Biological equilibrium in ecosystems 1. A theory of biological equilibrium

In this paper the process of establishing equilibrium in ecosystems is explored, and compared to the process of transformation. This process changes the state of organisms from absent to present, and the reverse, and if functioning randomly on very large numbers of individuals, results in biological equilibrium which can be expressed by the ratio (e?x): 1, withx=1 at Natural Biological Equilibrium (NBE). A model of ecosystems shows that four basic factors are operative in ecosystems: the constraint, or habitat-type; the regulator, or carrying capacity of the substrate; the input, or organisms; and the operator, death. The Theory of Biological Equilibrium (TBE) proposed, postulates that Natural Biological Equilibrium is reached when the individuals in an ecosystem are in dynamic balance with the carrying capacity of the substrate of the ecosystem. The TBE provides the theoretical basis for the Canonical Hypothesis, which postulates that the parameters in eco- systems are fixed, and can be computed from the number of species in the system. The TBE is in agreement with many well-known ecological phenomena, provides the basis for several hypotheses, and forces the rejection of some traditional hypotheses, viz., the hypothesis of competition as a factor in ecosystems.     

Measurement of biological activity in materially closed microbial ecosystems

Gas phase oxygen concentrations of materially closed, energetically open miniature microbial ecosystems were measured periodically. Our results indicate: (i) closed systems remain biologically active for at least 9 years, (ii) Po₂ values might serve as an indicator of stability, (iii) each closed ecosystem seems to seek its own unique final Po₂ state, and (iv) ecosystem response to experimentally depleted Po₂ suggests the presence of positive feedback control.     

基于模型数据融合的中国温带和亚热带典型森林生态系统碳通量模拟

生态系统碳循环过程对水分响应的研究已成为全球变化关注的焦点问题之一。基于长白山温带针阔混交林与千烟洲亚热带人工针叶林观测站2003—2009年生长季的碳通量(NEE)和气象观测数据,综合考虑水分对光合、呼吸作用的影响,构建不同的NEE模型,并应用模型数据融合方法优化模型参数、遴选最适模型,系统分析了水分因子对不同森林生态系统碳循环的影响。结果表明:(1)优化后的模型参数均能被NEE实测数据较好约束。长白山生长季的光合、呼吸参数值均高于千烟洲,未考虑空气饱和水汽压差(VPD)的模型高估了千烟洲温度敏感性参数(Q10)值、低估了千烟洲基础呼吸速率参数(BR)值;(2)仅考虑VPD对光合作用影响的模型是长白山生长季碳通量模拟的最优模型,但模拟精度提高不显著。不同模型间碳通量组分模拟结果差异较小;(3)考虑VPD和土壤含水量对光合、呼吸作用共同影响的模型是千烟洲生长季碳通量模拟的最优模型,并且显著提高了模拟精度。未考虑水分的模型在生长季高估了总生态系统生产力(GEP)总量2.0%(21.85 g C/m~2),同时更大幅度地高估了生态系统呼吸(RE)总量4.4%(38.02 g C/m~2),从而导致NEE总量低估于实测值7.8%(18.55 g C/m~2)。     

陆地生态系统臭氧通量观测和气孔吸收估算研究进展

近地面大气中臭氧(O3)对植物生长发育和产量会产生不良影响。工业和交通排放的增加使得全球地面O3浓度逐年增加,不断升高的O3浓度已开始影响到我国的粮食产量。O3对植物的影响是由于其进入植物体内发生生化反应所引起的,所以需要建立一种考虑到植物生理生态状况的评估指标来评估O3对植物的影响。其中基于O3通量(特别是植物气孔吸收)的评价指标和方法,被认为比传统的基于O3浓度的评价指标和方法更符合O3对植物的影响机理。介绍了O3对生态系统影响评估方法和评价指标,重点评述了生态系统尺度O3通量观测和气孔吸收估算的主要方法以及在不同生态系统上的研究进展分析了我国关于O3对植物和生态系统影响的研究现状,并对未来的研究工作进行了展望。     

Identifying functional species pool of planktonic protozoa for discriminating water quality status in marine ecosystems

It is cost-effective protocol to identify a functional species pool for marine bioassessment by removing redundant species from a raw dataset. The feasibility of functional species pool for discriminating water quality status was studied based on a dataset of 120 samples of ciliated protozoa. From the full 60-species dataset of the whole ciliate communities, a 35-species subset was identified as a functional species pool, the species number, abundance and biodiversity indices of which were significantly correlated with those of the full species dataset. The spatial pattern of the subset was significantly related to the changes in nutrients soluble reactive phosphates (SRP), nitrate/nitrite nitrogen (NO₃-N/NO₂-N) and ammonium nitrogen (NH₄-N). Four indices of the taxonomic diversity (Δ), taxonomic distinctness (Δ*), average in taxonomic distinctness (Δ⁺) and the variation in taxonomic distinctness (Λ⁺) based on this small species pool were significantly correlated with the changes of nutrients NO₃-N and/or (NH₄-N). The paired indices Δ⁺ and Λ⁺ showed a clear decreasing trend of departure from the expected taxonomic pattern. These findings suggest that the 35-species functional species subset may be used as a feasible functional surrogate of ciliated protozoan assemblages for community-based bioassessment in marine ecosystems.     

Biological equilibrium in ecosystems 3. Classification of ecosystems

The Theory of Biological Equilibrium (TBE) is applied to the classification of ecosystems. It is shown that one of the basic factors, the habitat-type, governs the distribution of species through the subfactors climate and substrate in accordance with the Theory of Tolerance. Groups of species can be distinguished which show a very similar distribution, and combinations of species in these groups form the kengroups of classification units, or associations. Because the habitat-type of associations is often fragmented, the classification procedures can be applied to explaint the natural extinction of species, as well as the probability of species extinction through man's actions upon biocenoses.     

陆地生态系统甲烷产生和氧化过程的微生物机理

陆地生态系统存在许多常年性或季节性缺氧环境,如:湿地、水稻土、湖泊沉积物、动物瘤胃、垃圾填埋场和厌氧生物反应器等。每年有大量有机物质进入这些环境,在缺氧条件下发生厌氧分解。甲烷是有机质厌氧分解的最终产物。产生的甲烷气体可通过缺氧-有氧界面释放到大气,产生温室效应,是重要的温室气体。产甲烷过程是缺氧环境中有机质分解的核心环节,而甲烷氧化是缺氧-有氧界面的重要微生物过程。甲烷的产生和氧化过程共同调控大气甲烷浓度,是全球碳循环不可分割的组成部分。对陆地生态系统甲烷产生和氧化过程的微生物机理研究进展进行了概要回顾和综述。主要内容包括:新型产甲烷古菌即第六和第七目产甲烷古菌和嗜冷嗜酸产甲烷古菌的发现;短链脂肪酸中间产物互营氧化过程与直接种间电子传递机制;新型甲烷氧化菌包括厌氧甲烷氧化菌和疣微菌属好氧甲烷氧化菌的发现;甲烷氧化菌生理生态与环境适应的新机制。这些研究进展显著拓展了人们对陆地生态系统甲烷产生和氧化机理的认识和理解。随着新一代土壤微生物研究技术的发展与应用,甲烷产生和氧化微生物研究领域将面临更多机遇和挑战,对未来发展趋势做了展望。     

Microbial carbon use efficiency in different ecosystems: A meta-analysis based on a biogeochemical equilibrium model

Soil microbial carbon use efficiency (CUE) is a crucial parameter that can be used to evaluate the partitioning of soil carbon (C) between microbial growth and respiration. However, general patterns of microbial CUE among terrestrial ecosystems (e.g., farmland, grassland, and forest) remain controversial. To address this knowledge gap, data from 41 study sites (n = 197 soil samples) including 58 farmlands, 95 forests, and 44 grasslands were collected and analyzed to estimate microbial CUEs using a biogeochemical equilibrium model. We also evaluated the metabolic limitations of microbial growth using an enzyme vector model and the drivers of CUE across different ecosystems. The CUEs obtained from soils of farmland, forest, and grassland ecosystems were significantly different with means of 0.39, 0.33, and 0.42, respectively, illustrating that grassland soils exhibited higher microbial C sequestration potentials (p < .05). Microbial metabolic limitations were also distinct in these ecosystems, and carbon limitation was dominant exhibiting strong negative effects on CUE. Exoenzyme stoichiometry played a greater role in impacting CUE values than soil elemental stoichiometry within each ecosystem. Specifically, soil exoenzymatic ratios of C:phosphorus (P) acquisition activities (EEA_C:P) and the exoenzymatic ratio of C:nitrogen (N) acquisition activities (EEA_C:N) imparted strong negative effects on soil microbial CUE in grassland and forest ecosystems, respectively. But in farmland soils, EEA_C:P exhibited greater positive effects, showing that resource constraints could regulate microbial resource allocation with discriminating patterns across terrestrial ecosystems. Furthermore, mean annual temperature (MAT) rather than mean annual precipitation (MAP) was a critical climate factor affecting CUE, and soil pH as a major factor remained positive to drive the changes in microbial CUE within ecosystems. This research illustrates a conceptual framework of microbial CUEs in terrestrial ecosystems and provides the theoretical evidence to improve soil microbial C sequestration capacity in response to global change.     

The relationship between body weight and natural mortality in juvenile and adult fish: a comparison of natural ecosystems and aquaculture

The relationship between body weight and natural mortality in juvenile and adult fish was analysed for different aquatic ecosystems: lakes, rivers, the ocean, and pond, cage and tank aquaculture systems. Mortality was modelled as a power function of weight, and the parameters b (exponent) and M_u (mortality at the unit weight of 1 g) estimated for fish in the six ecosystems, as well as within selected populations, species and families. At the ecosystem level, no significant differences in parameters were found between lakes, rivers and the ocean and a joint mortality-weight relationship for all natural ecosystems was estimated with parameters b=?0.288 (90% CL[?0.315, ?0.261]) and M_u=3.00 (90% CL[2.70, 3.30]) year^?1. Among the culture systems, mortality-weight relationships in ponds and cages were not significantly different and a joint relationship was estimated. The weight exponents of mortality in ponds/cages and tanks were very similar at about b=?0.43, and significantly more negative than in natural ecosystems. Mortalities at unit weight were significantly lower in tanks (0.91 year^?1) than in ponds/cages (2.24 year^?1), and both were significantly lower than in natural ecosystems. No systematic differences were found between the mortality-weight relationships determined for individual populations, species or families, and fish in the respective ecosystems. It is hypothesized that aquaculture mortality-weight relationships indicate the allometric scaling of non-predation mortality, which is therefore more strongly size dependent than predation mortality. If non predation mortality in natural ecosystems shows a similar scaling with body weight, then the allometric exponent of predation mortality must be less negative than that observed for total natural mortality. Implications of the established mortality-weight relationships for aquaculture and culture-based fisheries are discussed.     

Diurnal and Seasonal Variations in Carbon Dioxide Exchange in Ecosystems in the Zhangye Oasis Area,Northwest China

Quantifying carbon dioxide exchange and understanding the response of key environmental factors in various ecosystems are critical to understanding regional carbon budgets and ecosystem behaviors. For this study, CO₂ fluxes were measured in a variety of ecosystems with an eddy covariance observation matrix between June 2012 and September 2012 in the Zhangye oasis area of Northwest China. The results show distinct diurnal variations in the CO₂ fluxes in vegetable field, orchard, wetland, and maize cropland. Diurnal variations of CO₂ fluxes were not obvious, and their values approached zero in the sandy desert, desert steppe, and Gobi ecosystems. Additionally, daily variations in the Gross Primary Production (GPP), Ecosystem Respiration (R_eco) and Net Ecosystem Exchange (NEE) were not obvious in the sandy desert, desert steppe, and Gobi ecosystems. In contrast, the distributions of the GPP, R_eco, and NEE show significant daily variations, that are closely related to the development of vegetation in the maize, wetland, orchard, and vegetable field ecosystems. All of the ecosystems are characterized by their carbon absorption during the observation period. The ability to absorb CO₂ differed significantly among the tested ecosystems. We also used the Michaelis-Menten equation and exponential curve fitting methods to analyze the impact of Photosynthetically Active Radiation (PAR) on the daytime CO₂ flux and impact of air temperature on R_eco at night. The results show that PAR is the dominant factor in controlling photosynthesis with limited solar radiation, and daytime CO₂ assimilation increases rapidly with PAR. Additionally, the carbon assimilation rate was found to increase slowly with high solar radiation. The light response parameters changed with each growth stage for all of the vegetation types, and higher light response values were observed during months or stages when the plants grew quickly. Light saturation points are different for different species. Nighttime R_eco increases exponentially with air temperature. High Q₁₀ values were observed when the vegetation coverage was relatively low, and low Q₁₀ values occurred when the vegetables grew vigorously.     

Regional atmospheric CO2 inversion reveals seasonal and geographic differences in Amazon net biome exchange

Understanding tropical rainforest carbon exchange and its response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate–carbon feedbacks. Of particular importance for the global carbon budget is net biome exchange of CO₂ with the atmosphere (NBE), which represents nonfire carbon fluxes into and out of biomass and soils. Subannual and sub‐Basin Amazon NBE estimates have relied heavily on process‐based biosphere models, despite lack of model agreement with plot‐scale observations. We present a new analysis of airborne measurements that reveals monthly, regional‐scale (~1–8 × 10⁶ km²) NBE variations. We develop a regional atmospheric CO₂ inversion that provides the first analysis of geographic and temporal variability in Amazon biosphere–atmosphere carbon exchange and that is minimally influenced by biosphere model‐based first guesses of seasonal and annual mean fluxes. We find little evidence for a clear seasonal cycle in Amazon NBE but do find NBE sensitivity to aberrations from long‐term mean climate. In particular, we observe increased NBE (more carbon emitted to the atmosphere) associated with heat and drought in 2010, and correlations between wet season NBE and precipitation (negative correlation) and temperature (positive correlation). In the eastern Amazon, pulses of increased NBE persisted through 2011, suggesting legacy effects of 2010 heat and drought. We also identify regional differences in postdrought NBE that appear related to long‐term water availability. We examine satellite proxies and find evidence for higher gross primary productivity (GPP) during a pulse of increased carbon uptake in 2011, and lower GPP during a period of increased NBE in the 2010 dry season drought, but links between GPP and NBE changes are not conclusive. These results provide novel evidence of NBE sensitivity to short‐term temperature and moisture extremes in the Amazon, where monthly and sub‐Basin estimates have not been previously available.     

Meta-analysis of diazotrophic signatures across terrestrial ecosystems at the continental scale

Biological nitrogen fixation performed by diazotrophs forms a cornerstone of Earth's terrestrial ecosystem productivity. However, the composition, diversity and distribution of soil diazotrophs are poorly understood across different soil ecosystems. Furthermore, the biological potential of the key diazotroph species in relation to key environmental parameters is unknown. To address this, we used meta-analysis approach to merge together 39 independent diazotroph amplicon sequencing (nifH gene) datasets consisting of 1988 independent soil samples. We then employed multiple statistical analyses and machine-learning approaches to compare diazotroph community differences and indicator species between terrestrial ecosystems on a global scale. The distribution, composition and structure of diazotroph communities varied across seven different terrestrial ecosystems, with community composition exhibiting an especially clear effect. The Cyanobacteria were the most abundant taxa in crust ecosystems (accounting for ~45% of diazotrophs), while other terrestrial ecosystems were dominated by Proteobacteria, including Alpha-, Beta- and Gamma-Proteobacteria (accounting for ~70% of diazotrophs). Farmland ecosystems harboured the highest and crust ecosystems the lowest alpha and phylogenetic diversities. Azospirillum zeae, Skermanella aerolata and four Bradyrhizobium species were identified as key indicator species of potential diazotroph activity. Overall, diazotroph abundances and distribution were affected by multiple environmental parameters, including soil pH, nitrogen, organic carbon, C:N ratio and annual mean precipitation and temperature. Together, our findings suggest that based on the relative abundance and diversity of nifH marker gene, diazotrophs have adapted to a range of environmental niches globally.     

Biological nitrogen fixation by alternative nitrogenases in terrestrial ecosystems: a review

Biological nitrogen fixation (BNF), a key reaction of the nitrogen cycle, is catalyzed by the enzyme nitrogenase. The best studied isoform of this metalloenzyme requires molybdenum (Mo) at its active center to reduce atmospheric dinitrogen (N₂) into bioavailable ammonium. The Mo-dependent nitrogenase is found in all diazotrophs and is the only nitrogenase reported in diazotrophs that form N₂-fixing symbioses with higher plants. In addition to the canonical Mo nitrogenase, two alternative nitrogenases, which use either vanadium (V) or iron (Fe) instead of Mo are known to fix nitrogen. They have been identified in ecologically important groups including free-living bacteria in soils and freshwaters and as symbionts of certain cryptogamic covers. Despite the discovery of these alternative isoforms more than 40 years ago, BNF is still believed to primarily rely on Mo. Here, we review existing studies on alternative nitrogenases in terrestrial settings, spanning inland forests to coastal ecosystems. These studies show frequent Mo limitation of BNF, ubiquitous distribution of alternative nitrogenase genes and significant contributions of alternative nitrogenases to N₂ fixation in ecosystems ranging from the tropics to the subarctic. The effect of temperature on nitrogenase isoform activity and regulation is also discussed. We present recently developed methods for measuring alternative nitrogenase activity in the field and discuss the associated analytical challenges. Finally, we discuss how the enzymatic diversity of nitrogenase forces a re-examination of existing knowledge gaps and our understanding of BNF in nature.

     

A laboratory study on biochemical degradation and microbial utilization of organic matter comprising a marine diatom,land grass,and salt marsh plant in estuarine ecosystems

We studied the biochemical degradation of organic matter comprising marine diatom, land grass, and salt marsh plant in estuarine ecosystems in two laboratory microcosms consisting of estuarine sediments and coastal seawater. The materials were incubated separately and together under controlled oxic and anoxic conditions to test effects of co-metabolism and redox on overall degradation of organic matter. We followed variations of bulk parameters [total organic carbon (TOC), total nitrogen (TN), C/N ratio, δ¹³C_TOC, and δ¹⁵N_TN], fatty acid concentrations, and compound-specific δ¹³C values over 3 months. Coexistence of marine diatom (relatively labile) with land grass/salt marsh plant (relatively refractory) in the microcosms yielded a negative co-metabolism effect (retardation rather than acceleration) on the overall degradation of organic matter. The ratios of oxic to anoxic degradation rate constants (k _ox/k _an) of TOC and most fatty acids were in a range of 1.1–1.7, implying that redox conditions per se had a limited influence on degradation of fresh organic materials in estuarine ecosystems. Variations of two bacteria-specific fatty acids (iso- and anteiso-15:0) and their δ¹³C values indicated that bacterial metabolism could use organic carbon (OC) from any available material when only one single-source material was dominant in the ecosystems. However, bacteria probably utilized OC preferentially from labile marine diatom when multiple-source materials were almost equally present in the ecosystems.     

Experimental studies of thermal denaturation of the Na-DNA system with respect to Manning's model

The sodium and chloride activity coefficients in DNA solution were measured by selective electrodes. These experiments were performed for native and thermally denatured DNA. The ratio of activities in helix and coil states were compared with those given by Manning's model. These results are in good agreement with the theoretical values.We also compare the experimental values of the charge parameter XXX of DNA in the helix (XXX_h) and coil (XXX_c) configurations with the theoretical parameters appearing in Manning's model and which have been adjusted to correspond with the known conformation of the molecule. From this comparison, we deduce the change of enthalpy (ΔH)T_m at the temperature of denaturation (T_m) of DNA.The value of (ΔH)T_m thus calculated is smaller than the theorstical value and comparable with that observed experimentally by Privalov et al.     

Guano deposition and nutrient enrichment in the vicinity of planktivorous and piscivorous seabird colonies in Spitsbergen

The crucial role of seabirds in the enrichment of nutrient-poor polar terrestrial ecosystem is well-known. However, no studies have examined the potentially different impacts associated with piscivorous and planktivorous bird colonies on the surrounding tundra soils. Therefore, we compared guano deposition and physical and chemical parameters of soil near two large seabird colonies, one of planktivorous little auks (Alle alle) and the other comprising piscivorous Brunnich’s guillemots (Uria lomvia) and kittiwakes (Rissa tridactyla). The two colonies generated similar levels of guano deposition, with the intensity of deposition decreasing away from the colony. Guano deposition adjacent to both colonies was considerably higher than that in control areas. The increased guano supply around colonies significantly enhanced soil conductivity, nitrogen (NO₃ ^?, NH₄ ⁺), potassium (K⁺), and phosphate (PO₄ ^3?) ion concentrations and led to reduced pH values. Guano deposition explained 84 % (piscivorous colony) and 67 % (planktivorous colony) of the total variation in the tested soil parameters. Planktivore and piscivore colonies affected adjacent tundra in different ways. The phosphate content and pH value of soil influenced by piscivores were significantly higher than values measured in planktivore-influenced soil. The gradient of guano deposition and associated ion content in the soil decreased more rapidly with distance from the piscivore colony. Climate-induced changes in populations of planktivorous and piscivorous seabirds are expected in the study region and may therefore have substantial consequential effects on Arctic terrestrial ecosystems.     

Global net biome CO2 exchange predicted comparably well using parameter–environment relationships and plant functional types

Accurate estimation and forecasts of net biome CO₂ exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based “environmental filtering” (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model–data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby “true” parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels—a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed “true” values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.     

Nutrient limitation of bacterial production in clear water Amazonian ecosystems

The aim of this research was to determine the main limiting nutrient (carbon, nitrogen or phosphorus) to bacterial production in different clear water Amazonian ecosystems during the high water period, when there is influence of the flooded land, mainly as sources of organic matter. Five stations were sampled in three clear water ecosystems: Trombetas River, Lake Batata and Caranã Stream. We estimated in each station the nutrient concentration, bacterial production and bacterial abundance. The experiment was set up with GF/F filtered water from all stations together with additions of glucose (400 M C), KNO₃ (15 M N) and KH₂PO₄ (5 M P) in accordance with each treatment (C, N, P ,CN, CP, NP, CNP and no amends). Bacterial production was estimated after 24 h of incubation. We observed that the values of bacterial production after additions of phosphate alone (P treatment) were 2- to 6-fold greater than the values measured in control flasks. Additions of nitrate (N treatment) and glucose alone (C treatment) had no effect on the bacterial production in four out of five ecosystems studied. However, additions of glucose with phosphate (CP treatment) strongly stimulated bacterial production in all ecosystems studied, including treatments with phosphate addition only. We conclude that phosphorus is the main limiting nutrient to bacterioplankton production in these clear water Amazonian ecosystems during the high water period. In addition, we conclude that, together with phosphorus, additions of glucose stimulated the bacterial production mainly due to the low quality of the carbon pool present in these ecosystems.     

Theoretical considerations and modeling of chemical inactivation of microorganisms: Inactivation of Giardia Cysts by free chlorine

Chemical inactivation of microorganisms is a common process widely employed in many fields such as in treatment of water, preservation in food industry and antimicrobial treatments in healthcare. For economy of applications and efficiency of treatment establishment the minimum dosage of breakpoint in the chemical application becomes essential. Even though experimental investigations have been extensive, theoretical understanding of such processes are demanding. Commonly employed theoretical analyses for the inactivation of microorganisms and depletion of chemicals include kinetics expressing the rates of depletion of chemical and microorganisms. The terms chemical demand (x) and specific disinfectant demand (α) are often used in theoretical modeling of inactivation. The value of specific disinfectant demand (α) has always been assumed to be a constant in these models. Intracellular concentration built up within the cells of the microorganisms during inactivation could lead to possible weakening effects of microorganisms thereby requiring lower doses as disinfection proceeds makes the assumption of constant α inaccurate. Model equations are formulated based on these observations co-relating the parameters α and x with a progressive inactivation (N/N₀). The chemical concentration (C) is also presented in terms of the inactivation time (t) and the survival ratio (N/N₀) for given pH and temperature conditions. The model is examined using experimentally verified Ct data of Giardia Cysts/chlorine system. The respective values of x for different survival ratios were evaluated from the data using MatLab software. Proposed model correlating for the disinfectant demand (x) with the survival ratio (N/N₀) fits satisfactorily with those evaluated from data. The rate constants for different pH and temperature conditions are evaluated which showed compatibility with the Arrhenius model. The dependence of frequency factors with pH indicated compatibility with accepted models. The Ct values regenerated with the kinetic data shows a very accurate fit with published data.     

Carbon quality and soil microbial property control the latitudinal pattern in temperature sensitivity of soil microbial respiration across Chinese forest ecosystems

Understanding the temperature sensitivity (Q₁₀) of soil organic C (SOC) decomposition is critical to quantifying the climate–carbon cycle feedback and predicting the response of ecosystems to climate change. However, the driving factors of the spatial variation in Q₁₀ at a continental scale are fully unidentified. In this study, we conducted a novel incubation experiment with periodically varying temperature based on the mean annual temperature of the soil origin sites. A total of 140 soil samples were collected from 22 sites along a 3,800 km long north–south transect of forests in China, and the Q₁₀ of soil microbial respiration and corresponding environmental variables were measured. Results showed that changes in the Q₁₀ values were nonlinear with latitude, particularly showing low Q₁₀ values in subtropical forests and high Q₁₀ values in temperate forests. The soil C:N ratio was positively related to the Q₁₀ values, and coniferous forest soils with low SOC quality had higher Q₁₀ values than broadleaved forest soils with high SOC quality, which supported the “C quality temperature” hypothesis. Out of the spatial variations in Q₁₀ across all ecosystems, gram‐negative bacteria exhibited the most importance in regulating the variation in Q₁₀ and contributed 25.1%, followed by the C:N ratio (C quality), fungi, and the fungi:bacteria ratio. However, the dominant factors that regulate the regional variations in Q₁₀ differed among the tropical, subtropical, and temperate forest ecosystems. Overall, our findings highlight the importance of C quality and microbial controls over Q₁₀ value in China's forest ecosystems. Meanwhile, C dynamics in temperate forests under a global warming scenario can be robustly predicted through the incorporation of substrate quality and microbial property into models.