Effect of error in the DEM on environmental variables for predictive vegetation modelling

Question: Predictive vegetation modelling relies on the use of environmental variables, which are usually derived from abase data set with some level of error, and this error is propagated to any subsequently derived environmental variables. The question for this study is: What is the level of error and uncertainty in environmental variables based on the error propagated from a Digital Elevation Model (DEM) and how does it vary for both direct and indirect variables? Location: Kioloa region, New South Wales, Australia Methods: The level of error in a DEM is assessed and used to develop an error model for analysing error propagation to derived environmental variables. We tested both indirect (elevation, slope, aspect, topographic position) and direct (average air temperature, net solar radiation, and topographic wetness index) variables for their robustness to propagated error from the DEM. Results: It is shown that the direct environmental variable net solar radiation is less affected by error in the DEM than the indirect variables aspect and slope, but that regional conditions such as slope steepness and cloudiness can influence this outcome. However, the indirect environmental variable topographic position was less affected by error in the DEM than topographic wetness index. Interestingly, the results disagreed with the current assumption that indirect variables are necessarily less sensitive to propagated error because they are less derived. Conclusions: The results indicate that variables exhibit both systematic bias and instability under uncertainty. There is a clear need to consider the sensitivity of variables to error in their base data sets in addition to the question of whether to use direct or indirect variables.     

多尺度下宝鸡地区干旱动态格局演变及其与植被覆盖的关系

利用宝鸡地区11个气象站点1974—2013年逐月气温和降水量数据,基于标准化降水蒸散指数(SPEI),结合土地利用/覆盖数据,从干旱发生频率、发生强度及与植被NDVI相关性等角度,探讨了近40年来干旱时空变化格局及其对植被覆盖的响应。结果显示:宝鸡地区年均SPEI指数以-2.50%/a的速度下降,干旱趋势明显增强。自20世纪末以来,全区年均干旱指数呈明显的上升趋势,以2007—2010年增大趋势最为显著(超过0.05临界线);近40年来,春季干旱发生频率达60%及以上的有21 a,达90%以上的有9a。1981—1986年起伏变化最为剧烈。秋季平均干旱发生频率为46.29%,为春、夏、秋、冬4个季节中最低。从干旱发生强度来看,全区年际、四季及月6个时间尺度上干旱强度高、低值区域分布均比较集中;秋季强度最弱的区域面积表现最高,占总面积的75.47%。干旱发生最严重的是春季,占总面积的11.90%。全区干旱与植被覆盖相关性均表现较好(均通过0.05显著性水平检验),林地、草地负相关性最为显著(除夏季),夏季、秋季、月尺度上,耕地、水域、城乡地区干旱与植被覆盖的相关性与土地利用类型无关。     

内蒙古植被降水利用效率的时空格局及其驱动因素

植被降水利用效率(precipitation-use efficiency, PUE)是评价干旱、半干旱地区植被生产力对降水量时空动态响应特征的重要指标。该研究利用光能利用率CASA (Carnegie-Ames-Stanford Approach)模型估算了2001-2010年内蒙古地区植被净初级生产力(net primary productivity, NPP), 结合降水量的空间插值数据, 分析了近10年内蒙古地区植被PUE的空间分布、主要植被类型的PUE,及其时空格局的驱动因素。结果表明: 2001-2010年内蒙古地区所有植被的平均PUE为0.94 g C·m^-2·mm^-1, 且在105-120° E地带性规律明显,PUE上升速率为每10° 0.55 g C·m^-2·mm^-1。各植被类型间PUE差别较大, 其中灌丛PUE最高, 荒漠PUE最低。在不同的降水量区域, 植被PUE的空间分布与气候因子的关系有较大差别, 0-75 mm降水量区间内, PUE随降水量、气温的升高显著下降(R² = 0.226, p < 0.05); 175-300 mm降水量区间内, 植被 PUE的空间变化与降水量和气温呈极显著相关关系(R² = 0.878, p < 0.001), 且随降水量的增加显著上升( R² = 0.94, p < 0.001), 变化速率约为每100 mm降水0.57 g C·m ^-2·mm^-1; 在降水量大于475 mm的区域, 植被PUE的空间分布与降水量、气温的相关性显著(R² = 0.19, p < 0.05), 且随着气温的上升、降水量的下降而增加, 其中气温的贡献是降水量的8.61倍。在不同的降水量区域, 植被 PUE的年际波动与气候因子的关系也有较大差别, 对于年降水量0-220 mm的地区, PUE的年际波动与降水量呈正相关性、与气温呈负相关性; 在年降水量为220-310 mm的地区, PUE的年际波动主要受降水量的控制, 受气温影响较小; 在年降水量>310 mm的地区,PUE的年际波动与降水量、气温均呈正相关关系, 但在降水量越高的地区, PUE的年际波动与降水量的相关性越弱, 与气温的相关性越强。植被覆盖度与PUE的空间分布极显著相关(R² = 0.73, p < 0.001), 且与 PUE的年际波动也存在线性相关关系(R² = 0.11, p < 0.001); 叶面积指数( LAI)与PUE的年际波动呈线性相关关系(R² = 0.42, p < 0.001), 而当 LAI < 3.15时, PUE的空间分布随LAI增加而呈线性增加。     

植被叶面积指数遥感反演的尺度效应及空间变异性

遥感作为宏观生态学研究中数据获取的一种便捷手段,有助于把握较大尺度内生态学现象的特征.应用遥感数据反演LAI时,由于像元的异质性,不同尺度遥感数据之间的转换是遥感发展的一个重要问题.以河北省黄骅市为研究区,在利用TM和MODIS遥感数据对芦苇LAI反演误差产生原因进行分析的基础上,利用半变异函数对像元空间异质性进行了定量描述.发现NDVI算法的非线性带给LAI尺度转换的误差很小,而LAI的空间异质性则是引起LAI尺度效应的根本原因.并且当像元内空间异质性很大时半变异函数的基台值比纯像元要大得多,空间自相关的程度是引起LAI尺度转换误差的主要原因;反之,像元内空间异质性不大时,随机误差是引起LAI尺度转换误差的主要原因.当像元为纯像元时,由像元异质性引起的反演误差基本可以忽略.此外,研究区芦苇的空间相关有效尺度约为360m,超过此距离空间相关性则不复存在.     

Vegetation patterns in heterogeneous landscapes: The importance of history and environment

Abstract. Throughout the eastern United States, plant species distributions and community patterns have developed in response to heterogeneous environmental conditions and a wide range of historical factors, including complex histories of natural and anthropogenic disturbance. Despite increased recognition of the importance of disturbance in determining forest composition and structure, few studies have assessed the relative influence of current environment and historical factors on modern vegetation, in part because detailed knowledge of prior disturbance is often lacking. In the present study, we investigate modern and historical factors that control vegetation patterns at Harvard Forest in central Massachusetts, USA. Similar to the forested uplands throughout the northeastern United States, the site is physiographically heterogeneous and has a long and complex history of natural and anthropogenic disturbance. However, data on forest composition and disturbance history collected over the past > 90 years allow us to evaluate the importance of historical factors rigorously, which is rarely possible on other sites. Soil analyses and historical sources document four categories of historical land use on areas that are all forested today: cultivated fields, improved pastures/mowings, unimproved pastures, and continuously forested woodlots. Ordination and logistic regressions indicate that although species have responded individualistically to a wide range of environmental and disturbance factors, many species are influenced by three factors: soil drainage, land use history, and C:N ratios. Few species vary in accordance with ionic gradients, damage from the 1938 hurricane, or a 1957 fire. Contrary to our expectation that the effects of disturbance will diminish over time, historical land use predicts 1992 vegetation composition better than 1937 composition, perhaps because historical woodlots have become increasingly differentiated from post-agricultural stands through the 20th century. Interpretations of modern vegetation must consider the importance of historical factors in addition to current environmental conditions. However, because disturbances such as land use practices and wind damage are complex, it is often difficult to detect disturbance effects using multivariate approaches, even when the broad history of disturbance is known.     

2001年以来宝鸡地区植被覆盖时空演变及驱动力分析

植被在全球变化中影响着地-气系统的能量平衡,是自然和人文因素对环境影响的敏感指标。分析地表植被的覆盖现状并探究影响植被变化的驱动力因素对区域生态恢复以及区域经济发展和区域生态文明建设都有促进作用。本研究基于中分辨率成像光谱仪-归一化植被指数（MODIS-NDVI）数据,结合宝鸡11个气象站的气温和降水量实测数据、净初级生产力（NPP）以及宝鸡统计年鉴数据,采用趋势分析方法、Pearson相关分析法、主成分分析方法对2001-2013年宝鸡地区植被覆盖的时空演化特征进行了分析,并对自然驱动因子和人为驱动因子双重影响下的宝鸡地区植被覆盖演化状况进行了综合评价。结果显示：（1）2001-2013年宝鸡地区年均NDVI以0.025/10a的速度上升,比三北防护林工程区1982-2006年植被覆盖的增速（0.007/10a）快,且2001-2002年、2003-2004年两个年份段为年均NDVI值的两次高恢复期;（2）植被覆盖以轻度改善为主,基本不变和中度改善次之,严重退化和中度退化最弱。植被覆盖恢复状况整体上呈稳中上升的趋势（个别地区除外）;（3）自然因素中的降水量和NPP是制约植被生长的主要因素。整体来看,人为因素相对于自然因素对宝鸡全区的植被覆盖影响较大,贡献率在90%左右,呈先减小后增加的趋势。     

祁连山国家公园植被时空变化及其对人类活动的响应

祁连山国家公园地处青藏、蒙新、黄土三大高原交汇地带的祁连山北麓,作为国家公园体制试点之一,是我国重要的生态功能区、水源涵养地和生物多样性保护优先区域,其生态功能不可忽视。以祁连山国家公园2000—2019年归一化植被指数(NDVI)和净初级生产力(NPP)数据为基础,结合气温、降水、土地利用、矿产开采和旅游发展数据,利用泰尔-森趋势分析(Theil-Sen趋势分析)、曼-肯德尔检验(Mann-Kendall显著性检验)、土地转移概率矩阵和多元残差分析方法,分析该区域的植被时空分布特征、变化趋势特征及其对气候变化和人类活动的响应。结果表明：(1)2000—2019年祁连山国家公园内NDVI和NPP在空间上呈现出东南高西北低,由东南向西北递减的格局。时间上呈现上升趋势,上升速率分别为0.0053/a和0.0014/a;(2)祁连山国家公园内NPP提高、降低和稳定区域分别占总面积的87.29%、0.40%和12.30%。降低区域零星分布于整个国家公园,其中在走廊南山和冷龙岭交汇处,靠近甘青两省交界边缘分布最为集中。提高区域分布广泛,尤其以国家公园东部最为明显;(3)祁连山国家公园NDVI与气...     

Effects of scale-dependent factors on herbaceous vegetation patterns in a wetland,northern Japan

Herbaceous vegetation was examined in an Otanoshike wetland in northern Japan to clarify the relationships between vegetation patterns and environmental factors with different scales. Alders (Alnus japonica) have recently invaded and might modify the herbaceous vegetation. In total, 150 50×50cm plots were established on the transitional areas between alder thickets and grassy marshland. Cover was measured for the vascular plant taxa, and canopy area, number of stumps, number of mounds, water depth, elevation difference, litter thickness, soil organic matter, and soil pH were measured in each plot. TWINSPAN cluster analysis classified four vegetation groups: (i), grasslands represented by Phragmites australis, Trientalis europaea, Lythrum salicaria, and Hosta rectifolia; (ii), Calamagrostis langsdorfii, and Polygonum thunbergii grasslands with Spiraea salicifolia; (iii), reed swamp dominated by Phragmites australis, and (iv), marshland dominated by Carex lyngbyei. Canonical correspondence analysis indicated that water depth primarily divided vegetation groups 1–2 and 3–4. Alder established in drier sites mostly by re-sprouting, and the canopy affected light and soil conditions on the ground surface. The second axis of canonical correspondence analysis was related to the canopy area and soil pH, and explained the vegetation differentiation between groups 1 and 2, and groups 3 and 4. In conclusion therefore, scale-dependent or hierarchical variables affected the vegetation patterns in different ways, that is, the herbaceous vegetation was first differentiated by water depth that was corresponding to alder establishment on a large scale, and subsequent light and soil conditions were second determinants on a small scale.     

Consistent shifts in spring vegetation green‐up date across temperate biomes in China, 1982–2006

Understanding spring phenology changes in response to the rapid climate change at biome‐level is crucial for projecting regional ecosystem carbon exchange and climate–biosphere interactions. In this study, we assessed the long‐term changes and responses to changing climate of the spring phenology in six temperate biomes of China by analyzing the global inventory monitoring and modeling studies (GIMMS) NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) and concurrent mean temperature and precipitation data for 1982–2006. Results show that the spring phenology trends in the six temperate biomes are not continuous throughout the 25 year period. The spring phenology in most areas of the six biomes showed obvious advancing trends (ranging from ?0.09 to ?0.65 day/yr) during the 1980s and early 1990s, but has subsequently suffered consistently delaying trends (ranging from 0.22 to 1.22 day/yr). Changes in spring (February–April) temperature are the dominating factor governing the pattern of spring vegetation phenology in the temperate biomes of China. The recently delayed spring phenology in these temperate biomes has been mainly triggered by the stalling or reversal of the warming trend in spring temperatures. Results in this study also reveal that precipitation during November–January can explain 16.1% (P < 0.05), 20.9% (P < 0.05) and 14.2% (P < 0.05) of the variations in temperate deciduous forest (TDF), temperate steppe (TS), temperate desert (TD) respectively, highlighting the important role of winter precipitation in regulating changes in the spring vegetation phenology of water–limited biomes.     

生态公益林补偿政策对植被覆盖时空格局的影响——以杭州市临安区为例

生态补偿政策绩效评价对完善政策调控和促进植被恢复具有重要意义。分析了临安2001—2015年植被覆盖的时空格局和变化,建立了植被退化地区土地利用变化矩阵。在Arc GIS软件中建立了临安地区归一化植被指数(NDVI)、国家级和省级公益林覆盖边界(重点生态公益林补偿边界)、道路、海拔、中心城镇用地边界、重点森林保护区、河流边界和地形湿度指数的多要素地理空间数据集。采用多元回归模型量化了重点生态公益林补偿政策、自然因素、城市化和其他人类活动对植被覆盖变化的影响。结果表明,2001—2015年间,临安大约有97%的林地呈现出不同程度的退化,其中中等退化程度的林地所占比例最高。多元线性回归模型的结果表明重点生态公益林补偿政策、海拔、河流距离、重点森林保护区距离和中心城镇距离对植被退化有抑制作用,道路和地形湿度指数对植被退化有促进作用。海拔在所有的外部影响因素中对植被退化的影响最大。政策覆盖地区的植被退化面积在每一个退化等级上都小于无政策覆盖地区。生态公益林补偿政策的实施对加强植被的保护,限制不合理的林地利用和改善区域环境质量具有十分重要的积极作用。     

Spatial patterns in brown bear Ursus arctos diet: the role of geographical and environmental factors

• 1 We reviewed worldwide spatial patterns in the food habits of the brown bear Ursus arctos in relation to geographical (latitude, longitude, altitude) and environmental (temperature, snow cover depth and duration, precipitation, primary productivity) variables.
• 2 We collected data from 28 studies on brown bear diet based on faecal analysis, covering the entire geographical range of this widely distributed large carnivore. We analysed separately four data sets based on different methods of diet assessment.
• 3 Temperature and snow conditions were the most important factors determining the composition of brown bear diet. Populations in locations with deeper snow cover, lower temperatures and lower productivity consumed significantly more vertebrates, fewer invertebrates and less mast. Trophic diversity was positively correlated with temperature, precipitation and productivity but negatively correlated with the duration of snow cover and snow depth. Brown bear populations from temperate forest biomes had the most diverse diet. In general, environmental factors were more explicative of diet than geographical variables.
• 4 Dietary spatial patterns were best revealed by the relative biomass and energy content methods of diet analysis, whereas the frequency of occurrence and relative biomass methods were most appropriate for investigating variation in trophic diversity.
• 5 Spatial variation in brown bear diet is the result of environmental conditions, especially climatic factors, which affect the nutritional and energetic requirements of brown bears as well as the local availability of food. The trade‐off between food availability on the one hand, and nutritional and energetic requirements on the other hand, determines brown bear foraging decisions. In hibernating species such as the brown bear, winter severity seems to play a role in determining foraging strategies. Large‐scale reviews of food habits should be based on several measures of diet composition, with special attention to those methods reflecting the energetic value of food.

     

基于临界慢化模型和长时间序列叶面积指数的植被及其恢复力遥感监测研究——以三峡库区为例

基于临界慢化模型,利用长时间序列叶面积指数(GLASS LAI)数据,进行时间序列分解后,计算了LAI及其时间自相关指数作为指标,对三峡库区植被及其恢复力进行监测,通过案例模型对临界慢化模型精度进行了验证,分析了三峡库区植被及其植被恢复力的时空分布特征,探索基于临界慢化模型的植被恢复力遥感定量估算方法的适用性。结果表明：(1)2000—2018年三峡库区LAI平均值为3.4,重庆段LAI较低,湖北段LAI较高;三峡库区LAI整体呈上升趋势,重庆段LAI呈现降低趋势,显著下降区域占重庆段面积的21.75%,湖北段LAI呈现升高趋势,显著上升区域占湖北段面积的21.22%;(2)2000—2018年三峡库区重庆市北碚区、大渡口区、渝北区植被恢复力较低,宜昌市兴山县、夷陵区、点军区植被恢复力较高;(3)模型精度方面,在两个地质灾害扰动事件中案例模型结果与临界慢化模型结果呈现较高的一致性。本文对三峡库区2000—2018年的植被恢复力进行了定量估算,同时通过案例模型对临界慢化模型在恢复力监测上的有效性进行了验证,为三峡库区制定相应生态环境管理决策提供理论基础,为保障西南地区生态安全提供决策依据...     

呼伦贝尔沙地不同植被恢复模式对土壤固氮微生物多样性的影响

利用聚合酶链式反应-变性梯度凝胶电泳(PCR-DGGE)技术及扩增产物序列分析方法,研究了经过4年不同植被恢复模式下呼伦贝尔沙地土壤固氮微生物的nifH基因多样性和群落结构的变化.结果表明:不同植被恢复模式间土壤固氮微生物群落组成差异显著.混播柠条+羊柴+冰草+披碱草模式(ACHE)下的土壤固氮微生物nifH基因多样性指数最高,其次为混播柠条+冰草(AC)、单播柠条(UC)、单播冰草(UA)和单播羊柴(UH)模式,对照(裸地)最低.除单播羊柴(UH)模式与对照的多样性指数差异不显著外,其余4种植被恢复模式均显著高于对照.单一恢复模式(UA、UH、UC)下,绝大多数土壤固氮微生物属于蓝藻门,结构比较单一;而混播模式(AC和ACHE)下,土壤固氮微生物组成发生明显变化,以变形菌门为主,还包含蓝藻门,其种类增加,多样性提高.不同植被恢复模式的速效磷(AP)、全磷(TP)、全氮(TN)和硝态氮(N03-N)对固氮微生物区系的影响均达到显著水平,且AP、TP、TN和NO3--N之间均具有显著相关性.不同植被恢复模式下土壤固氮微生物区系组成的变化是不同理化因子之间相互关联、共同影响的结果.