竹茶混交模式对表层土壤有机碳储量及组分的影响

为探究毛竹林下种植茶树对土壤有机碳储量与碳组分的影响,该研究以毛竹纯林、竹茶混交林和常绿阔叶林为研究对象,采集这3种林分类型的表层(0～10 cm)土壤,测定土壤有机碳(SOC)、碳组分、生物与非生物因素指标。结果表明:(1)竹茶混交林林下植物多样性相较于毛竹纯林显著降低,但其土壤有机碳密度(22.54±2.09)t·hm^-2、碳组分与毛竹纯林无显著差异(P>0.05)。竹茶混交林的矿物结合态有机碳(MOC)为(20.13±1.83)g·kg^-1,占总有机碳的92.66%。常绿阔叶林土壤有机碳密度比竹茶混交林和毛竹纯林高土壤有机碳密度分别高41.15%和41.00%(P<0.05)。(2)3种林分类型土壤微生物量碳(MBC)含量范围为0.58～3.08 g·kg^-1,土壤16S rRNA丰度范围为2.18×10¹⁰ ～5.65×10¹⁰copies·g^-1,固碳基因cbbL丰度范围为0.37×10⁸～ 1.10 ×10⁸ copies·g^-1,土壤微生物碳利用效率范围为0.03～0.28; 3种林分类型之间微生物相关指标不存在显著差异(P>0.05)。(3)3种林分类型SOC与土壤pH、砂粒含量和地上凋落物生物量呈显著负相关,与土壤黏粒含量、粉粒含量、总氮、C:N、总磷和铵态氮含量呈显著正相关(P<0.05)。(4)就不同碳组分而言,颗粒有机碳(POC)和MOC均与土壤pH、砂粒含量和根系生物量呈显著负相关,与土壤含水量、黏粒含量、粉粒含量、总氮、C:N、总磷和铵态氮含量呈显著正相关(P<0.05)。综上表明,竹茶混交改造会造成原生毛竹纯林林下植被多样性下降,但并未造成土壤碳储量下降; 而相较于常绿阔叶林,毛竹经营措施需要改进,以提升其碳汇效益。     

1980-2010年北京市农用地碳储量对土地利用变化的响应

分析北京市农用地碳储量对土地利用变化的响应,对快速城市化和工业化区域及全国农用地低碳利用调控具有重要意义。利用1980年第二次土壤普查数据与2010年测土配方施肥项目成果土壤数据核算北京市农用地表层土壤碳储量,利用生物量遥感信息（NDVI）模型反演林地、草地植被碳储量,对北京市土地利用变化造成的农用地碳储量变化进行研究,结果表明：1）1980-2010年,北京市农用地碳储量由75.29 Tg-C增至81.13Tg-C,增加5.83 Tg-C,其中,土壤碳储量减少7.51 Tg-C,植被碳储量增加13.34 Tg-C;2）30年间,北京市农用地面积减少14.11×10⁴ hm²,其中,耕地流失最为显著,主要去向为建设用地和林地,林地面积略有增加;3）北京市用地类型保持不变的农用地土壤碳储量减少297.63×10⁴ t,植被碳储量增加1095.21×10⁴ t,共计增加797.58×10⁴ t,其中,用地类型保持不变的耕地、林地碳储量增加,草地碳储量减少;4）30年间,土地利用类型转化使北京市农用地土壤碳储量减少75.71×10⁴ t,植被碳储量增加212.49×10⁴ t,共计增加136.78×10⁴ t,其他用地类型转为林地使碳储量增加,有利于碳汇的形成,林地转出为其他用地类型均会造成一定碳排放;5）平原造林、退耕还林等工程有利于增加北京市农用地固碳量。未来北京市可通过控制农用地面积减少量,优化农用地内部结构,降低用地类型间的转换频率以提高农用地碳储量。研究可为其他区域及全国在快速城市化工业化过程中提升农用地碳储量提供一定参考。     

放牧强度对内蒙古荒漠草原土壤有机碳及其空间异质性的影响

放牧是内蒙古荒漠草原主要利用方式之一,研究不同放牧强度下土壤有机碳分布规律对退化草原恢复以及推广精准放牧技术具有重要的指导意义。基于不同放牧强度长期放牧样地（0、0.93、1.82、2.71羊单位hm^-2（a/2）^-1）,采用高样本数量的取样设计并结合地统计学分析方法,研究荒漠草原土壤有机碳及其空间异质性。结果表明：中度放牧会显著降低0-30 cm土层全氮含量（P<0.05）,全磷含量随放牧强度增强出现先降低后升高趋势;放牧样地土壤有机碳含量均显著低于对照样地（P<0.05）,不同放牧强度处理土壤有机碳含量没有显著差异;土壤有机碳密度受放牧影响在0-20 cm土层出现显著下降（P<0.05）,变化趋势同有机碳含量相似,碳氮比在重度放牧区0-10 cm土层显著降低（P<0.05）。土壤有机碳空间异质性和异质性斑块的破碎程度随放牧强度增加而增大;土壤有机碳含量与海拔高度在对照、轻度放牧和中度放牧区均呈极显著负相关（P<0.01）,在重度放牧区土壤有机碳含量和海拔无显著相关性;土壤有机碳含量与土壤全氮、全磷含量均呈极显著正相关（P<0.01）。综上所述,放牧降低土壤有机碳含量,提高土壤有机碳空间异质性,土壤有机碳含量的空间变异受海拔和土壤养分含量等因素的共同影响。     

基于小波变换的土壤有机碳与其影响因子多尺度相关分析

基于GIS,采用小波变换和相关分析方法,以广东山区表层(0～20 cm)土壤有机碳密度及其影响因子(包括归一化植被指数NDVI、海拔、坡度和坡向)作为分析对象,选取4条样带,使用一维离散小波变换对分析对象进行多尺度分解,在栅格尺度上定量分析土壤有机碳密度与其影响因子相关关系的多尺度响应特征.结果表明: 研究区土壤有机碳密度与其影响因子具有不同程度的尺度相关性.NDVI在2、8和16 km尺度、海拔在8和16 km尺度下的控制作用最强;坡度的控制作用极弱,尺度相关性不显著;坡向在大于2 km尺度表现为随尺度增加而增大的负相关作用.不同样带的土壤有机碳密度受不同影响因子的制约,NDVI和海拔是影响广东山区土壤有机碳密度分布的主要因子,坡度和坡向仅在个别样带、较大尺度上起作用.     

基于InVEST模型的疏勒河流域碳储量时空变化研究

研究区域土地利用方式与生态系统服务碳储量的关系，对于区域生态系统保护及经济社会可持续发展具有重要意义。利用InVEST模型碳储量模块和CA-Markov模型，探究并预测疏勒河流域1990-2015及2015-2040年流域生态系统碳储量时空变化特征及其与土地利用方式之间的关系。结果表明：疏勒河流域1990、1995、2000、2005、2010、2015年碳储量分别为7.994×10⁸、7.996×10⁸、7.998×10⁸、8.038×10⁸、8.064×10⁸、8.071×10⁸t，呈逐年增加趋势，累计增加7.7×10⁶t。土地利用类型变化是导致生态系统碳储量变化的主要因素，未利用地向耕地和草地转化有利于碳储量增加，而草地向耕地和未利用地的转化则导致碳储量减少。疏勒河流域碳储量存在显著的空间格局，碳储量较高区域呈现"北部点状-中部带状-南部点状片状"特征，这种分布格局与流域土地利用类型紧密联系。预测表明至2040年疏勒河流域碳储量为9.128×10⁸t，较2015年增加13.1%，主要原因是草地、耕地和林地面积较大幅度增长，提高了流域内的碳储量。     

基于林业清查资料的桂西北植被碳空间分布及其变化特征

基于2005-2010年林业资源清查数据,采用材积源生物量法,运用地理信息系统技术,估算和分析了桂西北植被碳密度及其储量的空间分布及其变化。结果显示:(1) 研究区域从2005年到2010年呈现碳汇变化趋势,植被碳储量由4.19×10⁴t增加到4.27×10⁴t(增幅为1.84%),植被碳密度从29.04t/hm²增加到29.57 t/hm²。(2) 从治理措施、林种起源方式及林种类型来看,自然保护区的植被碳密度最大,超过40 t/hm²。2005-2010年,人工植苗、直播、飞播和萌生方式植被碳密度增加,退耕还林工程的植被碳密度均呈明显增长(增加3.00 t/hm²),所有林种碳密度都呈不同程度的增长。 (3)植被碳密度空间分布上,大致表现为西部高、中东部低,北部高、南部低。西部区植被碳密度均值超过40 t/hm²,中东部区植被碳密度均值低于25 t/hm²。植被碳密度变化在空间分布上表现为无论是非喀斯特区还是喀斯特区的植被碳密度都有增长趋势,其中有7个县市植被碳密度升级为更高等级。研究表明,随着退耕还林、生态移民等治理措施的实施,区域植被碳密度显著增加,生态环境好转。     

陕北农田作物生产碳源/汇及碳足迹空间特征

农作物生产过程既是碳源,也是碳汇。研究作物生产过程中碳吸收、碳排放特征对区域农业碳减排具有重要意义。以陕北区域为例,采用高分辨率遥感数据,结合GEE遥感云平台和随机森林算法,获取了作物种植分布信息,并建立碳吸收排放测算模型,分析了陕北地区2021年农田作物的碳源/汇效应、碳足迹及其空间分布格局。结果表明:①陕北种植的粮食作物主要为玉米、稻谷、薯类、豆类,经济作物主要为蔬菜、苹果、枣树,这七类作物集中分布在延安南部河谷区域和榆林西北部区域。②除枣类外,陕北地区其余作物的碳吸收量均高于碳排放量,以碳汇功能为主,其中,玉米和苹果分别对该地区碳吸收、碳排放的贡献率最高,碳吸收、排放量分别达到了189.74×10⁴ t和11.41×10⁴ t,苹果、薯类和枣类碳足迹较高,分别达到了9.92×10⁴ hm²、8.77×10⁴ hm²和21.65×10⁴ hm²,其余作物碳足迹处于0.26-1.49×10⁴ hm²之间。③从空间上看,研究区单位面积农田碳吸收量呈现西北高、南部低的分布格局,而碳排放量、碳足迹分布正好相反,南部高、西北低。④研究区可通过培育高产品种、优化施肥量、控制农膜农药用量、调整作物种植结构等措施,提高作物固碳效应,促进农业生产碳减排。     

耕地占补面积时空变化对碳储量的影响测度——以湖北省为例

基于InVEST模型定量评估湖北省2000-2020年耕地占补面积时空变化对陆地生态系统碳储量的影响,在县级行政单元尺度探究由耕地占补导致的碳储量变化量在空间上的集聚程度,并运用PLUS模型模拟区域未来四种发展情景下的土地利用格局及碳储量变化趋势。结果表明：（1）2000年至2020年,湖北省耕地面积净变化率为-3.89%,耕地面积略微下降,基本实现耕地占补数量平衡。（2）2000-2005年、2005-2010年、2010-2015年、2015-2020年耕地占用和补偿导致的碳储量变化值占该时段碳储量变化值的比例分别为68.45%、59.45%、57.86%、55.46%,二十年整体占比为61.38%。耕地碳储量的变化对陆地生态系统碳储量的影响巨大。碳固持的地块面积为1.29×10⁵ hm²,碳损失的地块面积为3.88×10⁵ hm²。（3）2000-2020年,湖北省耕地占补导致的碳储量变化值具有明显的空间集聚性,"高高聚集"区主要分布在西部和西南部山区,"低低聚集"区分布在中南部的江汉平原。（4）2020-2030年,湖北省陆地生态系统碳储量在自然发展情景下减少5.50×10⁶ t,在耕地保护情景下减少1.22×10⁶ t,在城镇开发情景下减少8.89×10⁶ t,在生态保护情景下增加2.43×10⁶ t。与其他三种情景相比,生态保护情景是未来发展的最优情景。研究通过定量评估耕地占补平衡背景下湖北省耕地面积时空变化对区域碳储量的影响为未来的国土空间规划以及增汇政策的制定提供决策依据和科学参考,对于实现土地资源的可持续利用和生态环境保护具有重要意义。     

中国草地生态系统碳库及其变化

准确评估草地生态系统碳库及其年际变化, 对揭示草地在中国陆地生态系统碳循环中的作用以及合理利用有限的草地资源有着极为重要的意义. 虽然中国学者在研究草地碳库及其动态变化方面已开展了很多工作, 但目前仍缺乏对中国草地生态系统碳库及其动态变化特征的全面认识. 通过综述当前中国草地碳循环研究的最新进展, 结合本研究组的工作, 试图全面评价中国草地生态系统碳库(植被生物量碳库和土壤有机碳库)及其动态变化. 结果显示: (1) 不同研究得到的中国草地生物量碳密度(单位面积生物量)存在较大差异, 为215.8~348.1 g C/m², 平均值为 300.2 g C/m². 同样, 对中国草地土壤有机碳密度(单位面积土壤碳库)的估算也存在显著差异, 在8.5~15.1 kg C/m²之间变动, 但考虑到8.5 kg C/m²的估算值是基于近千个土壤剖面的实测数据计算得到, 全国平均水平的土壤碳密度一般不会超过此值. 因此, 若采用目前最广泛使用的草地面积(331×104 km²), 那么中国草地生态系统碳库约为29.1 Pg C(1 Pg=1×10¹⁵ g), 其中96.6%的碳储存于土壤有机质中. (2) 文献报道的近20年中国草地生物量和土壤有机碳库的变化方向和变化量均存在差异. 按照最新的估算, 中国草地生物量和土壤有机碳库在过去20年里没有发生显著变化, 即中国草地生态系统处于中性碳汇状态. (3) 中国草地生物量的时空变异与降水量的变化关系密切. 土壤有机碳库的空间变异主要受与降水量密切相关的土壤水分的影响, 但土壤质地等因素也起一定作用. 此外, 放牧与围封等人类活动将对草地生物量和土壤碳库及其动态变化产生强烈影响.     

不同恢复方式下大兴安岭重度火烧迹地林地土壤温室气体通量

为研究大兴安岭重度火烧迹地在不同恢复方式下林地土壤CO₂、CH₄和N₂O排放特征及其影响因素,采用静态箱/气相色谱法,在2017年生长季（6月-9月）对3种恢复方式（人工更新、天然更新和人工促进天然更新）林地土壤温室气体CO₂、CH₄、N₂O通量进行了原位观测。研究结果表明：（1）3种恢复方式林地土壤在生长季均为大气CO₂、N₂O的源,CH₄的汇;生长季林地土壤CO₂排放通量大小关系为人工促进天然更新（（634.40±246.52）mg m^-2 h^-1） > 人工更新（（603.63±213.22）mg m^-2 h^-1） > 天然更新（（575.81±244.12）mg m^-2 h^-1）,3种恢复方式间无显著差异;人工更新林地土壤CH₄吸收通量显著高于人工促进天然更新;天然更新林地土壤N₂O排放通量显著高于其他两种恢复方式。（2）土壤温度是影响3种恢复方式林地土壤温室气体通量的关键因素;土壤水分仅对人工更新林地土壤N₂O通量有极显著影响（P < 0.01）;3种恢复方式林地土壤CO₂通量与大气湿度具有极显著的响应（P < 0.01）;土壤pH仅与天然更新林地土壤CO₂通量显著相关（P < 0.05）;土壤全氮含量仅与人工促进天然更新林地土壤CH₄通量显著相关（P < 0.05）。（3）基于100年尺度,由3种温室气体计算全球增温潜势得出,人工促进天然更新（1.83×10⁴ kg CO₂/hm²） > 人工更新（1.74×10⁴ kg CO₂/hm²） > 天然更新（1.67×10⁴ kg CO₂/hm²）。（4）阿木尔地区林地土壤年生长季CO₂和N₂O排放量为8.85×10⁶ t和1.88×10² t,CH₄吸收量为1.05×10³ t。     

广西不同森林类型土壤有机碳的空间异质性

采用经典统计学和地统计学相结合的方法,研究广西10类主要森林类型不同土层(0~10、10~20、20~30、30~50、50~100 cm)土壤有机碳含量的空间异质性。结果表明:广西森林不同土层土壤有机碳平均含量变化为8.01~29.78 g·kg-1,变异系数在50.27%~74.89%之间;10~20 cm土层土壤有机碳的半变异函数符合球状模型,其余土层符合指数模型,且拟合效果均较好;各土层土壤有机碳半变异函数的块金效应为16.75%~49.33%,表现为强烈或中等强度的空间自相关性;Kriging插值结果显示,不同森林各土层土壤有机碳含量的分布具有一定相似的空间分布特征,总体表现为北高南低,最高和最低值分别出现在东北和东南;广西不同森林类型不同土壤深度土壤有机碳含量和变异系数不同,0~100 cm土壤有机碳平均含量的大小顺序为硬阔杉木石山林软阔竹林八角桉树油茶栎类松树,总体上土壤有机碳含量随土壤深度的增加而降低,变异系数则相反。广西森林土壤的空间异质性受结构性和人为因素的共同制约,其中结构性因素起主导作用。因此,加强自然林封育和人工林保育、优化调控桉树林和经济林种植规模是提高广西森林固碳潜力的重要措施。     

Patterns of SOC and soil 13C and their relations to climatic factors and soil characteristics on the Qinghai–Tibetan Plateau

Background and aims

SOC inventory and soil δ¹³C were widely used to access the size of soil C pool and to indicate the dynamics of C input and output. The effects of climatic factors and soil physical characteristics and plant litter input on SOC inventory and soil δ¹³C were analyzed to better understand the dynamics of carbon cycling across ecosystems on the Qinghai-Tibetan Plateau.

Methods

Field investigation was carried out along the two transects with a total of 1,875 km in length and 200 km in width. Sixty-two soil profiles, distributed in forest, meadow, steppe, and cropland, were stratified sampled every 10 cm from 0 to 40 cm.

Results

Our result showed that SOC density in forest and meadows were much higher than in steppe and highland barley. In contrast, δ¹³C in forest and meadow were lower than in steppe and highland barley. Soil δ¹³C tended to enrich with increasing soil depth but SOC decline. SOC and δ¹³C (0–40 cm) were correlated with different climatic factors in different ecosystems, such that SOC correlated negatively with MAT in meadow and positively with MAP in steppe; δ¹³C correlated positively with MAT in meadow and steppe; and δ¹³C also tended to increase with increasing MAT in forest. Of the variation of SOC, 55.15 % was explained by MAP, pH and silt content and 4.63 % was explained by the interaction between MAT and pH across all the ecosystems except for the cropland. Meanwhile, SOC density explained 27.40 % of variation of soil δ¹³C.

Conclusions

It is suggested that different climatic factors controlled the size of the soil C pool in different ecosystems on the Tibetan Plateau. SOC density is a key contributor to the variation of soil δ¹³C.     

Increase in soil organic carbon stock over the last two decades in China's Jiangsu Province

Estimates of regional and national topsoil soil organic carbon (SOC) stock change may help evaluating the soil role in mitigation of greenhouse gas (GHG) emissions through carbon (C) sequestration in soils. However, understanding of the exact mitigation role is often constrained by the uncertainty of the stock estimation associated with different methodologies. In this paper, a soil database of topsoil (0–20 cm) SOC measurements of Jiangsu Province, China, obtained from a soil survey in 1982, and from a geological survey in 2004, was used to analyze the variability of topsoil SOC among soil groups and among soil regions, and to estimate the change in SOC stocks that have occurred in the province over the last two decades. The soil survey data was obtained from measurements of 662 690 randomly collected samples, while the geological survey data was from 24 167 samples taken using a 2 km × 2 km grid. Statistical analysis was conducted on SOC values for 1982 and 2004 for different categories of soil groups, soil regions, and administrative municipalities, respectively. Topsoil SOC storage was then calculated and the provincial topsoil SOC stock was estimated for each sampling time. There were remarkable differences in SOC levels between soil groups and soil regions and different municipalities. The grid sampling with the geological survey in 2004 yielded smaller variability of topsoil SOC averages, both with soil groups and with soil spatial distribution than the random sampling method used in 1982. Variation of SOC was greater with soil groups than with soil regions in both sampling times, although it was less variable across soil taxonomic categories than within a spatial category. Little variance of the SOC level with soil groups could be explained by clay content. However, the prevalence of paddy fields in the total cropland area governed the regional and municipal average SOC levels. The average provincial topsoil SOC content increased from 9.45 g kg⁻¹ in 1982 to 10.9 g kg⁻¹ in 2004, and the total provincial topsoil SOC stock was enhanced from 149.0±58.1 Tg C in 1982 to 173.2±51.4 Tg C in 2004, corresponding to a provincial average SOC sequestration rate of 0.16±0.09 t C ha⁻¹ yr⁻¹. The SOC sequestration trend for the last two decades could be, in part, attributed to the enhanced agricultural production, symbolized by the grain yield per hectare. The results of SOC stock changes suggest a significant C sequestration in soils of Jiangsu, China, during 1980–2000, with paddy management playing an important role in regional SOC storage and sequestration capacity.     

Species Richness,Spatial Variation,and Abundance of the Soil Seed Bank of a Secondary Tropical Rain Forest1

Despite the importance of the soil seed bank in tropical forest regeneration, little is known about spatial variability in species composition and abundance of seeds stored in the soil. To develop sampling methods for comparative studies, we examined species richness, spatial variation, and abundance of germinants from the soil seed bank in a 16 year old secondary, tropical wet forest at La Selva Biological Station, Costa Rica. Surface soil (10 cm deep, 4.7 cm diameter) was collected at the intersection points of a gridded 1 ha plot (10 × 10-m grid, 121 samples) and in a nested 100 m² subplot (2 × 2-m grid, 36 samples). The 1 ha plot had a density of 4535 seeds/m² with 34 species observed. Based on a series of 100 randomized species accumulation curves, a Michaelis-Menten fit predicted a mean species richness of 36.3 species; the number of observed species was close to the predicted asymptote. A nonparametric, first-order jackknife species richness estimator predicted a species richness of 37.0 species. Eighty-five and 95 percent of the observed species richness is contained, on average, within 41 and 74 pooled samples, respectively. Within the 100 m² nested subplot, a density of 5476 seeds/m² was observed, comprising 26 species with an estimated species richness (Michaelis-Menten fit) of 29.1 species. The jackknife species richness estimator predicted a species richness of 36.7 species. For species richness and abundance of both plots, spatial autocorrelation statistics (Moran's I) were not significantly different from zero at lag distances from 2 to 100 m, indicating a random distribution at these spatial scales. For this site, accurate estimates of species composition depend upon the number of samples collected as well as the spatial distribution of sampling effort. Many small samples distributed over a large area provide greater accuracy and precision for estimating species richness of the soil seed bank.     

Impact of rainfall gradient on aboveground biomass and soil organic carbon dynamics of forest covers in Gujarat,India

Alterations in precipitation are affecting forest ecosystems’ soil carbon cycling. To understand how shifts in rainfall may alter these carbon pools, above-ground biomass (AGB), soil organic carbon (SOC), and microbial biomass carbon (MBC) of tropical forest covers were measured across a rainfall gradient (543–1590 mm) in Gujarat (India), a state falling under semi arid to tropical dry–wet conditions. Species diversity, tree density and soil texture were also measured. Field visits and data collection were carried out for 2 years (2009–2011) in 95 plots of 250 × 250 m in the forest covers across four distinct rainfall zones (RFZs). Data analysis showed that differences seen in the values of the measured parameters across the RFZs are statistically significant (P < 0.05). Positive correlations were observed between mean annual precipitation (MAP) and tree density, species diversity, AGB, SOC, and MBC. Across the RFZs, AGB ranged between 0.09 and 168.28 Mg ha^?1; SOC values (up to 25 cm soil depth) varied between 2.94 and 147.84 Mg ha^?1. Soil texture and MBC showed a significant impact on the dynamics of SOC in all the RFZs. MBC is more influenced by SOC rather than AGB. Both vegetation type and MAP have an important role in the regulation of SOC in tropical soils. Together, these results reveal complex carbon cycle responses are likely to occur in tropical soils under altered rainfall regimes.     

Elevational species shifts in a warmer climate are overestimated when based on weather station data

Strong topographic variation interacting with low stature alpine vegetation creates a multitude of micro-habitats poorly represented by common 2 m above the ground meteorological measurements (weather station data). However, the extent to which the actual habitat temperatures in alpine landscapes deviate from meteorological data at different spatial scales has rarely been quantified. In this study, we assessed thermal surface and soil conditions across topographically rich alpine landscapes by thermal imagery and miniature data loggers from regional (2-km²) to plot (1-m²) scale. The data were used to quantify the effects of spatial sampling resolution on current micro-habitat distributions and habitat loss due to climate warming scenarios. Soil temperatures showed substantial variation among slopes (2–3 K) dependent on slope exposure, within slopes (3–4 K) due to micro-topography and within 1-m² plots (1 K) as a result of plant cover effects. A reduction of spatial sampling resolution from 1 × 1 m to 100 × 100 m leads to an underestimation of current habitat diversity by 25% and predicts a six-times higher habitat loss in a 2-K warming scenario. Our results demonstrate that weather station data are unable to reflect the complex thermal patterns of aerodynamically decoupled alpine vegetation at the investigated scales. Thus, the use of interpolated weather station data to describe alpine life conditions without considering the micro-topographically induced thermal mosaic might lead to misinterpretation and inaccurate prediction.     

Intermediary disturbance increases tree diversity in riverine forest of southern Brazil

Floods are frequently associated with disturbance in structuring riverine forests and they lead to environmental heterogeneity over space and time. We evaluated the distribution of tree species, ecological groups, species richness and diversity from the point bar to the slope of a riverside forest in southern Brazil (Lat. 30°01′S, Long. 52°47′W) to analyze the effects of flooding on soil properties and forest structure. A plot of 50 × 200 m divided in five contiguous transects of 10 × 200 m parallel to the river was installed, where we measured all the individual trees with pbh ≥ 15 cm. A detailed topographical and soil survey was carried out across the plot and indicated significant differences in organic matter and most mineral nutrients through the topographical gradient. The 1,229 surveyed individuals belonged to 72 species and 35 families. We used Partial CCA and Species Indicator Analysis to observe the spatial distribution of species. Both analyses showed that species distribution was strongly related to the flooding gradient, soil properties and also by space and pure spatial structuring of species and environmental variables (spatial autocorrelation), although a large part of variation remains unexplained. The ecological groups of forest stratification, plant dispersal and requirements for germination indicated slight differences among frequently, occasional and non-flooded transects. Species richness and diversity were higher at intermediate elevations and were associated to the increased spatial–temporal environmental heterogeneity. Across the plot, the direct influence of flooding on tree species distribution created a vegetation zonation that is determined by predicted ecological traits.     

Linking woody species diversity with plant available water at a landscape scale in a Brazilian savanna

Question: How is the diversity of woody species in a seasonally dry savanna related to plant available water (PAW)? Location: Savannas in central Brazil. Methods: Two‐dimensional soil resistivity profiles to 10‐m depth previously measured along three 10 m × 275 m replicate transects revealed differences in belowground water resources among and within transects: (1) driest/most heterogeneous; (2) wettest/least heterogeneous; and (3) PAW‐intermediate. All woody plants along these transects were identified to species, and height and basal circumference measured. Species diversity was evaluated for the whole transect (total diversity), 100‐m² plots (alpha‐diversity) and dissimilarity among 100‐m² plots within transects (beta‐diversity). Correlation analyses were conducted between PAW and vegetation variables at the 100‐m² scale. Results: The driest/most heterogeneous transect had the lowest total species diversity, while the wettest/least heterogeneous transect showed the lowest beta‐diversity. Floristic variation was correlated with PAW in all transects. In the most heterogeneous transect, species density was positively correlated with PAW in the 0‐400 cm soil layer. Evenness and Simpson's diversity were negatively correlated with PAW in the 700‐1000 cm soil layer. Conclusion: Woody species diversity was related to PAW at a fine spatial scale. Abundant PAW in the top 4 m of soil may favour many species and increase species total diversity. Conversely, abundant PAW at depth may result in lower evenness and total diversity, probably because the few species adapted to obtaining deep soil water can become dominant. Environmental changes altering soil water availability and partitioning in soil layers could affect the diversity of woody plants in this savanna.     

Soil Carbon Storage by Switchgrass Grown for Bioenergy

Life-cycle assessments (LCAs) of switchgrass (Panicum virgatum L.) grown for bioenergy production require data on soil organic carbon (SOC) change and harvested C yields to accurately estimate net greenhouse gas (GHG) emissions. To date, nearly all information on SOC change under switchgrass has been based on modeled assumptions or small plot research, both of which do not take into account spatial variability within or across sites for an agro-ecoregion. To address this need, we measured change in SOC and harvested C yield for switchgrass fields on ten farms in the central and northern Great Plains, USA (930 km latitudinal range). Change in SOC was determined by collecting multiple soil samples in transects across the fields prior to planting switchgrass and again 5 years later after switchgrass had been grown and managed as a bioenergy crop. Harvested aboveground C averaged 2.5?±?0.7 Mg C ha^?1 over the 5 year study. Across sites, SOC increased significantly at 0–30 cm (P?=?0.03) and 0–120 cm (P?=?0.07), with accrual rates of 1.1 and 2.9 Mg C ha^?1 year^?1 (4.0 and 10.6 Mg CO₂ ha^?1 year^?1), respectively. Change in SOC across sites varied considerably, however, ranging from ?0.6 to 4.3 Mg C ha^?1 year^?1 for the 0–30 cm depth. Such variation in SOC change must be taken into consideration in LCAs. Net GHG emissions from bioenergy crops vary in space and time. Such variation, coupled with an increased reliance on agriculture for energy production, underscores the need for long-term environmental monitoring sites in major agro-ecoregions.