Abundance, Biomass and Contribution to Energy Flow by Soil Nematodes in Terrestrial Ecosystems

According to Kyoto protocol carbon seques- tration in terrestrial ecosystem is a low cost option to mitigate the increasing atmospheric CO2 concentrations. It has been understood that the world's forests and their soils have a high potential to sequester the atmospheric carbon. For the last two decades there has been increasing interest among scientists in terrestrial soil carbon storage processes. This review made an attempt to summarize the major chronological advancement of soil organic carbon (SOC) sequestration research and also to underpin the problems yet to be focused on this research at global level. SOC sequestration research began in the early seventies, where most of the studies were estimating the size/stock of the global SOC. In the early eighties, most of the researchers have started to focus on the factors involved in the storage of organic carbon in different ecosystems. Subsequently, the researchers started to work on different types of SOC pools, their size, turnover and chemical characterization in different types of ecosystems. Recently the researcher's main focus has been the temperature sensitivity of organic carbon in different types of soil and their mechanism of stabilization. There has been interest among researchers on the contribution of microbial derived (microbial necro- mass) carbon in recalcitrant pool of SOC and their sequestration process in different types of ecosystems. Arguably, the contribution in SOC sequestration research on the fate of sequestered carbon in different types of soil and their stabilization mechanisms is insufficient. India is the country spread over regions from temperate to dry desert zones with different types of fragile ecosystems and its vulnerable nature to the global climate change. There- fore, the future research must focus on SOC sensitivity to temperature and SOC stabilization mechanisms in different ecosystems for better understanding of the soil carbon cycle.

Comparison of the 2010 and 2020 ecosystem structures in Xihu Harbor based on the Ecopath model

Investigating the spatiotemporal variations in Aerosol Optical Depth (AOD) in terrestrial ecosystems and their driving factors is significant for deepening our understanding of the relationship between ecosystem types and aerosols. This study utilized 1 km resolution AOD data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Mann–Kendall (M-K) trend test to analyze the spatiotemporal variations in AOD in seven ecosystems in Northern Xinjiang from 2001 to 2023. The geographic detector model was employed to investigate the effects of driving factors, including gross domestic product, population density, specific humidity, precipitation, temperature, wind speed, soil moisture, and elevation, on the distribution of AOD in the ecosystems. The results indicate that over the past 23 years, wetlands had the highest annual average AOD values, followed by settlements, farmlands, deserts, grasslands, others, and forests, respectively. Furthermore, the AOD values decrease with increasing ecosystem elevation. The annual mean of AOD in Northern Xinjiang generally shows a fluctuating upward trend. The M-K test shows that the proportion of area with an increasing trend in AOD in the settlement ecosystems is the highest (92.17%), while the proportion of area with a decreasing trend in the forest ecosystem is the highest (21.78%). On a seasonal scale, grassland, settlement, farmland, forest, and wetland ecosystems exhibit peak values in spring and winter, whereas desert and other ecosystems only show peaks in spring. Different types of ecosystems show different sensitivities to driving factors. Grassland and forest ecosystems are primarily influenced by temperature and altitude, while desert and settlement ecosystems are most affected by wind speed and humidity. Farmlands are mainly influenced by wind speed and altitude, wetlands are significantly impacted by population density and humidity, and other ecosystems are predominantly affected by humidity and altitude. This paper serves as a reference for targeted air pollution prevention and regional ecological environmental protection.

Swimming crab (Portunus trituberculatus) are an important aquaculture species in eastern coastal areas of China. To improve the understanding of P. trituberculatus culture ecosystem functioning, the dynamics of energy flow and trophic structure of a P. trituberculatus polyculture system (co-culture with white shrimp Litopenaeus vannamei and short-necked clam Ruditapes philippinarum) were investigated in this study. Three Ecopath models representing the early, middle, and late culture periods of a P. trituberculatus polyculture ecosystem, respectively, were constructed to compare ecosystem traits at different culture periods. The results demonstrated that detritus was the main energy source in this polyculture ecosystem, and most of the total system throughput occurred at trophic levels I and II. Artificial food input and consumption by the culture organisms increased from early to middle and late periods, which produced marked impacts on biomass structure and primary production. R. philippinarum was considered to have a dominant influence on phytoplankton community dynamics which changed from nano- to pico-phytoplankton predominance, from the middle to the late period. Considering the low utilization efficiency of pico-phytoplankton production, large amounts of detritus accumulated in the sediment in the late period, which may constitute a potential risk for the ecosystem. Ecological network analyses indicated that the total energy flow and level of system organization increased from the early to the middle and late periods, whereas food web complexity and system resilience decreased from early to middle and late periods, which may indicate a trend of decreasing ecosystem stability. The system may be further optimized by increased stocking density of R. philippinarum and by introducing macro-algae at a suitable biomass to increase ecosystem stability, energy utilization efficiency, and aquaculture production.

Plasticity of xylem architecture can be a species specific strategy to reduce vulnerability to climate change. To study how the evergreen shrub Erica arborea regulates its xylem at different time scales as a response to climatic variability, we compared time series of annual xylem traits such as ring-width (growth), vessel size (hydraulic diameter and mean vessel area), vessel density, and potential conductivity (Kh) at two sites characterized by contrasting Mediterranean climates in Italy and Spain. Shrubs regulated their xylem in response to major differences in climate by modifying mostly their growth and vessel density. The different adjustment of xylem observed at the two sites was partly explained by the nonlinear nature of the relationship between the studied traits and temperature. Xylem development was mostly limited by low winter temperature at the cold and moist site, where plants produced more vessels per unit area of xylem and reduced growth in comparison with the warm and dry site. The responses of vessel size and density to climate were opposite. Vessel size and Kh were similar at the two sites and exhibited less sensitivity to climate than vessel density and growth. Humid conditions in spring increased growth and vessel size but decreased vessel density at the cold site, whereas the effect on xylem adjustment of high temperatures during the vegetation period was generally contrary to that of high moisture availability. These results likely express within species adaptations of the hydraulic function and the safety-efficiency trade-off in response to climate. A decline in growth in response to a recent decrease in precipitation at the dry site could be interpreted as a first sign of vulnerability to increasing drought severity. Similar to other species, climate change may have contrasting effects for E. arborea at its cold and dry distributional limits.

Vibrational energy flow in elastic circular cylindrical shells

Who is the new sheriff in town regulating boreal forest growth?

In order to compile an annual or seasonal energy budget for a small mammal population, it is necessary to derive estimates of standing crop, consumption, egestion, digestion, excretion, assimilation, respiration, growth and reproduction. This review gives an account of the methods available for compiling such budgets, and uses results obtained from a study of Microtus agrestis in south west Britain as a worked example. This population was live–trapped on twenty occasions during the course of 2 years. Total energy flow was 309 kJ/m2 in the first year and 173 kJ/m2 in the second. The average coefficient of digestibility of the natural diet was 54–3%, the average net production efficiency was 1 –0% and the average gross ecological efficiency was 1 –2%. Peak energy flow occurred in spring and late summer each year, and coincided with peaks in the abundance and growth rate of the grasses which formed the main source of food. Previously published estimates show that the annual flow of energy is higher amongst small mammal populations inhabiting open habitats, such as grasslands, than it is in successionally more mature habitats, such as woodlands.

Accurately estimating the carbon budgets in terrestrial ecosystems ranging from flux towers to regional or global scales is particularly crucial for diagnosing past and future climate change. This research investigated the feasibility of two comparatively advanced machine learning approaches, namely adaptive neuro-fuzzy inference system (ANFIS) and extreme learning machine (ELM), for reproducing terrestrial carbon fluxes in five different types of ecosystems. Traditional artificial neural network (ANN) and support vector machine (SVM) models were also utilized as reliable benchmarks to measure the generalization ability of these models according to the following statistical metrics: coefficient of determination (R2), index of agreement (IA), root mean square error (RMSE), and mean absolute error (MAE). In addition, we attempted to explore the responses of all methods to their corresponding intrinsic parameters in terms of the generalization performance. It was found that both the newly proposed ELM and ANFIS models achieved highly satisfactory estimates and were comparable to the ANN and SVM models. The modeling ability of each approach depended upon their respective internal parameters. For example, the SVM model with the radial basis kernel function produced the most accurate estimates and performed substantially better than the SVM models with the polynomial and sigmoid functions. Furthermore, a remarkable difference was found in the estimated accuracy among different carbon fluxes. Specifically, in the forest ecosystem (CA-Obs site), the optimal ANN model obtained slightly higher performance for gross primary productivity, with R2 = 0.9622, IA = 0.9836, RMSE = 0.6548 g C m−2 day−1, and MAE = 0.4220 g C m−2 day−1, compared with, respectively, 0.9554, 0.9845, 0.4280 g C m−2 day−1, and 0.2944 g C m−2 day−1 for ecosystem respiration and 0.8292, 0.9306, 0.6165 g C m−2 day−1, and 0.4407 g C m−2 day−1 for net ecosystem exchange. According to the findings in this study, we concluded that the proposed ELM and ANFIS models can be effectively employed for estimating terrestrial carbon fluxes.

Understanding the processes that influence the diversity of ecological communities and their susceptibility to invasion by exotic species remains a challenge in ecology. In many systems, a positive relationship between the richness of native species and exotic species has been observed at larger spatial (e.g., regional) scales, while a negative pattern has been observed at local (e.g., plot) scales. These patterns are widely attributed to (1) biotic interactions, particularly biotic resistance, limiting invasions in high‐diversity locations, producing negative local‐scale relationships, and (2) native and exotic richness covarying at larger spatial scales as a function of environmental conditions and heterogeneity, producing positive large‐scale relationships. However, alternative processes can produce similar patterns and need to be critically evaluated to make sound inferences about underlying mechanisms. We aggregated a large dataset of aquatic vegetation surveys from 1,102 Minnesota shallow lakes collected over 13 years to quantify spatial and temporal patterns of community composition. Using those data and additional information on environmental conditions we evaluated evidence for four distinct mechanisms that could drive patterns of native and exotic species richness: biotic resistance, competitive exclusion, environmental filtering and environmental heterogeneity. We found the classic pattern of a negative native‐exotic richness relationship at local scales and a positive relationship at lake scales. However, we found no evidence for local‐scale biotic resistance; instead, competitive exclusion by invasive species appeared to reduce native species richness after locations became invaded. Evaluating the influence of environmental filtering and heterogeneity, we found that native and exotic species occupied somewhat different niches. Invaders were less sensitive to environmental gradients and more tolerant of a wider range of conditions. This segregation of habitat preferences alone could produce a negative local native‐exotic richness relationship and a positive regional pattern without the involvement of biotic interactions. Synthesis. Our findings conflict with established expectations, which come from research predominantly conducted in terrestrial ecosystems. This illustrates the importance of explicitly evaluating underlying mechanisms in diversity‐invasibility research and for comparisons across different types of ecosystems. Identification of different drivers of diversity also has direct implications for decisions about management of freshwater plant communities.

Understanding the patterns and drivers of primary productivity is a major goal of ecology, but little is known about whether the primary productivities of different types of ecosystems—here, lakes and the landscapes in which they are embedded—fluctuate in related ways through time. Due to shared climatic variation and well-known connections between lake and terrestrial ecosystems, such as nutrient and resource subsidies, we hypothesized that interannual fluctuations in aquatic and terrestrial primary productivity indices could be coherent. We also expected that lake and watershed characteristics could modify the strength and nature of primary productivity relationships. We applied wavelet coherence analyses to time series of lake chlorophyll-a and satellite-derived NDVI to examine coherence between lakes and land, and used random forest regression and generalized additive models to evaluate why coherence varies among lakes. There can be substantial coherence between lake and terrestrial primary productivity, but the strength and phase (direction and time lag) of this relationship vary widely, and there were marked differences between short (2–4-year periods of oscillation) and long (> 4-year periods of oscillation) timescales. Across all timescales, variables associated with the connectedness of lakes to their watersheds were consistently the important explanatory variables of the strength and phase of coherence. The patterns observed in this study suggest the importance of cross-ecosystem flows, as opposed to shared climatic variation, in determining temporal coherence between lakes and the landscape.

<p>Selenium is an essential micronutrient required for normal functioning of living organisms. It is distributed in inorganic and organic forms in marine and freshwater systems, in soils, biomass, and atmosphere. Its distribution patterns in terrestrial ecosystems have great diversity. There are biogeochemical provinces with selenium deficiency and toxic concentrations of this trace element. Variability of biochemical characteristics of soil and water in different regions of the world makes significant differences in the content of selenium in plants. The total content of selenium in plants depends on several factors: soil type, pH, redox potential reserves of selenium in soils, selenium compounds form (available or unavailable), precipitation, temperature and growth stage of the plant.</p><p>There is a correlation between the content of selenium in the soil and feed on plants, on the one hand, and animals and birds – on the other. Cereal crops, animals and birds, grown in soils of different types of ecosystems are included in human food chain, therefore food is a major source of selenium for human organism. Selenium status of the population varies, from 10 g<sup>-3</sup>/day in selenium deficient regions to 1400 g-<sup>3</sup>/day in regions with selenium toxicity.</p><p>Large number of countries are characterized by moderate and low levels of selenium intake from foods of plant-grower and stock-raising. Inadequate flow of it in the body (depending on the degree of deficiency) could lead to physiological changes within the normal regulation or significant metabolic disorders or cause the specific diseases, since selenium deficiency is associated with more than 75 different diseases and pain symptoms. The only way of selenium contamination increase in human organism is the selen inclusion in the diet enriched with such micronutrient, like poultry meat.</p><p>The selenium-enriched dietary meat product can be considered as biocorrection food and iIts consumption will contribute to the prevention of hiposelenoz. Nevertheles, there is a narrow range between the recommended rates (50–120 g<sup>-3</sup>/day) and the maximum permissible level of selenium consumption (400 g<sup>-3</sup>/day) while at high concentrations it can cause toxic effects in human body. Further comprehensive environmental and toxicological studies of migration patterns and levels of selenium in the environment should be done to minimize adverse effects to human health associated with dangerous concentrations of selenium.</p>

Effects of diet, climate and physiology on nitrogen isotope abundances in terrestrial foodwebs

Near- and mid-infrared spectroscopy allows for the detection of local patterns of forest soil properties. In combination with dendrometric data, it may be used as a prospective tool for determining soil heterogeneity before setting up long-term forest monitoring experiments. Forest soils and stands generally exhibit higher spatial heterogeneity than other terrestrial ecosystems. This variability needs be taken into account before setting up long-term forest monitoring experiments to avoid multiple interactions between local heterogeneity and the factors tested in the experiment. We hypothesized that raw near- and mid-infrared spectra can be used as an integrated proxy of a large set of soil properties. The use of this method, in combination with dendrometric data, should provide a quick and cost-effective tool for optimizing the design of experimental forest sites. We assessed the local soil heterogeneity at 11 experimental sites in oak and beech stands, which belong to a new forest long-term ecological research (LTER) network. We used near- and mid-infrared spectroscopy in soil and litter samples. The spectra were subjected to principal components analyses (PCA) to determine the intra-site variability of the soil and litter layers. Based on mapped PCA coordinates and basic dendrometric data, it was possible to design the experiment and minimize the interactions between the treatment layout and the tested variables. The method was validated with chemical analyses of the soil. No interaction was detected at the set-up of the experiment between the treatment layout and chemical soil properties (C, N, C/N ratio, pH, CEC, Al, Mg, P2O5, Fe, Mn, Na, and K). Near-infrared (NIR) and mid-infrared (MIR) spectroscopy is a useful tool for characterizing the overall heterogeneity of soil chemical properties. It can be used without any preliminary calibration. In combination with dendrometric data, it provides a reliable method for optimizing LTER plots in different types of ecosystems.

It has been found in the last 3–4 decades that different ecosystems in the tropical regions contributed maximum trace gases (CH4 and N2O) to atmosphere. Terrestrial ecosystems in tropics, sub-tropics and in temperate regions are the well-known sources and sinks of important GHGs (green house gases). Nowadays, developing countries of Asia Pacific regions are contributing a maximum amount of these trace gases at the global scale. Anthropogenic activities and changing environmental conditions alter the dynamics of different ecosystems that stimulate GHGs emission in the last few years. A higher concentration of CO2 and temperature in soil enhance microbial activity. The techniques for sampling, estimation and future prediction of fluxes of these trace gases from different types of ecosystem are still undergoing changes with the advancement in knowledge of microbiology, geology and technology. This review discusses GHG, mainly methane (CH4) and nitrous oxide (N2O) emission estimated from different ecosystems, advancement in estimation technology and the key controlling factors for their emission around the world.