artificial neural network algorithm (ANNA), generalized linear regression algorithm (GLMA), conditional inference tree algorithm (CITA), and eXtreme gradient boosting algorithm (eXGBA), were used. The RFA had the best performance among the nine algorithms. Climate data based on the RFA can explain 78–92% variation of NH₄⁺-N, NO₃⁻-N and AP under fencing conditions. Climate data and NDVI together can explain 83–93% variation of NH₄⁺-N, NO₃⁻-N and AP under grazing conditions based on the RFA. The absolute values of relative bias, linear slopes, R² and RMSE values between simulated soil NH₄⁺-N, NO₃⁻-N and AP based on RFA were ≤8.65%, ≥0.90, ≥0.91 and ≤3.37 mg kg⁻¹, respectively. Therefore, random forest algorithm can be used to model soil available nitrogen and phosphorus based on observed climate data and/or normalized difference vegetation index in Xizang’s grasslands. The random forest models constructed in this study can be used to obtain a long-term (e.g., 2000–2020) raster dataset of soil available nitrogen and phosphorus in alpine grasslands on the whole Qinghai–Tibet Plateau. The raster dataset can explain changes in grassland productivity from the perspective of nitrogen and phosphorus constraints across the Tibetan grasslands, which can provide an important basis for the sustainable development of grassland ecosystem itself and animal husbandry on the Tibetan Plateau. Full article