Global Ecosystem Research Articles

A new method for mapping vegetation structure parameters in forested areas using GEDI data

The spatially continuous mapping of vegetation structure parameters in forested areas serves as a crucial foundation for research in various fields, including ecosystem ecology, climate change, hydrology, and forest management and protection. However, there is a notable scarcity of regional scale data regarding vegetation structure parameters. Therefore, our objective was to fill this data gap by providing a methodology for mapping vegetation structure parameters in forested areas at regional-scale. Global Ecosystem Dynamics Investigation (GEDI) provides precise observational data on vegetation structure parameters across the world. Using GEDI vegetation structure parameter point data, we developed a vegetation state coefficient based on the ratio of plant area index (PAI) and vegetation coverage (COVER). Subsequently, we proposed a method for decomposing vegetation coverage to simulate layered vegetation coverage. Taking Jiangxi Province as a case study, we integrated machine learning models to generate a spatially continuous map of vegetation structure parameters in forested areas, including layered coverage and layered leaf area index, in 2020. The map has a spatial resolution of 30 m and a vertical resolution of 5 m. The model exhibits excellent performance. Among the 140 sets of models, approximately 63 % of them achieved an R2 surpassing 0.6, while 89 % of the models achieved a root mean square error (RMSE) below 0.3. This study can serve as a valuable reference for the decomposition of vegetation structure parameters at the regional scale and provide a more precise depiction of the spatial characteristics of vertical vegetation structure at the regional scale. It contributes by providing data support and methodological guidance for research related to forest structure analysis, resource management, and ecological process simulation at the regional scale.

Land cover change assessment in Thai Nguyen Province, Vietnam using GIS and remote sensing techniques

The expansion of agricultural production and urbanization has led to the depletion of the global forest ecosystem, resulting in land cover changes (LCCs) that pose threats to the land environment. Therefore, it is imperative to identify these LCCs as an essential step toward resolution and mitigation. This study aims to evaluate temporal LCCs in Thai Nguyen province by utilizing GIS and remote sensing techniques (RST) to analyze high-resolution satellite imagery spanning from 2001 to 2023. LCCs were identified using semi-automatic classification plugin (SCP) techniques with Landsat-8 and Sentinel-2 images in ERVI software. The accuracy of the LCC maps was validated through post-classification comparisons, yielding high precision rates ranging from 87% to 96%. The results indicate a significant reduction in forest cover area, declining by 1018 ha from 226,18 ha in 2001 to 207,22 ha in 2023. This decline primarily occurred in urban areas, highlighting the intensification of urbanization processes. Cultivated and bare land experienced a minor decrease and a substantial decrease from 18,631 ha and 105,000 ha to 16,578 ha and 86,82 ha between 2001 and 2010, followed by a slight increase and a significant increase to 5,069 ha and 24,487 ha (1.4% and 6.9%) during the 2010-2023 period. These findings underscore the escalating risk of diminishing forest cover in the study area.

Genome-wide annotation and comparative analysis revealed conserved cuticular protein evolution among non-biting midges with varied environmental adaptability

Chironomidae, non-biting midges, a diverse and abundant insect group in global aquatic ecosystems, represent an exceptional model for investigating genetic adaptability mechanisms in aquatic insects due to their extensive species diversity and resilience to various environmental conditions. The cuticle in insects acts as the primary defense against ecological pressures. Cuticular Proteins (CPs) determine cuticle characteristics, facilitating adaptation to diverse challenges. However, systematic annotation of CP genes has only been conducted for one Chironomidae species, Propsilocerus akamusi, by our team. In this study, we expanded this annotation by identifying CP genes in eight additional Chironomidae species, covering all Chironomidae species with available genome data. We identified a total of 889 CP genes, neatly categorized into nine CP families: 215 CPR RR1 genes, 272 CPR RR2 genes, 23 CPR RR3 genes, 21 CPF genes, 16 CPLCA genes, 19 CPLCG genes, 28 CPLCP genes, 77 CPAP genes, and 37 Tweedle genes. Subsequently, we conducted a comprehensive phylogenetic analysis of CPs within the Chironomidae family. This expanded annotation of CP genes across diverse Chironomidae species significantly contributes to our understanding of their remarkable adaptability.

Future of Pharmaceutical Industry: Role of Artificial Intelligence, Automation and Robotics

Background The future of smart factories and pharmaceutical industries has evolved significantly since the 19th century. Computers have been used in the pharmaceutical field since the 1980s with the emergence of Artificial Intelligence (AI). In addition, automation and robotics are used in the pharmaceutical industry to improve the efficiency of pharmaceutical development and production. Purpose The present review article covers the future roles of AI, automation and robotics in pharmaceutical industries. Methodology The current review article employed a comprehensive search strategy across relevant databases, including PubMed, Scopus and Web of Science, utilizing keywords such as AI, Automation, Robotics and Pharmaceutical Industries. The articles considered a focus on recent advancements and emerging trends in the intersection of AI, automation and robotics within pharmaceutical sectors. Results AI, incorporating predictive machine learning and reasoning techniques, aids in the preclinical identification of molecules and forecasting potential lead compounds before conducting clinical trials. automation offers significant benefits in monitoring and predictive maintenance of production lines, power distribution and control machines. Robotic process automation improves efficiency by connecting computer terminals to handle various manufacturing process elements. Conclusion Artificial intelligence, automation and Robotics have sparked innovations in the healthcare business, benefiting the global ecosystem and healthcare delivery. Incorporating these advanced tools in pharmaceutical industries from raw material selection to final product development could improve the quality and safety of the pharmaceutical products and reduce the time and cost.

A spectral mixture analysis based framework for estimating and charactering water use efficiency in heterogeneous drylands

Climate change and irrational land utilization have significantly disrupted the function and structure of the dryland ecosystems, leading to tremendously potential effects on the carbon and water cycles of the global terrestrial ecosystems. Ecosystem-scale water use efficiency (WUE) is a crucial metric that defines the ratio of gross primary productivity (GPP) to evapotranspiration (ET), revealing the coupling relationship between such two ecological processes and playing a significant role in water resource management decision-making. However, quantifying WUE in drylands remains a challenge because of their heterogeneous land surface challenging to characterize model parameters using traditional remote sensing techniques. Here, we developed a process-based framework to estimate GPP and ET, as well as WUE based on physical endmember fractions from spectral mixture analysis (SMA) model. And such framework is used to quantify the spatial and temporal evolution of WUE by optimizing the light use efficiency and assisting in the construction of a GV-Cws model for the separation of transpiration and evaporation processes during computation by utilizing the physically fractional vegetation and soil obtained from SMA in the Hexi Corridor of China, a typical dryland ecosystem. The results demonstrate that our framework can accurately estimate GPP and ET in the Hexi Corridor, as indicated by favorable performance in R2 (0.669, 0.705), RMSE (0.383,0.885) and NSE (0.534, 0.690) respectively. Such results surpass the accuracy of both two Moderate Resolution Imaging Spectroradiometer (MODIS) products and Penman-Monteith-Leuning Evapotranspiration V2 (PML_V2)’s ET product. These advantages highlight that our SMA-based framework can provide highly accurate and distinct characterization of surface carbon and water interaction processes. Meanwhile, the WUE of the Hexi Corridor ecosystem exhibited a positive trend from 2001 to 2017 (0.016 gC·m−2·mm−1·a-1), characterized by simultaneous increases in GPP and ET.

Biodiversity and Wetting of Climate Alleviate Vegetation Vulnerability Under Compound Drought‐Hot Extremes

AbstractGlobal warming has intensified the intensity of compound drought‐hot extremes (CDHEs), posing more severe impacts on human societies and ecosystems than individual extremes. The vulnerability of global terrestrial ecosystems under CDHEs, along with its key influencing factors, remains poorly understood. Based on multiple remote sensing data, we construct a Vine Copula model to appraise vegetation vulnerability under CDHEs, and attribute it to climatic and biotic factors for five different vegetation types. High vulnerability is detected in central and southern regions of North America, eastern and southern regions of South America, Southern Africa, northern and western Europe, and northern and eastern Australia. The drier the climate, the higher will be the vulnerability. Furthermore, biodiversity and biomass are key biotic factors influencing the vulnerability of various vegetation types, such that ecosystems with richer biodiversity and higher biomass have lower vulnerability to CDHEs. The findings deepen understanding of terrestrial ecosystem response to CDHEs.

Viewpoint: could cultivated meat's real route to mainstream markets be as hybrid food ‐ why this makes sense?

SummaryFrom beginnings as an esoteric research topic, cultivated meat (produced from cells originating from the meat producing animals) has developed with increasing pace from a research concept and is starting to break into restaurant markets in Singapore, USA, and Israel. However, there remains a significant journey in the global food ecosystem in order for it to reach mainstream retail. This viewpoint piece will probe how combining the best from plant‐based meat alternatives and cultivated meat disciplines may end up addressing consumers desires, delivering on sustainability, palatability, nutritional balance and economic viability.

Achieving Sustainable Development Goal Four (4) in Africa: Spotlighting the role of quality education and innovation orientation

The novel coronavirus (COVID-19) has damaged the global economy and business ecosystem. Also, quality education and skills mismatch have become critical in today’s working environment post-COVID-19. Furthermore, one of the 17 Global Goals comprising the 2030 Agenda for Sustainable Development is quality education, yet Africa pays less attention to this and its impact in the workplace and organizations. This study, therefore, examined the effects of quality education on the innovation orientation of selected consumer goods companies listed in Nigeria and their role in achieving SDGs in Nigeria, the most populous and largest economy in Africa. Findings showed that quality education had a significant effect on innovation orientation. This study recommends that management and stakeholders consider the benefits of quality education in innovation and innovation orientation and, therefore, channel resources to achieve and align with Sustainable Development Goal 4.

Impact of fire severity on forest structure and biomass stocks using NASA GEDI data. Insights from the 2020 and 2021 wildfire season in Spain and Portugal

Wildfires have been progressively shrinking the C sink capacity of forest accelerating climate change effects on forest biodiversity, especially where megafires are recurrent and of increased frequency such as in the Mediterranean. Data from The Global Ecosystem Dynamics Investigation (GEDI) mission can inform on changes on forest structure to inform on fire impacts on vegetation. In this study, we assessed the performance of GEDI at measuring biomass and structural change from wildfires using the 2020/21 summer fire seasons in Spain and Portugal. The GEDI hybrid-inference method was used to calculate mean and total biomass in pre- and post-fire stages, while GEDI footprint data was further used to explain the fire severity classes derived from optical data. Our results showed the increasing impact of wildfires on biomass stocks and GEDI ecological metrics by increasing fire severity. More than over biomass stocks, severe fires substantially altered trends in structural metrics such as plant area volume density. The integration of GEDI metrics to explain fire severity had an accuracy of 52% considering five severity classes and an accuracy of 69% when considering the three main classes: unburned, moderate and high. Structural metrics from GEDI can be used to improve optical-based fire severity estimates used globally and to evaluate potential fire impacts based on time-series of GEDI tracks as showcased in the study, but also to measure forest recovery between fire seasons. The extension of GEDI is a major support for wildfire mapping efforts, integrated approaches to capture the increasing impact of fire on forest biodiversity and the monitoring of changes in carbon stocks.

Integrating Indicators in Agricultural Vulnerability Assessment to Climate Change

AbstractClimate change stands as one of the most pressing challenges confronting global ecosystems and human livelihoods. The agriculture sector of Anuradhapura district, Sri Lanka, well renowned for its pivotal role in the nation’s food production, faces an increasing threat from the changing climate. This study aims to incorporate the indicator system method which uses a set of indicators to assess the agricultural vulnerability (AV) to climate change in Anuradhapura district. The AV assessment used in this study involves three principal components exposure, sensitivity, and adaptive capacity. The indicators are normalized to allow spatial analysis and smooth integration within a geographic information system (GIS) framework. The AV of Anuradhapura district ranged from 0.32 to 0.67 and was divided among five levels very low, low, moderate, high, and very high. The findings suggest that Anuradhapura’s agricultural sector was significantly impacted by climate change as the majority of the total area was found to have very high, high, and moderate levels of AV with 25, 28, and 24%, respectively. The results obtained from this study are essential for formulating plans to improve Anuradhapura’s agricultural sector resilience and adaptability to ensure food security and livelihood sustainability considering the ever-changing climate.

Repeat GEDI footprints measure the effects of tropical forest disturbances

More of the Amazon rainforest is disturbed each year than completely deforested, but the impact of these disturbances on the carbon cycle remains poorly understood. Recent algorithmic advances using optical and radar remote sensing have improved detection of disturbances at fine spatiotemporal resolution, but quantifying changes in forest structure and biomass associated with these detected disturbances has proven challenging. The Global Ecosystem Dynamics Investigation (GEDI), a spaceborne lidar mission collecting data from 2019 to 2023, provides an opportunity to address this problem. GEDI captured billions of measurements of forest height, plant area, and understory structure within ∼25-m diameter footprints scattered across the tropics. Though the instrument had no guaranteed repeat cycle, it sometimes sampled nearby locations twice; some of these spatially near-coincident footprints happened to measure forest structure before and after a detected disturbance, providing information on how disturbance affected aboveground biomass. In this study, we developed an efficient general-purpose open-source pipeline for identifying spatially coincident footprints, which is a computationally complex task, and used the pipeline to find over 13,700 footprint pairs with intervening disturbance events across the Amazon biome. We also identified a set of ∼65,000 spatially near-coincident footprint pairs that lacked an intervening disturbance but came from regions with similar disturbance threat; these provided a control dataset to evaluate the effectiveness of estimating forest structure and biomass changes with nearby footprints. Analysis of this Amazon-wide dataset demonstrated that GEDI was able to measure statistically significant canopy height and biomass deficits following non-stand-replacing disturbances as small as 900 m2 (30 m × 30 m). GEDI's unique three-dimensional view of forest structure also reflected the effects of different intensities of fire disturbance, including 20% of burned areas where the upper canopy retained most of its height, but the understory suffered substantial foliage losses. Finally, we modeled the relationship between Landsat and Sentinel-1 disturbance detection parameters and GEDI-estimated percent biomass loss, showing that certain satellite-derived intensity metrics are correlated with increasing biomass loss and identifying temporal trends in biomass loss and recovery following disturbance. This work represents an important step towards the development of a pan-tropical, spatially explicit system for tracking carbon losses and structural changes arising from forest disturbance.

Polystyrene Plastic Particles Result in Adverse Outcomes for Hyalella azteca When Exposed at Elevated Temperatures

Micro- and nano-plastics are pervasive pollutants in global ecosystems, yet their interactions with aquatic wildlife and abiotic factors are poorly understood. These particles are recognized to cause subtle detrimental effects, underscoring the necessity for sensitive endpoints in ecotoxicological exposure studies. We investigated the effects of particle uptake, size, and temperature on Hyalella azteca. Organisms were exposed to blue fluorescent polystyrene beads (500 nm and 1000 nm in diameter) at 0.43 mg/L for 96 h at temperatures mirroring climate predictions (21 °C, 24 °C, 27 °C). Besides survival and growth, particle uptake, visualized via confocal microscopy, and swimming behavior were analyzed. Mortality rates increased at 27 °C, and particle presence and temperature affected organism growth. Particle treatments influenced various behaviors (thigmotaxis, cruising, movement, acceleration, meander, zone alternation, and turn angle), with hypoactivity observed with 1000 nm particles and hypo- as well as hyper-activity responses with 500 nm particles. Particle uptake quantities were variable and increased with temperature in 500 nm treatments, but no migration beyond the gut was observed. Particle size correlated with uptake, and relationships with behavior were evident. Elevated temperatures exacerbated particle effects, highlighting the urgency of addressing plastic pollution in light of climate change for aquatic organism welfare and ecosystem health.

Geomorphological Evolution in the Tidal Flat of a Macro-Tidal Muddy Estuary, Hangzhou Bay, China, over the Past 30 Years

Tidal flat plays an important role in coastal development because of its ecological and spatial resources. We take the southern tidal flat in the macro-tidal turbid Hangzhou Bay as an example to study the long-term (1990–2020) evolution of the muddy tidal flat, using remote sensing data and field observational data. The detailed bathymetric elevation of the tidal flat is obtained, using remote sensing images of Landsat and Sentinel-2, combined with the real-time kinematic (RTK) data. The correlation coefficient between the remote sensing data and the RTK data is 0.73. The tidal flat and vegetation areas are affected by reclamation. The total tidal flat area decreased by 467.78 km2. The vegetation area declined from 64.98 km2 in 2000 to 13.41 km2 in 2015 and recovered to 41.62 km2 in 2020. The largest change in tidal flat slope occurs in the eastern and western sides of the tidal flat, compared with the wide middle part. The total length of tidal creeks decreased to 45.95 km in 2005 and then increased to 105.83 km in 2020. The middle- and low-grade tidal creeks accounted for 91.4%, with a curvature slightly larger than 1 in 2020. High-grade tidal creeks occur inside the vegetation areas, with less bending and fewer branch points. Vegetation promotes the development of tidal creeks but limits the lateral swing and bifurcation. These results provide a basis for the management of global tidal flat resources and ecosystems.

China’s ecological footprint via biomass import and consumption is increasing

As China’s economic and population demands grow, the need for biomass imports rises, presenting challenges for sustainable development and global ecosystem protection. Here we examine China’s increasing influence on global ecosystems through its biomass product consumption and trade using the Human Appropriation of Net Primary Productivity framework, analyzing data from 2004 to 2017 with projections until 2050. In 2017, China was the world’s largest biomass consumer, consuming approximately 1.75 petagrams of carbon per year, projected to rise by 317.6% by 2050, highlighting China’s major role in global ecosystem stress. Our findings also show an increase in biomass imports from lower-middle-income and low-income countries between 2004 and 2017, and these imports are expected to continue increasing by 402.9% in 2050. The analysis reveals that domestic product demand and changes in foreign production efficiency are key drivers of this trend, suggesting the need for China to shift towards more efficient trade practices and support cleaner production methods internationally.

Using biophysical modelling and marine connectivity to assess the risk of natural dispersal of non-indigenous species to comply with the Ballast Water Management Convention

The introduction of Marine Non-Indigenous Species (NIS) poses a significant threat to global marine biodiversity and ecosystems. To mitigate this risk, the Ballast Water Management Convention (BWMC) was adopted by the UN International Maritime Organisation (IMO), setting strict criteria for discharges of ballast water. However, the BWMC permits exemptions for shipping routes operating within a geographical area, known as a Same-Risk-Area (SRA). An SRA can be established in areas where a risk assessment (RA) can conclude that the spread of NIS via ballast water is low relative to the predicted natural dispersal. Despite the BWMC's requirement for RAs to be based on modelling of the natural dispersal of NIS, no standard procedures have been established. This paper presents a methodology utilizing biophysical modelling and marine connectivity analyses to conduct SRA RA and delineation. Focusing on the Kattegat and Øresund connecting the North Sea and Baltic Sea, we examine two SRA candidates spanning Danish and Swedish waters. We provide an example on how to conduct an RA including an RA summary, and addressing findings, challenges, and prospects. Our study aims to advance the development and adoption of consistent, transparent, and scientifically robust SRA assessments for effective ballast water management.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit.

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Stingless bee foragers experience more thermally stressful microclimates and have wider thermal tolerance breadths than other worker subcastes

IntroductionThe current state of anthropogenic climate change is particularly concerning for tropical insects, species predicted to be the most negatively affected. Researching climatic tolerance in social insects is challenging because adaptations exist at both individual and societal levels. Division of labor research helps to bridge the gap between our understanding of these adaptations at different scales, which is important because social insects comprise a tremendous portion of global animal biomass, biodiversity, and ecosystem services. Considering how individual physiologies construct group-level adaptations can improve climate change impact assessments for social species. Tetragonisca angustula is a neotropical stingless bee species that exhibits high worker subcaste specialization with a morphologically distinct soldier caste.MethodsWe used this species to investigate 1) whether age- and size-differentiated subcastes differ in thermal tolerance, 2) which worker subcaste operates closest to their thermal limits, and 3) the extent to which this species selects active foraging times to offset thermal stress. We measured the thermal tolerance (CTmax and CTmin) of small-bodied foragers and two soldier subcastes (hovering guards and standing guards) in T. angustula.Results and discussionDespite body size differences between foragers and guards, no differences in the upper or lower thermal limits were observed. However, the average thermal tolerance breadth of foragers was significantly larger than that of guards, and foraging sites were more thermally variable than nest sites, supporting the Climatic Variability Hypothesis at a microclimate scale and in the context of division of labor. Warming tolerance was significantly lower among small-bodied foragers compared to hovering and standing guards. The magnitude of warming tolerances indicated low risk of imminent climate change impacts in this environment but suggests that increasing temperatures and heatwave prevalence may cause foragers to meet their upper thermal limits before other subcastes. Foraging occurred at a narrower range of temperatures than would challenge critical temperatures, with higher morning activity. Directionally increasing temperatures will likely confine these preferred foraging temperatures to a narrower time window. Further study is needed to elucidate how foragers may shift times of activity in response to anthropogenic warming, but changing climates may impact plant pollination rates in natural and agricultural systems.

Spatial distribution and environmental/biological co-regulation mechanism of dimethyl sulfur compounds in the eastern Indian Ocean

Dimethyl sulfur compounds including dimethylsulfoniopropionate (DMSP), dimethyl sulfide (DMS), and dimethyl sulfoxide (DMSO), play a crucial part in global sulfur cycling. The eastern Indian Ocean (EIO), characterized by its remarkable diversity of biomes and climate dynamics, is integral to global climate regulation. However, the regulation mechanism of DMS (P, O) in the EIO remains to be elucidated in detail. This paper presented a field survey aimed at investigating the spatial distribution of DMS (P, O) and their relationships with environmental and biological factors in the EIO. The surface concentrations of DMS, DMSPt, and DMSOt varied from 0.07 to 7.37 nmol/L, 0.14 to 9.17 nmol/L, and 0.15 to 3.32 nmol/L, respectively, and their distributions are attributed to high Chl-a concentration near Sri Lanka and the influence of ocean currents (Wyrtki jets, Bay of Bengal runoff). Higher concentrations of DMS (P) and DMSOt were predominantly observed in water columns shallower than 75m and deeper than 75m deep, respectively. The monthly DMS fluxes in the study area peaked in August. Temperature and Dissolved Silica Index (DSI) were the key environmental determinants for DMS distribution, while nitrate (NO3-) was the primary factor for both DMSPt and DMSOt. In terms of biological factors, Prochlorococcus and Synechococcus were significant contributors to DMS (P, O) dynamics. Synechococcus was the dominant influence on the DMS source and DMSPt sink, whereas Prochlorococcus primarily consumed DMSOt. Furthermore, the structural equation modeling (SEM) revealed the relationship between DMS, DMSPt, DMSOt, and the key environmental/biological factors, as well as among them, and together they formed a co-regulatory network in the EIO. This contributes significantly to the advancement of global ecosystem models for DMS (P, O).

Effects of reduced snowpack due to climate warming on abiotic and biotic soil properties in alpine and boreal forest systems

Reduction in snow cover, depth, onset, and duration of seasonal snow in mid-latitude regions due to climate warming has multiple global and local scale ecosystem impacts. These effects include modulations of the hydrological cycles and increases in land surface solar radiation absorption due to decreased albedo. Changes in snow cover characteristics also affect underlying soils. Snow has an insulating effect on soils by decoupling air and soil temperatures, thus seasonal snow cover reduction leads to overall lower soil temperatures and an increase in freeze-thaw cycles. This is especially prominent during the fall and spring thaw seasons when the snow cover is not as extensive. This in turn has downstream impacts on soil physical, chemical, and biological properties. Among these impacts are soil moisture reduction, temperature, frost regimes, soil pH shifts, and alteration in nutrient flux dynamics during winter, snowmelt period and the following summer growing season. These changes in soil physicochemical properties due to snowpack reduction can then impact the biological soil properties via increased plant root mortality, reduced abundance and diversity of soil arthropods, and shifts in composition, abundance and activity of soil microbial communities. All these soil biotic factors can in turn alter the dynamics of soil nutrient fluxes and future greenhouse gas emissions. Here, we integrate data on the effects of snow cover reduction on abiotic and biotic soil properties, with focus on temperate alpine and forest ecosystems and with an outlook on future impacts.

Variations of the soil macrofauna community and corresponding influencing factors in the newly reclaimed coastal area: A case study in Yangtze Estuary, China

Intensive reclamation activity has reshaped global coastal ecosystems. Soil macrofauna, an effective proxy for ecosystem health, has the potential to predict coastal reclamation ecological impact. Previous studies have primarily focused on the long-term (≥ 30 years) soil macrofaunal succession in reclaimed areas. However, composition of the soil macrofauna and its environmental drivers in newly reclaimed areas (< 30 years) remain uncertain. We selected Hengsha Dongtan in the Yangtze Estuary to conduct the study, and four different regions (reclaimed for 13, 8, 4, and 1 year, respectively) were employed to investigate soil macrofaunal composition and corresponding environmental drivers. The results showed that: (1) Terrestrial species millipedes (Paradoxosomatidae sp.), chinch bugs (Dimorphopterus spinolae), and wolf spiders (Pirata subpiraticus) were dominant. Millipedes, chinch bugs, wolf spiders, ants (Myrmecina sp.), and rove beetles (Stenus melanarius and Paederus fuscipes) were major species contributing to the average dissimilarity among regions. (2) The taxonomic composition of soil macrofauna varied over time after reclamation, which showed that the number of species, density, and biomass of soil macrofauna in region 1 (reclaimed for 13 years) was higher than that in regions 2, 3, and 4 (reclaimed for 8, 4, and 1 year). (3) The functional composition of soil macrofauna varied over time after reclamation. The number of species, density, and biomass of the phytophagous and saprophagous groups increased over time, whereas those of the predatory group decreased gradually. (4) Soil pH and total organic carbon content, together with land use, appeared to be key factors that determine soil macrofaunal composition. Overall, our study illustrates the response of soil macrofauna to changes in environmental factors and land use in newly reclaimed areas. Future studies should expand the range of potential factors and comprehensively analyze the mechanisms that maintain soil macrofaunal diversity in reclaimed areas.