Spatial variation in vegetation structure coupled to plant available water determined by two-dimensional soil resistivity profiling in a Brazilian savanna

Tropical savannas commonly exhibit large spatial heterogeneity in vegetation structure. Fine-scale patterns of soil moisture, particularly in the deeper soil layers, have not been well investigated as factors possibly influencing vegetation patterns in savannas. Here we investigate the role of soil water availability and heterogeneity related to vegetation structure in an area of the Brazilian savanna (Cerrado). Our objective was to determine whether horizontal spatial variations of soil water are coupled with patterns of vegetation structure across tens of meters. We applied a novel methodological approach to convert soil electrical resistivity measurements along three 275-m transects to volumetric water content and then to estimates of plant available water (PAW). Structural attributes of the woody vegetation, including plant position, height, basal circumference, crown dimensions, and leaf area index, were surveyed within twenty-two 100-m² plots along the same transects, where no obvious vegetation gradients had been apparent. Spatial heterogeneity was evaluated through measurements of spatial autocorrelation in both PAW and vegetation structure. Comparisons with null models suggest that plants were randomly distributed over the transect with the greatest mean PAW and lowest PAW heterogeneity, and clustered in the driest and most heterogeneous transect. Plant density was positively related with PAW in the top 4 m of soil. The density-dependent vegetation attributes that are related to plot biomass, such as sum of tree heights per plot, exhibited spatial variation patterns that were remarkably similar to spatial variation of PAW in the top 4 m of soil. For PAW below 4 m depth, mean vegetation attributes, such as mean height, were negatively correlated with PAW, suggesting greater water uptake from the deep soil by plants of larger stature. These results are consistent with PAW heterogeneity being an important structuring factor in the plant distribution at the scale of tens of meters in this ecosystem.     

放牧和刈割条件下草山草坡群落空间异质性分析

采用变异矩分析和分形方法,研究了草山草坡群落在放牧和刈割条件下的空间异质性及空间自相关性,结果表明,群落空间格局有尺度依赖性,刈割条件下空物异质性及空间相关性弱,多样性梯度即β多样性小,放牧消除地形引起的样地差异,因而使空间异质性简单化。     

Local and landscape factors determining occurrence of phyllostomid bats in tropical secondary forests

Neotropical forests are being increasingly replaced by a mosaic of patches of different successional stages, agricultural fields and pasture lands. Consequently, the identification of factors shaping the performance of taxa in anthropogenic landscapes is gaining importance, especially for taxa playing critical roles in ecosystem functioning. As phyllostomid bats provide important ecological services through seed dispersal, pollination and control of animal populations, in this study we assessed the relationships between phyllostomid occurrence and the variation in local and landscape level habitat attributes caused by disturbance. We mist-netted phyllostomids in 12 sites representing 4 successional stages of a tropical dry forest (initial, early, intermediate and late). We also quantitatively characterized the habitat attributes at the local (vegetation structure complexity) and the landscape level (forest cover, area and diversity of patches). Two focal scales were considered for landscape characterization: 500 and 1000 m. During 142 sampling nights, we captured 606 individuals representing 15 species and 4 broad guilds. Variation in phyllostomid assemblages, ensembles and populations was associated with variation in local and landscape habitat attributes, and this association was scale-dependent. Specifically, we found a marked guild-specific response, where the abundance of nectarivores tended to be negatively associated with the mean area of dry forest patches, while the abundance of frugivores was positively associated with the percentage of riparian forest. These results are explained by the prevalence of chiropterophilic species in the dry forest and of chiropterochorous species in the riparian forest. Our results indicate that different vegetation classes, as well as a multi-spatial scale approach must be considered for evaluating bat response to variation in landscape attributes. Moreover, for the long-term conservation of phyllostomids in anthropogenic landscapes, we must realize that the management of the habitat at the landscape level is as important as the conservation of particular forest fragments.     

Roles of Climate,Vegetation and Soil in Regulating the Spatial Variations in Ecosystem Carbon Dioxide Fluxes in the Northern Hemisphere

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60 % and 58 % of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45 - 47 % of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75 %. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary.     

Influence of edaphic factors on the spatial structure of inland halophytic communities: a case study in China

Abstract. In order to understand the influence of edaphic factors on the spatial structure of inland halophytic plant communities, a 2.6 km² study site, located on the lower fringe of the alluvial fan of the Hutubi River, in an arid region of China, was sampled and mapped. 105 patches were found to be homogeneous in species composition. Plant species and their coverage were recorded in each patch. 45 patches were randomly selected for the measurement of edaphic variables. A map with quadrat locations and boundaries of patches was digitized into a GIS and related to the vegetation and edaphic data matrices. CCA was used to evaluate the relative importance of edaphic factors in explaining the variation of the species assemblages and to identify the ecological preferences of species. The spatial structure of the communities and the main edaphic factors were analyzed using correlograms, Mantel correlograms and clustering under constraint of spatial contiguity. Gradient analysis showed that there are two distinct vegetation gradients in the study area, one of which is determined mainly by soil moisture (determined by depth to the water table), and the other by soil salinity (determined by electrical conductivity and hydrolytic alkalinity of the first soil layer). However, spatial analyses showed that at the sampling scale the halophytic communities in the study area are structured along one main spatial gradient determined by the water table level. Similar spatial autocorrelation structures between the factors related to the first soil layer and the communities, given our sampling scale, could not be detected. Our results suggest that the relative importance of the effects of different edaphic factors on the spatial structure of halophytic communities is scale-dependent. The partitioning of species variation indicates that in addition to edaphic factors, other factors, such as biotic interactions, may play an important role in structuring these communities.     

Does scale‐dependent feedback explain spatial complexity in salt‐marsh ecosystems?

Complexity theory highlights scale-dependent feedback mechanisms as an explanation for regular spatial patterning in ecosystems. To what extent scale-dependent feedback clarifies spatial structure in more complex, non-regular systems remains unexplored so far. We report on a scale-dependent feedback process generating patchy landscapes at the interface of intertidal flats and salt marshes. Here, vegetation was characterized by Spartina anglica tussocks, surrounded by erosion gullies. To demonstrate the presence of a scale-dependent feedback, we determined if vegetation induced habitat modification resulted in local facilitation and large scale-inhibition of plant growth. Field surveys revealed that larger tussocks have deeper gullies, suggesting that gully erosion is caused by increased water flow around tussocks. This was confirmed by flume experiments, showing that feedback effects vary with current velocity and water depth. Transplantation of small Spartina units inside and just outside present tussocks revealed that the growth of Spartina transplants compared to transplant growth on bare sediment was higher within the raised Spartina tussocks, but lower in the gully just outside Spartina tussocks, providing clear evidence of scale-dependent feedback. Our results emphasize that scale-dependent feedback is a more general explanation for spatial complexity in ecosystems than previously considered.     

Fire acting as an increasing spatial autocorrelation force: Implications for pattern formation and ecological facilitation

Fire is an indissoluble component of ecosystems, however quantifying the effects of fire on vegetation is a challenging task as fire lies outside the typical experimental design attributes. A recent simulation study showed that under increased fire regimes positive tree–tree interactions were recorded (Bacelar et al., 2014). Data from experimental burning plots in an African savanna, the Kruger National Park, were collected across unburnt and annual burn plots. Indices of aggregation and spatial autocorrelation of the distribution of trees between different fire regimes were explored. Results show that the distribution of trees under fire were more clumped and exhibited higher spatial autocorrelation than in unburnt plots. In burnt plots spatial autocorrelation values were positive at finer scales and negative at coarser scales potentially indicating co-existence of facilitation and competition within the same ecosystem depending on the scale. The pattern derived here provides inference for (a) fire acting as an increasing aggregation & spatial autocorrelation force, (b) tree survival under fire regimes is potentially facilitated by forming patches of trees and (c) scale-dependent facilitation and competition coexisting within the same ecosystem with finer scale facilitation and coarser scale competition.     

Predicting Tropical Dry Forest Successional Attributes from Space: Is the Key Hidden in Image Texture?

Biodiversity conservation and ecosystem-service provision will increasingly depend on the existence of secondary vegetation. Our success in achieving these goals will be determined by our ability to accurately estimate the structure and diversity of such communities at broad geographic scales. We examined whether the texture (the spatial variation of the image elements) of very high-resolution satellite imagery can be used for this purpose. In 14 fallows of different ages and one mature forest stand in a seasonally dry tropical forest landscape, we estimated basal area, canopy cover, stem density, species richness, Shannon index, Simpson index, and canopy height. The first six attributes were also estimated for a subset comprising the tallest plants. We calculated 40 texture variables based on the red and the near infrared bands, and EVI and NDVI, and selected the best-fit linear models describing each vegetation attribute based on them. Basal area (R ² = 0.93), vegetation height and cover (0.89), species richness (0.87), and stand age (0.85) were the best-described attributes by two-variable models. Cross validation showed that these models had a high predictive power, and most estimated vegetation attributes were highly accurate. The success of this simple method (a single image was used and the models were linear and included very few variables) rests on the principle that image texture reflects the internal heterogeneity of successional vegetation at the proper scale. The vegetation attributes best predicted by texture are relevant in the face of two of the gravest threats to biosphere integrity: climate change and biodiversity loss. By providing reliable basal area and fallow-age estimates, image-texture analysis allows for the assessment of carbon sequestration and diversity loss rates. New and exciting research avenues open by simplifying the analysis of the extent and complexity of successional vegetation through the spatial variation of its spectral information.     

Plant Spatial Pattern Predicts Hillslope Runoff and Erosion in a Semiarid Mediterranean Landscape

Abstract The importance of the spatial pattern of vegetation for hydrological behavior in semiarid environments is widely acknowledged. However, there is little empirical work testing the hypothetical covariation between vegetation spatial structure and hillslope water and sediment fluxes. We evaluated the relationships between vegetation structural attributes (spatial pattern, functional diversity), soil surface properties (crust, stone, plant, and ground cover, and particle size distribution) and hillslope hydrologic functioning in a semiarid Mediterranean landscape; in particular, we tested whether decreasing patch density or coarsening plant spatial pattern would increase runoff and sediment yield at the hillslope scale. Runoff and sediment yield were measured over a 45-month period on nine 8 × 2-m plots that varied in vegetation type and spatial pattern. We grouped vegetation into functional types and derived plant spatial pattern attributes from field plot maps processed through a GIS system. We found that there was an inverse relationship between patch density and runoff, and that both runoff and sediment yields increased as the spatial pattern of vegetation coarsened. Vegetation pattern attributes and plant functional diversity were better related to runoff and sediment yield than soil surface properties. However, a significant relationship was found between physical crust cover and plant spatial pattern. Our results present empirical evidence for the direct relationship between the hydrologic functioning of semiarid lands and both the spatial pattern and the functional diversity of perennial vegetation, and suggest that plant spatial pattern, physical crust cover, and functional diversity may be linked through feedback mechanisms.     

Changes of species richness pattern in mountain grasslands: abandonment versus restoration

Changes in plant species richness at various spatial scales were investigated by manipulative experiment in mountain grasslands. The aim of the research was to compare changes in species richness in newly abandoned sites and sites where restoration measures were applied after 20 years of abandonment. The plots were located in two vegetation types with different moisture regime. Species richness decreased significantly after abandonment, mainly at the finest spatial scale of 10 × 10 cm. There was significant increase of species richness on restored sites, but it was apparent mainly at a larger scale. However, even 4 years of regular mowing were not sufficient to restore species richness to the level typical for traditionally managed grasslands in the region. No significant difference was found in the performance of the 2 contrasting vegetation types (wet and dry) in relation to management measures. A significant difference in scale-dependent species richness was only observed. The dry type had a steeper species-area curve, with a lower number of species at the finest spatial scale. According to the results of the experiment, mountain grasslands are very vulnerable habitats, losing their conservation value quickly after abandonment. Restoration is possible due to an extensive species pool in the region, but return to the original species richness at all spatial scales is quite a long process.     

Observer variation in field assessments of vegetation condition: Implications for biodiversity conservation

Summary   Uncertainty in assessments of vegetation condition that are used to inform land management and planning decisions for biodiversity conservation in Australia may lead to unexpected outcomes, including loss of biodiversity. This study investigates observer error in field estimates of vegetation attributes, one component of uncertainty in assessments of vegetation condition. Ten observers conducted vegetation condition assessments using two assessment protocols (BioMetric and Habitat Hectares) on 20 sites in a grassy woodland community. Observers' estimates varied substantially across multiple scoring categories for all vegetation attributes on almost all sites. Across all sites, the average coefficient of variation in total vegetation condition scores was 15–18% for both protocols, with a maximum of 60%. The primary cause of variation in total vegetation condition scores was random error in raw estimates of vegetation attributes, although sensitivity of some highly weighted attributes to error exacerbated variation in some cases. Observers generally agreed on the total scores and ranks of highly degraded (pasture) sites, but were less consistent on other sites. Rank correlations between pairs of observers were stronger for Habitat Hectares, suggesting BioMetric may be slightly more sensitive to observer error. It is recommended that: (i) research is undertaken into methods for reducing observer error; (ii) review is made of the sensitivity of index scoring structures to observer error; (iii) field observers estimate uncertainty around point estimates of vegetation condition; and, (iv) decision-makers explicitly incorporate uncertainty into the decision-making processes and aim for outcomes that are robust to this uncertainty.     

陕北黄土高原植被恢复与生态系统服务的时空关系

陕北黄土高原作为退耕还林还草核心区域,是地表格局及植被显著变化的区域之一。评估植被恢复成果及其对生态系统服务的影响,对促进区域生态环境提升具有重要作用。本研究选择植被覆盖度作为指标评估区域植被恢复状况,以碳固定服务、土壤保持服务、生境质量及产水服务作为指标表征区域生态系统服务,分析权衡协同关系及不同尺度的时空变化,同时运用双变量空间自相关分析植被恢复对生态系统服务的影响。结果表明: 2000—2020年,陕北黄土高原植被覆盖度呈波动上升趋势,年均值由31.7%升至47.1%,植被改善显著;研究区碳固定服务、土壤保持服务呈明显上升趋势,生境质量几乎保持不变,产水服务先升后下降总体呈上升趋势,各生态系统服务时空变化存在明显的尺度效应;4种生态系统服务间的关系主要为协同;植被覆盖与生态系统服务之间存在显著的空间依赖性,相关程度存在一定差异,植被覆盖度对土壤保持服务影响最明显,其次为碳固定服务,而植被覆盖增强条件下林草耗水增多则导致区域产水量下降,造成一定的负效应。总的来说,陕北黄土高原地区植被建设已取得显著成效,生态环境得到明显改善。     

Spatial scaling of ecosystem C and N in a subtropical savanna landscape

Widely occurred woody encroachment in grass‐dominated ecosystems has the potential to influence soil organic carbon (SOC) and total nitrogen (TN) pools at local, regional, and global scales. Evaluation of this potential requires assessment of both pool sizes and their spatial patterns. We quantified SOC and TN, their relationships with soil and vegetation attributes, and their spatial scaling along a catena (hill‐slope) gradient in the southern Great Plains, USA where woody cover has increased substantially over the past 100 years. Quadrat variance analysis revealed spatial variation in SOC and TN at two scales. The larger scale variation (40–45 m) was approximately the distance between centers of woody plant communities and their adjoining herbaceous patches. The smaller scale variation (10 m) appeared to reflect the local influence of shrubs on SOC and TN. Litter, root biomass, shrub, and tree basal area (a proxy for plant age) exhibited not only similar spatial scales, but also strong correlations with SOC and TN, suggesting invasive woody plants alter both the storage and spatial scaling of SOC and TN through ecological processes related primarily to root turnover and, to a lesser extent litter production, as mediated by time of occupancy. Forb and grass biomass were not significantly correlated with SOC and TN suggesting that changes in herbaceous vegetation have not been the driving force for the observed changes in SOC and TN. Because SOC and TN varied at two scales, it would be inappropriate to estimate SOC and TN pools at broad scales by extrapolating from point sampling at fine scales. Sampling designs that capture variation at multiple scales are required to estimate SOC and TN pools at broader scales. Knowledge of spatial scaling and correlations will be necessary to design field sampling protocols to quantify the biogeochemical consequences of woody plant encroachment at broad scales.     

不同群落蒙古栎种群空间格局的地统计学分析

以蒙古栎天然次生林中的蒙古栎种群为研究对象,在吉林省汪清林业局塔子沟林场设置2块1 hm^2的处于不同演替阶段的样地(A、B).采用相邻网格调查法将每块样地划分为100个10 m×10 m的调查单元,对单元内每株林木的空间坐标进行精确定位,调查所有胸径≥1 cm的林木基本信息.采用地统计学分析的半方差函数法和分维数对蒙古栎种群各林木属性的空间异质性程度、组成、尺度、方向进行分析;运用克里格插值法对具有空间自相关的树木属性进行无偏估计并绘制分布图,分析其空间分布格局.结果表明:两块样地各林木属性的最优半方差函数以指数模型和球状模型为主,呈聚集分布,但样地A较样地B的空间自相关程度更高,空间连续性更大;两块样地内部,胸径和东西冠幅均表现出较强的空间异质性和空间自相关性.两块样地各林木属性均在南北方向上表现出较强的空间异质性.此外,样地A在西北-东南方向上也存在较强的空间异质性,而样地B则在东北-西南方向存在较强的空间异质性.两者相比,样地A的空间异质性强度更高、尺度更大.样地A中胸径和东西冠幅变异明显,而样地B中东西冠幅和南北冠幅变异明显.分维数值反映的结果与标准半方差函数值的结果基本一致.样地A各林木属性变量以斑块状和条带状分布为主,空间分布格局和变化趋势明显,而样地B各林木属性变量分布破碎,格局复杂.上述结果说明,种群属性特征、群落发育程度、空间尺度大小和空间水平方向可能影响种群的空间格局.基于地统计学的分析方法有助于定量、直观地描述种群的生长现状和发展趋势,可为东北林区大面积的蒙古栎天然次生林的可持续经营提供理论基础.     

Additive Partitioning of Diversity Reveals No Scale-dependent Impacts of Large Ungulates on the Structure of Tundra Plant Communities

Large herbivores can change ecosystem functioning by impacting plant diversity. However, although such impacts are expected to be scale-dependent in ecosystems with wide-roaming ungulates, scaling issues rarely enter empirical assessments. We here test the hypothesis that the impact of increased reindeer abundance on plant diversity in alpine tundra is scale-dependent. Based on potentially high productivity of the focal habitat units and hence the possibility of positive grazer impacts on plant diversity we predicted higher α and β diversity at the habitat scale where reindeer densities are high. We also explored whether there were differences in diversity patterns at larger scales, including the scale of reindeer management districts. We estimated grazing disturbance as high versus low reindeer density in selected districts (a total extent of 7421 km²) of Northern Norway where reindeer-induced vegetation shifts are debated. We focus on dominance patterns because they can quantify the vegetation state and thus performed additive partitioning of Simpson diversity on multiple scales assessing also species’ contributions to diversity. Contrary to our predictions, we found only weak scale-dependent effects of reindeer grazing on plant diversity. Under high reindeer densities there was evidence for a landscape-scale homogenization of the vegetation, but the predicted α and β diversity increases at the habitat scale were not found. Consistently through all scales considered, four shrub species contributed the most to plant diversity. These results contradict the idea that reindeer at high stocking densities induce shifts in plant species dominance in productive habitats. We conclude that context-dependencies such as spatial scales of management units and habitat types need to be explicitly considered in evaluations of the impacts of large ungulates on plant diversity.     

Hydrological Networks and Associated Topographic Variation as Templates for the Spatial Organization of Tropical Forest Vegetation

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10–1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30–600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20–300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.     

Post‐fire regeneration in alpine heathland: Does fire severity matter?

Fire severity is thought to be an important determinant of landscape patterns of post‐fire regeneration, yet there have been few studies of the effects of variation in fire severity at landscape scales on floristic diversity and composition, and none within alpine vegetation. Understanding how fire severity affects alpine vegetation is important because fire is relatively infrequent in alpine environments. Globally, alpine ecosystems are at risk from climate change, which, in addition to warming, is likely to increase the severity and frequency of fire in south‐eastern Australia. Here we examine the effects of variation in fire severity on plant diversity and vegetation composition, 5 years after the widespread fires of 2003. We used floristic data from two wide‐spread vegetation types on the Bogong High Plains: open heathland and closed heathland. Three alternative models were tested relating variation in plant community attributes (e.g. diversity, ground cover of dominant species, amount of bare ground) to variation in fire severity. The models were (i) ‘linear’, attributes vary linearly with fire severity; (ii) ‘intermediate disturbance’, attributes are highest at intermediate fire severity and lowest at both low‐ and high‐severity; and (iii) ‘null’, attributes are unaffected by fire severity. In both heathlands, there were few differences in floristic diversity, cover of dominant species and community composition, across the strong fire severity gradient. The null model was most supported in the vast majority of cases, with only limited support for either the linear and intermediate disturbance models. Our data indicate that in both heathlands, vegetation attributes in burnt vegetation were converging towards that of the unburnt state. We conclude that fire severity had little impact on post‐fire regeneration, and that both closed and open alpine heathlands are resilient to variation in fire severity during landscape scale fires.     

Mapping forest vegetation patterns in an Atlantic-Mediterranean transitional area by integration of ordination and geostatistical techniques

Aims Forest vegetation variability may be explained by the complex interplay among several spatial structuring factors, including climate and topography. We modelled the spatial variability of forest vegetation assemblages and significant environmental variables along a complex environmental gradient or coenocline to produce a detailed cartographic database portraying the distribution of forests along it.Methods We combined an analysis of ordination coenoclines with kriging over 772 field data plots from the third Spanish National Forest Inventory in an Atlantic–Mediterranean transitional area (northern Spain).Important findings The best fitted empirical semivariogram revealed a strong spatial structure of forest species composition along the complex environmental gradient considered (the climatic–topographic gradient from north to south). The steady and gradual increase of semivariance with a marked lag distance indicates a gradual turnover of forest assemblages according to the climatic–topographic variations (regional or local). Two changes in the slope of the semivariogram suggest the existence of two different scales of spatial variation. The interpolation map by Kriging of forest vegetation assemblages along the main coenocline shows a clear spatial distribution pattern of trees and shrubs in accordance with the spatial variation of significant environmental variables. We concluded that the multivariate geostatistical approach is a suitable technique for spatial analysis of forest systems employing data from national forest inventories based on a regular network of field plots. The development of an assortment of maps describing changes in vegetation assemblages and variation in environmental variables is expected to be a suitable tool for an integrated forest management and planning.     

Global vegetation productivity response to climatic oscillations during the satellite era

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño‐Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global‐scale vegetation productivity than previously thought, although continental‐scale responses are substantial. There is also clear evidence that other non‐ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time.     

Application of geographically weighted regression in estimating the effect of climate and site conditions on vegetation distribution in Haihe Catchment,China

Climate and topography are the two key factors influencing vegetation pattern, distribution, and plant growth. Traditionally, studies on the relationship between vegetation and climate rely largely on field data from limited samples. Now, digital elevation model (DEM) and remote sensing data readily provide huge amounts of spatial data on site-specific conditions like elevation, aspect, and climate, while recent development of geographically weighted regression (GWR) analysis facilitates efficient spatial evaluation of interactions among vegetation and site conditions. Using Haihe Catchment as a case study, GWR is applied in establishing spatial relations among leaf area index (LAI; a critical vegetation index from Moderate Resolution Imaging Spectroradiometer (MODIS)) and interpolated climate variables and site conditions including elevation, aspect, and Topographic Wetness Index (TWI). This study suggests that the GWR solution to spatial effect of climate and site conditions on vegetation is much better than ordinary least squares (OLS). In most of the study area, effects of elevation, aspect change from south to north, and precipitation on LAI are positive, while temperature, TWI, and potential evapotranspiration have a negative influence. Spatially, models perform better in places with large spatial variations in LAI—primarily driven by strong spatial variations in temperature and precipitation. On the contrary, the effect of topographic and climatic factors on vegetation is weak in regions with small spatial variations in LAI. This study shows that overall water availability is a determining factor for spatial variations in vegetation.