热振森林大型土壤动物群落特征及其影响因素

为了解西藏拉萨市林周县热振国家森林公园不同海拔大型土壤动物群落的空间分布特征及其与环境因子的关系,于2021年7月(夏季)根据其地理特征设置了三个不同海拔共9个样地.采用手捡法对大型土壤动物进行收集,并将其保存在75%酒精的收集管中,同时测定相应的环境因子.共捕获大型土壤动物1427个,经形态学鉴定隶属于2门5纲15目21科,其中优势类群为姬马陆科(Julidae)和蚁科(Formicidae),占总捕获量的66.0%.常见类群共10类,占总捕获量的31.3%;稀有类群占总捕获量的2.7%.热振国家森林公园大型土壤动物的类群、Shannon多样性指数、均匀度指数和优势度指数在三个不同海拔之间无显著性差异(P>0.05).大型土壤动物群落Jaccard相似性系数位于0.15~0.77.Pearson相关性结果显示,大型土壤动物个体数与海拔呈极显著负相关(P<0.01),与土壤温度和pH呈显著正相关(P<0.05);冗余分析显示,排序轴1和轴2共同解释了的类群组成变化的55.0%,全磷(TP)和有效磷(AP)为显著性解释变量,对大型土壤动物群落的解释率分别为29.6%和18.5%,是影响大型土壤动物群落的主要环境因子.     

Mn@海藻酸微球吸附去除盐酸四环素及其类Fenton再生

以海藻酸钠为基体,制备出了Mn@海藻酸复合吸附剂.采用FE-SEM、EDS和FT-IR对产品的结构进行了表征,研究了Mn@海藻酸复合吸附剂吸附去除盐酸四环素水溶液的过程,主要考察了溶液初始浓度、p H和吸附时间对盐酸四环素吸附过程的影响,同时进行了动力学、等温模型和热力学分析,并对吸附剂的再生进行了评价.结果表明,盐酸四环素溶液初始浓度越大,平衡吸附量越大;强酸不利于Mn@海藻酸微球吸附反应的进行;随着时间的延长,吸附量呈逐渐增加的趋势.动力学模拟结果表明,吸附过程符合准二级动力学模型,等温吸附曲线符合Langmuir等温模型;热力学参数ΔG0,ΔH0,ΔS0,表明该吸附过程为自发吸热过程.通过构造Fenton-like反应体系,表面富集有盐酸四环素的Mn@海藻酸微球吸附剂可有效实现原位再生,重复使用.研究结果对含盐酸四环素废水的处理提供重要的理论依据.     

二氧化钛对地下水中砷硅的吸附及再生回用

二氧化钛(TiO_2)材料作为性能优异的吸附材料被广泛应用于地下水砷(As)的去除中.结果表明,地下水中共存硅离子(Si)会占据TiO_2的吸附位点,从而影响As的吸附及TiO_2材料的再生回用.本文通过同步辐射扩展X射线吸收精细结构(EXAFS)研究了Si对As微观吸附机制的影响,表明Si的存在不会影响As在TiO_2上的吸附构型.衰减全反射傅里叶变换红外光谱(ATR-FTIR)原位研究表明Si在TiO_2表面形成Si单体、低聚体和多聚体,从而竞争As的吸附位点,同时增加TiO_2再生的难度.为了实现TiO_2材料的高效再生,本研究进一步考察了氟化钠(NaF)对TiO_2表面Si的脱附效果,发现NaF可以有效地洗脱Si,再生后的TiO_2吸附性能稳定.ATR-FTIR光谱原位分析发现,NaF的加入可有效脱附TiO_2表面的Si单体和多聚体.当利用NaF和Na OH共同洗脱TiO_2表面的As和Si时,3次循环中As的脱附率为86.8%~100.3%,Si的脱附率为67.9%~82.0%.本研究为地下水砷硅共吸附材料的再生提供了一种有效方法.     

生物质基纳米HZO杂化材料的研制及其除磷特性

采用3-氯-2-羟丙基三甲基氯化胺(CTA)对生物质秸秆进行胺基化改性获得St-N',通过正交试验确定其最佳合成条件为Na OH质量分数30%、CTA体积100 m L、反应温度80℃、反应时间3h.通过原位沉积法将纳米水合氧化锆(HZO)固载于St-N'内部,制备得到生物质基纳米HZO杂化材料St-N'-Zr.SEM、TEM、XRD与BET等技术表明纳米HZO已成功负载于StN'内部,以无定形为主,分布均匀,粒径为50~100 nm.批次吸附实验结果表明,St-N'-Zr吸附磷酸根符合Langmuir吸附等温模型,最大吸附量为33.90 mg·g-1;最佳吸附pH为1.8~6.0,可用于酸性水体除磷;强竞争离子体系中,磷去除率始终高于初始吸附量的70%,性能明显优于商用阴离子交换树脂D-201,吸附选择性良好.经10次吸附-解吸循环,再生性能良好,表明在水体磷污染深度治理领域具有一定应用潜力.     

新型铁铜锰复合氧化物颗粒吸附剂As(Ⅲ)吸附行为与机制研究

以壳聚糖为黏合剂,采用包覆法制备了一种新型除砷吸附剂——颗粒状铁铜锰复合氧化物(GFCM). GFCM吸附剂为不完全球状,直径0.7～1.0 mm,可以有效地将As(Ⅲ)氧化成As(V),并对形成的As(V)具有良好的吸附效果. GFCM对As(Ⅲ)的最大吸附容量(pH 7.0)为56.5 mg·g~(-1),显著优于目前已报道的多数颗粒状除砷吸附剂.溶液pH在5.0～9.0范围内, GFCM对As(Ⅲ)均有较好的吸附效果,离子强度则对砷吸附效果影响较小.共存阴离子对As(Ⅲ)吸附具有抑制作用,影响的大小顺序为:PO■ SiO■ CO■ Cl~- SO■.吸附As(Ⅲ)后的GFCM可用NaOH溶液进行有效脱附再生,可重复使用.在As(Ⅲ)的去除过程中,吸附剂中锰氧化物的主要作用是氧化As(Ⅲ),铁氧化物与铜氧化物的主要作用是吸附As(Ⅲ)与氧化形成的As(V),且铜氧化物有助于增强GFCM的砷吸附性能.     

An exploratory assessment of the attitudes of Chinese wood products manufacturers towards forest certification

Interviews with Chinese forest products manufacturers were conducted to explore their attitudes towards forest certification and related issues. Participants comprised owners, CEOs, and managers in 20 Chinese wood products companies, including producers of furniture, doors, flooring, and various engineered wood products. The interviews were used to analyze the extent to which participants were considering adopting forest certification and what might motivate such a decision. This was done by assessing their awareness and knowledge of certification. The results indicated that participants' understanding of forest certification was extremely low, despite major efforts in China to raise awareness of the issue. Potential economic benefits were the most frequently cited reason to adopt certification, including gaining or maintaining competitive advantage over their industry counterparts, improved access to both domestic and export markets, better customer recognition, and enhanced corporate responsibility practices. Some interviewees (3 out of 20) considered that certification would become a mandatory requirement or industry standard, and that this would be the only viable motivation for certification given that the financial benefits were potentially limited. According to the participants, the main differences between certified and uncertified wood products operations related to improved market access and public image. Interviewees felt that cooperation between and support from governments and the forest industry would enable the enhanced awareness of certification amongst manufacturers and the general public. This, in turn, could serve to stimulate demand for certified products.     

Shifting cultivation, forest fallow, and externalities in ecosystem services: Evidence from the Eastern Amazon

This study examines the value of fallow ecosystem services in shifting cultivation, including hydrological externalities that may affect other farms. Using farm-level survey data from the Brazilian Amazon, I estimate a production function to assess the value of forest fallow and test whether it provides local externalities to agricultural production. Soil quality controls, instrumental variables, and spatial econometric approaches help address endogeneity issues. I use GIS data on external forest cover at the farm level and model the hydrological externality as an upstream-to-downstream process. The estimated parameters indicate that fallow contributes significantly to productivity both on farm and downstream. In addition, most farms allocate sufficient land to fallow, accounting for both the value of hydrological spillovers and the opportunity cost of land left out of cultivation. These results suggest that farming communities may have some self-interest in preserving forest cover locally—a finding that may bolster policy efforts aimed at conserving tropical forests for their global public goods.     

Development of the gap model ZELIG-CFS to predict the dynamics of North American mixed forest types with complex structures

When the development of gap models began about three decades ago, they became a new category of forest productivity models. Compared with traditional growth and yield models, which aim at deriving empirical relationships that best fit data, gap models use semi-theoretical relationships to simulate biotic and abiotic processes in forest stands, including the effects of photosynthetic active radiation interception, site fertility, temperature and soil moisture on tree growth and seedling establishment. While growth and yield models are appropriate to predict short-term stemwood production, gap models may be used to predict the natural course of species replacement for several generations. Because of the poor availability of historical data and knowledge on species-specific allometric relationships, species replacement and death rate, it has seldom been possible to develop and evaluate the most representative algorithms to predict growth and mortality with a high degree of accuracy. For this reason, the developers of gap models focused more on developing simulation tools to improve the understanding of forest succession than predicting growth and yield accurately.In a previous study, the predictions of simulations in two southeastern Canadian mixed ecosystem types using the ZELIG gap model were compared with long-term historical data. This exercise highlighted model components that needed modifications to improve the predictive capacity of ZELIG. The updated version of the model, ZELIG-CFS, includes modifications in the modelling of crown interaction effects, survival rate and regeneration. Different algorithms representing crown interactive effects between crowns were evaluated and species-specific model components that compute individual-tree mortality probability rate were derived. The results of the simulations were compared using long-term remeasurement data obtained from sample plots located in La Mauricie National Park of Canada in Quebec. In the present study, three forest types were studied: (1) red spruce-balsam fir-yellow birch, (2) yellow birch-sugar maple-balsam fir, and (3) red spruce-balsam fir-white birch mixed ecosystems. Among the seven algorithms that represented individual crown interactions, two better predicted the changes in basal area and individual-tree growth: (1) the mean available light growing factor (ALGF), which is computed from the proportion of light intercepted at different levels of individual crowns adjusted by the species-specific shade tolerance index, and (2) the ratio of mean ALGF to crown width. The long-term predicted patterns of change in basal area were consistent with the life history of the different species.     

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning

In order to simulate forest growth response to pre-commercial thinning (PCT), TRIPLEX1.0 - a process-based model designed to predict forest growth as well as carbon (C) and nitrogen (N) dynamics - was modified and improved to also simulate managed forest ecosystem thinning practices. A three-parameter Weibull distribution model was integrated to simulate thinning treatments within the newly developed TRIPLEX-Management model. The thinning intensity component within the model allows users to simulate thinning treatments by applying basal area, stand density and volume to quantify thinning intensity. Natural mortality decreased following thinning due to an increase in growing space for residual stems. Predicted litterfall pools also increased after thinning events took place. The TRIPLEX-Management model was tested against published observational data for Jack Pine (Pinus banksiana Lamb.) stands subjected to PCT in Northwestern Ontario, Canada. The coefficients of determination (R²) between the predicted and observed variables including stand density, mean DBH (diameter at breast height), the quadratic mean DBH, total volume and merchantable volume as well as belowground, aboveground, and total biomass ranged from 0.50 to 0.88 (n = 20, P < 0.001) with the exception of mean tree height (R² = 0.25, n = 20, P < 0.05). Overall, the Willmott index of agreement between predicted and observed variables ranged from 0.97 to 1.00. Results show that the TRIPLEX-Management model is generally capable of simulating growth response to PCT for Jack Pine stands.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.