Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.     

Pressure cookers or pressure valves: Do roads lead to deforestation in China?

The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1 km² (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation.     

季节性雪被对青藏高原东缘高寒草甸土壤氮矿化的影响

依据自然雪被分布的差异,在青藏高原东缘高寒草甸中设置3条样带(即深雪、中等厚度雪被和浅雪),于2008年的秋冬过渡期,连续监测各样带中的雪被厚度和土壤温度,并采用原位培养法测定每月的土壤氮素氨化、硝化和矿化速率,以研究不同厚度雪被对高寒草甸土壤氮矿化的影响.结果表明,月均土温、每月日最高土温均值分别与雪被厚度极显著相关,二次函数关系拟合较好(R2=0.576,0.685),且根据每月日最高土温均值与雪被厚度的二次函数关系方程可知,25 cm厚的雪被可以起到较好的隔绝效果;土壤含水量受雪被厚度和土壤温差两个因素的显著影响.在秋冬过渡期末,浅雪梯度下土壤硝态氮含量显著降低,且雪被下的净氮矿化速率与月均土温、每月日最高土温均值、每月日最低土温均值都分别呈极显著相关,二次函数关系拟合较好(R2=0.589,0.541,0.601).研究表明,不同厚度的雪被对土壤温度和含水量影响显著,从而显著地影响着土壤氮的矿化,深雪更有利于氨化、硝化和氮矿化.图7表2参36     

浅议郴州市废弃矿山生态恢复途径

郴州市矿产资源丰富,采矿业发达,矿山资源开发导致了环境污染、生态破坏等一系列问题,矿山废弃地的生态恢复及景观重建已成为郴州市经济和社会发展需要迫切解决的问题之一.概括地介绍了郴州市的基本状况,分析了郴州市采矿业的无序发展对生态环境的影响,并针对矿山废弃地环境的污染问题,探索性地提出了郴州市废弃矿山生态恢复的途径.     

环境卫星CCD与Landsat TM影像质量及生态监测应用比对研究——以青海湖区域为例

针对环境卫星 CCD 影像,结合影像质量评价、专题制图、土地利用/覆被解译以及常用植被指数构建,以青海湖区域为例,与Landsat TM影像进行比对研究。结果表明,在与TM影像质量评价参数比较中,TM影像较优,而环境卫星影像具有很大的改善空间;在对地物判译中,环境卫星影像色彩稍暗淡,但对大多数地物解译判读的边界更清晰;环境卫星覆盖度大,区域制图的优势非常明显;生态监测定量遥感常用的植被指数比较中两种数据大致相同。     

长白山的台风灾区范围及植被恢复动态——基于遥感技术的研究

通过对1985年和1987年Thematic Mapper(TM)影像中提取出的归一化植被指数进行对比分析,提取了1986年长白山自然保护区内遭受台风袭击后的灾区范围,并通过比较1988年和2007年的TM影像,分析了风灾区的植被恢复过程。同时,结合该地区的地形、水文、土壤和公路数据对风灾区的植被恢复进行了驱动力分析。发现地形驱动因子与风灾区的恢复程度呈高度相关,随着高程、坡度和平地所占比例的减少,恢复程度逐渐变好;此外水文、土壤和人类活动都对风灾区的植被恢复产生一定影响,另外人工干预恢复对植被生长也起着积极的作用。研究结果可供风灾区内植被的进一步恢复和森林防火工作参考。     

西南高山峡谷区植被变化及影响因素分析

西南高山峡谷区是我国典型生态脆弱区,认识其植被变化特征及影响因素可以为西南高山峡谷区生态环境建设对策的制定提供理论依据,对实现区域经济、环境以及生态和谐统一发展,具有一定的现实意义.基于2000~2019年NDVI、社会经济因子和自然因子数据集,采用一元线性回归法、Hurst指数、地理探测器模型和变异系数等方法分析了西南高山峡谷区NDVI时空变化及稳定性特征,并探讨了NDVI空间分异影响因素.结果表明：①空间上看,植被呈现东南高,西北低的分布格局,中高和高植被覆盖的区域面积占比71.71%,植被覆盖总体处于较高水平.时间上看,植被呈现改善趋势的区域面积占比85.90%,恢复效果明显,且未来植被变化趋势还将以改善为主.②高程、植被类型和土壤类型是影响NDVI空间分异的主导因子,q值均不低于0.40;气温和降雨量为次要因子,q值分别为0.274和0.225.双因子交互作用增强了单因子的影响力,表现为双因子增强和非线性增强两种关系,其中高程∩植被类型组合q值最高为0.714,其次是高程∩土壤类型组合q值为0.688.③研究时段内NDVI整体稳定性较好,低波动变化和较低波动变化的区域面积占比为89.95%;而中等以上波动的区域面积占比为10.05%,集中在海拔高、气温低、降雨少、土壤贫瘠和植被较差等生态环境相对脆弱的区域.植被变化是多因素综合作用的结果,需因地制宜,有针对性地采取不同策略修复西南高山峡谷区生态环境.     

水蚀环境植被恢复对土壤有机碳固存和团聚体稳定的影响：Meta分析

为明确水蚀环境不同条件下植被恢复策略对土壤固碳和团聚体稳定性的影响差异,通过搜集91篇论文的实验数据,以农田(或裸地)为对照,基于Meta分析评估土壤有机碳(SOC)储量和团聚体稳定性对水蚀环境退耕还林/还草措施的响应.结果表明：(1)退耕还林/还草均有利于提高SOC储量,改善土壤团聚体稳定性,但两者的优势功能存在差异,还林的固碳效应强于还草,而还草对增强团聚体稳定性的作用更强.(2)多因素Meta分析表明显著影响SOC的因素有：恢复年份、土壤黏粒含量、植被覆盖度、年平均降雨(MAP)、年平均气温(MAT)和土壤深度.其中植被恢复对SOC储量的正向效应随着植被覆盖率增加而提高;草地恢复在土壤黏粒含量为20%～32%下对SOC储量的提高效应更显著,在MAP>800 mm或MAT<15℃条件下更易促进草地固碳效应,不同恢复年限下的草地固碳效应无显著变化;而林地恢复在土壤黏粒含量>32%下对SOC储量的提高效应更显著,气候条件对林地SOC储量无限制性影响,林地恢复下的SOC储量与恢复年限间存在正向效应.(3)植被恢复在黏粒含量为20%～32%时对平均重量直径(MWD)和平均...     

黄土高原不同植被带人工刺槐林土壤团聚体稳定性及其化学计量特征

为研究黄土高原不同植被带对土壤团聚体稳定性及团聚体化学计量变化特征的影响,本研究选取黄土高原不同植被带人工刺槐林地土壤为研究对象,分析了不同粒径团聚体含量,团聚体化学计量及稳定性指标.结果表明, 2 mm和0. 25～2 mm粒径团聚体含量,机械团聚体的平均重量直径(E_(MWD))和机械团聚体的几何平均直径(E_(GMD))表现为森林带森林草原带草原带,而0. 053～0. 25 mm粒径团聚体含量和可蚀性因子K呈现相反的变化特点;各粒径团聚体有机碳和全氮含量在3个植被带整体表现为森林带显著高于森林草原带和草原带,而全磷含量在各植被带间无明显变化规律;有机碳和全氮含量在草原带以0. 053 mm和0. 25～2 mm粒径占绝对优势,在森林草原带以0. 053～0. 25 mm和0. 25～2 mm粒径为主,而森林带各粒径间均无显著差异;草原带和森林草原带0. 053 mm粒径全磷含量最高,而森林带全磷含量在各粒径间无显著差异;0. 053 mm和0. 053～0. 25 mm粒径团聚体C∶N值以草原带和森林草原带高于森林带,而0. 25～2 mm和 2 mm粒径在3个植被带间无显著差异;各粒径C∶P和N∶P值以森林带显著高于森林草原带和草原带.综上可见,土壤团聚体稳定性和团聚体化学计量在3个植被带间存在较大差异,团聚体稳定性和团聚体有机碳、全氮含量整体表现为森林带显著高于森林草原带和草原带.