Variation in leaf area index and stand leaf mass of European beech across gradients of soil acidity and precipitation

Leaf area index (LAI, the one-sided foliage area per unit ground surface area) is a key determinant of plant productivity which has a large influence on water and energy exchange between vegetation and the atmosphere. The variation in forest LAI across landscapes and environmental gradients and its causes are not sufficiently understood. We measured the LAI of European beech (Fagus sylvatica) by litter trapping in 23 closed, mature stands across gradients of rainfall and soil acidity or fertility. With a mean LAI of 7.4 m² m⁻² (minimum: 5.6, maximum: 9.5 m² m⁻²), beech stands maintained a comparably high leaf area index with relatively small variation along steep environmental gradients. Contrary to expectation, decreasing water availability (rainfall gradient from 1030 to 520 mm yr⁻¹) or increasing soil acidity (pH 3–7) had no significant effect on LAI. Stand leaf mass (M _l) increased slightly with soil fertility (C/N ratio, base saturation). We regressed parameters of site water availability (rainfall), soil fertility or acidity (pH, base saturation, C/N ratio, exchangeable Mg and Al content), and stand structure (stand age and stem density) against LAI and M _l in order to detect environmental controls of stand leaf area. Stand age was the most influential factor for both LAI and M _l (negative relationship). Stem density and the base saturation of the soil affected M _l significantly, but had a weak influence on LAI. We conclude that the leaf area index of beech is mainly under control of age-related physiological factors, whereas the influence of soil chemistry and rainfall is comparably low.     

Tight Coupling Between Shoot Level Foliar N and P,Leaf Area,and Shoot Growth in Arctic Dwarf Shrubs Under Simulated Climate Change

Nutrient availability limits productivity of arctic ecosystems, and this constraint means that the amount of nitrogen (N) in plant canopies is an exceptionally strong predictor of vegetation productivity. However, climate change is predicted to increase nutrient availability leading to increases in carbon sequestration and shifts in community structure to more productive species. Despite tight coupling of productivity with canopy nutrients at the vegetation scale, it remains unknown how species/shoot level foliar nutrients couple to growth, or how climate change may influence foliar nutrients–productivity relationships to drive changes in ecosystem carbon gain and community structure. We investigated the influence of climate change on arctic plant growth relationships to shoot level foliar N and phosphorus (P) in three dominant subarctic dwarf shrubs using an 18-year warming and nutrient addition experiment. We found a tight coupling between total leaf N and P per shoot, leaf area and shoot extension. Furthermore, a steeper shoot length-leaf N relationship in deciduous species (Vaccinium myrtillus and Vaccinium uliginosum) under warming manipulations suggests a greater capacity for nitrogen to stimulate growth under warmer conditions in these species. This mechanism may help drive the considerable increases in deciduous shrub cover observed already in some arctic regions. Overall, our work provides the first evidence at the shoot level of tight coupling between foliar N and P, leaf area and growth i.e. consistent across species, and provides mechanistic insight into how interspecific differences in alleviation of nutrient limitation will alter community structure and primary productivity in a warmer Arctic.     

Identifying Differences in Carbon Exchange among Arctic Ecosystem Types

Our objective was to determine how varied is the response of C cycling to temperature and irradiance in tundra vegetation. We used a large chamber to measure C exchange at 23 locations within a small arctic catchment in Alaska during summer 2003 and 2004. At each location, we determined light response curves of C exchange using shade cloths, twice during a growing season. We used data to fit a simple photosynthesis-irradiance, respiration-temperature model, with four parameters. We used a maximum likelihood technique to determine the acceptable parameter space for each light curve, given measurement uncertainty. We then explored which sites and time periods had parameter sets in common—an indication of functional similarity. We found that seven distinct parameter sets were required to explain observed C flux responses to temperature and light variation at all sites and time periods. The variation in estimated maximum photosynthetic rate (P_max) was strongly correlated with measurements of site leaf area index (LAI). The behavior of tussock tundra sites, the dominant vegetation of arctic tundra, could largely be described with a single parameter set, with a P_max of 9.7 μmol m⁻² s⁻¹. Tussock tundra sites had, correspondingly, similar LAI (mean = 0.66). Non-tussock sites (for example, sedge and shrub tundras) had larger spatial and temporal variations in both C dynamic parameters (P_max varying from 9.7–25.7 μmol m⁻² s⁻¹) and LAI (0.6–2.0). There were no clear relationships between dominant non-tussock vegetation types and a particular parameter set. Our results suggest that C dynamics of the acidic tussock tundra slopes and hilltops in northern Alaska are relatively simply described during the peak growing season. However, the foot-slopes and water tracks have more variable patterns of LAI and C exchange, not simply related to the dominant vegetation type.     

Leaf litterfall,leaf area index,and radiation transmittance in cypress wetlands and slash pine plantations in north-central Florida

The seasonal dynamics of leaf litterfall and leaf area index (LAI, all-sided basis), light penetration and the vertical distribution of surface area index, and the feasibility of estimating LAI from radiation transmittance were studied from April 1993 to March 1994 in the canopies of three cypress (Taxodium ascendens) wetlands and their surrounding slash pine (Pinus elliottii) uplands in Florida flatwoods. Annual leaf litterfall ranged from 324 to 359 g m^–2 in the wetlands, which was very close to the average for 11 sites throughout Florida of 340±26 g m^–2. The seasonal pattern of the normalized LAI obtained for the dominant tree species in the ecosystems could be used to construct the seasonal dynamics of LAI at the ecosystem scale. The vertical distribution of surface area index in the wetlands was significantly different from that in the surrounding pine uplands. The maximum LAI of cypress wetlands in this area was about 8 m² m^–2, which was higher than the maximum of slash pine plantations of 6 m² m^–2. Cypress leaves were strongly erectophile in space. Results showed that the LAI-2000 canopy analyzer could generally be used to estimate forest LAI, whether the forest canopy was closed or not, if an overall clumping index of 2.00 was applied. However, as LAI decreased, the relative error contained in the radiation-based LAI estimates increased. This indicated that foliage clumping at the stand scale was more important than that at the tree or branch scale.     

Estimates of leaf-area index for the territory of Russia using State Forest Inventory data

The 2007 State Forest Inventory (SFI) data have been used at two scales of spatial resolution: the datasets of the forest regions (31) and the forest-management basic units (1900) to estimate the leafarea index (LAI, m² m^–2) of forests in Russia. The area and yield data on all 66 tree species recorded in the SFI offer the opportunity to obtain the wood specific gravity values U (m³ ha^–1) for all these tree species. The conversion coefficients of yield to leaf phytomass per unit area (t m^–3) and the projected specific leaf areas (SLAs) (cm² g^–1) are used to estimate the LAI. The obtained LAI values are similar to the average ground and remote-sensing estimates (the given review for July includes eighteen literature sources). The highest LAI values can be observed in the middle taiga subzone in the European part of Russia and in the Angara River regions. The LAI estimates may be used to compute the productivity of the forest ecosystems at different scales of analysis and to extrapolate the calibrated data acquired with remote control techniques.     

Canopy structure in savannas along a moisture gradient on Kalahari sands

Measurements of tree canopy architecture were made at six savanna sites on deep, sandy soils, along a gradient of increasing aridity. There was substantial variation in the leaf area estimated within each site, using the same sample frame, but different measurement techniques. The trends in canopy properties in relation to the aridity gradient were consistent, regardless of the technique used for estimating the properties. The effective plant area index for the tree canopy (the sum of the stem area index and the leaf area index (LAI)) declined from around 2 to around 0.8 m² m^?2 over a gradient of mean annual rainfall from 1000 to 350 mm. Stems contributed 2–5% of the tree canopy plant area index. Since the tree canopy cover decreased from 50% to 20% over this aridity range, the leaf area index within the area covered by tree canopies remained fairly constant at 3–4 m² m^?2. Tree leaves tended from a horizontal orientation to a more random orientation as the aridity increased. On the same gradient, the leaf minor axis dimension decreased from around 30 mm to around 3 mm, and the mean specific leaf area decreased from 14 to 5 m² kgha^?1. There was good agreement between LAI observed in the field using a line ceptometer and the LAI inferred by the MODIS sensor on the Terra satellite platform, 2 months later in the same season.     

Altitudinal Change in LAI and Stand Leaf Biomass in Tropical Montane Forests: a Transect Study in Ecuador and a Pan-Tropical Meta-Analysis

Abstract Leaf area index (LAI) is a key parameter controlling plant productivity and biogeochemical fluxes between vegetation and the atmosphere. Tropical forests are thought to have comparably high LAIs; however, precise data are scarce and environmental controls of leaf area in tropical forests are not understood. We studied LAI and stand leaf biomass by optical and leaf mass-related approaches in five tropical montane forests along an elevational transect (1,050–3,060 m a.s.l.) in South Ecuador, and conducted a meta-analysis of LAI and leaf biomass data from tropical montane forests around the globe. Study aims were (1) to assess the applicability of indirect and direct approaches of LAI determination in tropical montane forests, (2) to analyze elevation effects on leaf area, leaf mass, SLA, and leaf lifespan, and (3) to assess the possible consequences of leaf area change with elevation for montane forest productivity. Indirect optical methods of LAI determination appeared to be less reliable in the complex canopies than direct leaf mass-related approaches based on litter trapping and a thorough analysis of leaf lifespan. LAI decreased by 40–60% between 1,000 and 3,000 m in the Ecuador transect and also in the pan-tropical data set. This decrease indicates that canopy carbon gain, that is, carbon source strength, decreases with elevation in tropical montane forests. Average SLA decreased from 88 to 61 cm² g⁻¹ whereas leaf lifespan increased from 16 to 25 mo between 1,050 and 3,060 m in the Ecuador transect. In contrast, stand leaf biomass was much less influenced by elevation. We conclude that elevation has a large influence not only on the leaf traits of trees but also on the LAI of tropical montane forests with soil N (nitrogen) supply presumably being the main controlling factor.     

林地叶面积指数遥感估算方法适用分析

叶面积指数是与森林冠层能量和CO2交换密切相关的一个重要植被结构参数,为了探讨估算林地叶面积指数LAI的遥感适用方法和提高精度的途径,利用TRAC仪器测定北京城区森林样地的LAI,从Landsat TM遥感图像计算NDVI、SR、RSR、SAVI植被指数,分别建立估算LAI的单植被指数统计模型、多植被指数组合的改进BP神经网络,获取最有效描述LAI与植被指数非线性关系的方法并应用到TM图像估算北京城区LAI。结果表明,单植被指数非线性统计模型估算LAI的精度高于线性统计模型;多植被指数组合神经网络中,以NDVI、RSR、SAVI组合估算LAI的精度最高,估算值与观测值线性回归方程的R2最高,为0.827,而RMSE最低,为0.189,神经网络解决了多植被指数组合统计模型非线性回归方程的系数较多、较难确定的问题,可较为有效的应用于遥感图像林地LAI的估算。     

华南地区亚热带树木叶面积指数的高光谱反演研究

为构建树种叶面积指数的估算模型,以NDVI、RVI、FREP、CIGreen、CIRed-edge、MSAVI2为高光谱特征变量,通过统计分析,确定反演树种叶面积指数的最佳光谱特征变量,构建华南农业大学校园内50种亚热带树木的叶片反射率和叶面积指数(LAI)模型。结果表明,6种高光谱特征变量与树种叶面积指数间都具有极显著相关性,其中红边位置反射率(FREP)和比值植被指数(RVI)与LAI的拟合方程的R2都大于0.8,决定系数分别为0.820和0.811。经过精度验证,FREP估算的均方根误差(RMSE)只有0.13,该回归模型为估测亚热带典型树种的叶片LAI最佳模型。从高光谱遥感的角度结合亚热带植被的群落结构特点来看,建立的红边位置光谱反射率与叶面积指数的回归模型普遍具有较高的拟合度,所以利用高光谱特征变量反演亚热带树木叶片的叶面积指数等植被参数的应用前景较好。     

Effects of vegetation control on ecosystem water use efficiency within and among four grassland ecosystems in China

Through 2–3-year (2003–2005) continuous eddy covariance measurements of carbon dioxide and water vapor fluxes, we examined the seasonal, inter-annual, and inter-ecosystem variations in the ecosystem-level water use efficiency (WUE, defined as the ratio of gross primary production, GPP, to evapotranspiration, ET) at four Chinese grassland ecosystems in the Qinghai-Tibet Plateau and North China. Representing the most prevalent grassland types in China, the four ecosystems are an alpine swamp meadow ecosystem, an alpine shrub-meadow ecosystem, an alpine meadow-steppe ecosystem, and a temperate steppe ecosystem, which illustrate a water availability gradient and thus provide us an opportunity to quantify environmental and biological controls on ecosystem WUE at different spatiotemporal scales. Seasonally, WUE tracked closely with GPP at the four ecosystems, being low at the beginning and the end of the growing seasons and high during the active periods of plant growth. Such consistent correspondence between WUE and GPP suggested that photosynthetic processes were the dominant regulator of the seasonal variations in WUE. Further investigation indicated that the regulations were mainly due to the effect of leaf area index (LAI) on carbon assimilation and on the ratio of transpiration to ET ( T /ET). Besides, except for the swamp meadow, LAI also controlled the year-to-year and site-to-site variations in WUE in the same way, resulting in the years or sites with high productivity being accompanied by high WUE. The general good correlation between LAI and ecosystem WUE indicates that it may be possible to predict grassland ecosystem WUE simply with LAI. Our results also imply that climate change-induced shifts in vegetation structure, and consequently LAI may have a significant impact on the relationship between ecosystem carbon and water cycles in grasslands.     

Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna

Interactions between trees and grasses that influence leaf area index (LAI) have important consequences for savanna ecosystem processes through their controls on water, carbon, and energy fluxes as well as fire regimes. We measured LAI, of the groundlayer (herbaceous and woody plants <1-m tall) and shrub and tree layer (woody plants >1-m tall), in the Brazilian cerrado over a range of tree densities from open shrub savanna to closed woodland through the annual cycle. During the dry season, soil water potential was strongly and positively correlated with grass LAI, and less strongly with tree and shrub LAI. By the end of the dry season, LAI of grasses, groundlayer dicots and trees declined to 28, 60, and 68% of mean wet-season values, respectively. We compared the data to remotely sensed vegetation indices, finding that field measurements were more strongly correlated to the enhanced vegetation index (EVI, r ²=0.71) than to the normalized difference vegetation index (NDVI, r ²=0.49). Although the latter has been more widely used in quantifying leaf dynamics of tropical savannas, EVI appears better suited for this purpose. Our ground-based measurements demonstrate that groundlayer LAI declines with increasing tree density across sites, with savanna grasses being excluded at a tree LAI of approximately 3.3. LAI averaged 4.2 in nearby gallery (riparian) forest, so savanna grasses were absent, thereby greatly reducing fire risk and permitting survival of fire-sensitive forest tree species. Although edaphic conditions may partly explain the larger tree LAI of forests, relative to savanna, biological differences between savanna and forest tree species play an important role. Overall, forest tree species had 48% greater LAI than congeneric savanna trees under similar growing conditions. Savanna and forest species play distinct roles in the structure and dynamics of savanna–forest boundaries, contributing to the differences in fire regimes, microclimate, and nutrient cycling between savanna and forest ecosystems.     

Satellite‐based evidence for shrub and graminoid tundra expansion in northern Quebec from 1986 to 2010

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air‐photo studies have documented recent changes in high‐latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24‐year (1986–2010) Landsat time series in a latitudinal transect across the boreal forest‐tundra biome boundary in northern Quebec province, Canada. This region has experienced rapid warming during both winter and summer months during the last 40 years. Using a per‐pixel (30 m) trend analysis, 30% of the observable (cloud‐free) land area experienced a significant (P < 0.05) positive trend in the Normalized Difference Vegetation Index (NDVI). However, greening trends were not evenly split among cover types. Low shrub and graminoid tundra contributed preferentially to the greening trend, while forested areas were less likely to show significant trends in NDVI. These trends reflect increasing leaf area, rather than an increase in growing season length, because Landsat data were restricted to peak‐summer conditions. The average NDVI trend (0.007 yr^?1) corresponds to a leaf‐area index (LAI) increase of ~0.6 based on the regional relationship between LAI and NDVI from the Moderate Resolution Spectroradiometer. Across the entire transect, the area‐averaged LAI increase was ~0.2 during 1986–2010. A higher area‐averaged LAI change (~0.3) within the shrub‐tundra portion of the transect represents a 20–60% relative increase in LAI during the last two decades. Our Landsat‐based analysis subdivides the overall high‐latitude greening trend into changes in peak‐summer greenness by cover type. Different responses within and among shrub, graminoid, and tree‐dominated cover types in this study indicate important fine‐scale heterogeneity in vegetation growth. Although our findings are consistent with community shifts in low‐biomass vegetation types over multi‐decadal time scales, the response in tundra and forest ecosystems to recent warming was not uniform.     

Relationships between soil microbial properties and aboveground stand characteristics of conifer forests in Oregon

Eight forest sites representing a large range of climate, vegetation, and productivity were sampled in a transect across Oregon to study the relationships between aboveground stand characteristics and soil microbial properties. These sites had a range in leaf area index of 0.6 to 16 m² m^–2 and net primary productivity of 0.3 to 14 Mg ha^–1 yr^–1.Measurements of soil and forest floor inorganic N concentrations and in situ net N mineralization, nitrification, denitrification, and soil respiration were made monthly for one year. Microbial biomass C and anaerobic N mineralization, an index of N availability, were also measured. Annual mean concentrations of NH ₄ ⁺ ranged from 37 to 96 mg N kg^–1 in the forest floor and from 1.7 to 10.7 mg N kg^–1 in the mineral soil. Concentrations of NO ₃ ^– were low ( < 1 mg N kg^–1) at all sites. Net N mineralization and nitrification, as measured by the buried bag technique, were low on most sites and denitrification was not detected at any site. Available N varied from 17 to 101 mg N kg^–1, microbial biomass C ranged from 190 to 1230 mg Ckg^–1, and soil respiration rates varied from 1.3 to 49 mg C kg^–1 day^–1 across these sites. Seasonal peaks in NH ₄ ⁺ concentrations and soil respiration rates were usually observed in the spring and fall.The soils data were positively correlated with several aboveground variables, including leaf area index and net primary productivity, and the near infrared-to-red reflectance ratio obtained from the airborne simulator of the Thematic Mapper satellite. The data suggest that close relationships between aboveground productivity and soil microbial processes exist in forests approaching semi-equilibrium conditions.Abbreviations IR infrared - LAI leaf area index - k _c proportion of microbial biomass C mineralized to CO₂ - NPP net primary productivity - TM Thematic Mapper     

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。     

Impact of tropospheric ozone on the Euro‐Mediterranean vegetation

The impact of ozone (O₃) on European vegetation is largely under‐investigated, despite huge areas of Europe are exposed to high O₃ levels and which are expected to increase in the next future. We studied the potential effects of O₃ on photosynthesis and leaf area index (LAI) as well as the feedback between vegetation and atmospheric chemistry using a land surface model (ORCHIDEE) at high spatial resolution (30 km) coupled with a chemistry transport model (CHIMERE) for the whole year 2002. Our results show that the effect of tropospheric O₃ on vegetation leads to a reduction in yearly gross primary production (GPP) of about 22% and a reduction in LAI of 15–20%. Larger impacts have been found during summer, when O₃ reaches higher concentrations. During these months the maximum GPP decrease is up to 4 g C m^?2 day^?1, and the maximum LAI reduction is up to 0.7 m² m^?2. Since CHIMERE uses the LAI computed by ORCHIDEE to estimate the biogenic emissions, a LAI reduction may have severe implications on the simulated atmospheric chemistry. We found a large change in O₃ precursors that however leads to small changes in tropospheric O₃ concentration, while larger changes have been found for surface NO₂ concentrations.     

2020-2050年CO2施肥效应促进全球陆地生态系统碳吸收

CO₂施肥效应是全球变绿的主要原因,随着大气中CO₂浓度的持续增加,预估未来气候变化条件下,CO₂施肥效应对陆地生态系统的影响对减缓全球气候变化具有重大意义。基于未来气候情景数据和Farquhar模型,并结合生态过程模型BEPS(Boreal Ecosystem Productivity Simulator),定量化研究2020—2050年CO₂施肥效应对全球叶面积指数(LAI)和总初级生产力(GPP)的影响。研究结果显示2020—2050年,在RCP2.6、RCP4.5和RCP8.5气候情景下,CO₂施肥效应导致的LAI年际变化趋势分别为0.002、0.003和0.005 m^-2m^-2a^-1;三个气候情景下CO₂施肥效应对LAI的影响为CO₂每增加0.1%,LAI平均增加约8.1%—9.2%,由此导致GPP对应增加7.9%—14.6%;由CO₂施...     

Estimation of big sagebrush leaf area index with terrestrial laser scanning

Accurate monitoring and quantification of the structure and function of semiarid ecosystems is necessary to improve carbon and water flux models that help describe how these systems will respond in the future. The leaf area index (LAI, m² m⁻²) is an important indicator of energy, water, and carbon exchange between vegetation and the atmosphere. Remote sensing techniques are frequently used to estimate LAI, and can provide users with scalable measurements of vegetation structure and function. We tested terrestrial laser scanning (TLS) techniques to estimate LAI using structural variables such as height, canopy cover, and volume for 42 Wyoming big sagebrush (Artemisia tridentata subsp. wyomingensis Beetle & Young) shrubs across three study sites in the Snake River Plain, Idaho, USA. The TLS-derived variables were regressed against sagebrush LAI estimates calculated using specific leaf area measurements, and compared with point-intercept sampling, a field method of estimating LAI. Canopy cover estimated with the TLS data proved to be a good predictor of LAI (r² = 0.73). Similarly, a convex hull approach to estimate volume of the shrubs from the TLS data also strongly predicted LAI (r² = 0.76), and compared favorably to point-intercept sampling (r² = 0.78), a field-based method used in rangelands. These results, coupled with the relative ease-of-use of TLS, suggest that TLS is a promising tool for measuring LAI at the shrub-level. Further work should examine the structural measures in other similar shrublands that are relevant for upscaling LAI to the plot-level (i.e., hectare) using data from TLS and/or airborne laser scanning and to regional levels using satellite-based remote sensing.     

Using Information Theory to Determine Optimum Pixel Size and Shape for Ecological Studies: Aggregating Land Surface Characteristics in Arctic Ecosystems

Quantifying vegetation structure and function is critical for modeling ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Land surface heterogeneity is commonly characterized using rectangular pixels, whose length scale reflects that of remote sensing measurements or ecological models rather than the spatial scales at which vegetation structure and function varies. We investigated the ‘optimum’ pixel size and shape for averaging leaf area index (LAI) measurements in relatively large (85 m² estimates on a 600 × 600-m² grid) and small (0.04 m² measurements on a 40 × 40-m² grid) patches of sub-Arctic tundra near Abisko, Sweden. We define the optimum spatial averaging operator as that which preserves the information content (IC) of measured LAI, as quantified by the normalized Shannon entropy (E _S,n) and Kullback–Leibler divergence (D _KL), with the minimum number of pixels. Based on our criterion, networks of Voronoi polygons created from triangulated irregular networks conditioned on hydrologic and topographic indices are often superior to rectangular shapes for averaging LAI at some, frequently larger, spatial scales. In order to demonstrate the importance of information preservation when upscaling, we apply a simple, validated ecosystem carbon flux model at the landscape level before and after spatial averaging of land surface characteristics. Aggregation errors are minimal due to the approximately linear relationship between flux and LAI, but large errors of approximately 45% accrue if the normalized difference vegetation index (NDVI) is averaged without preserving IC before conversion to LAI due to the nonlinear NDVI-LAI transfer function. Author Contributions:  PS devised and undertook the analyses and wrote the paper. MW devised and implemented the measurement plan, and reviewed the analysis. LS assisted in the spatial data analysis and derivation of the terrain indices. RAB provided the macro-scale dataset. APB generated the DEM from aircraft data. JGE provided meteorological data. MvW generated the micro-scale field data with the help of Lorna Street and Sven Rasmussen. All authors contributed to the text.     

Effects of precipitation and soil water potential on drought deciduous phenology in the Kalahari

We utilized an ecosystem process model to investigate the influence of precipitation and soil water potential on vegetation phenology in the semi‐arid, drought‐deciduous ecosystems in the Kalahari region of South Africa. The timing of leaf flush was assumed to be the first day during which a rainfall event exceeded that day's estimate of potential evapotranspiration after a defined dry season. Leaf senescence was assumed to be a dynamic feedback between soil water potential and net plant carbon gain and was determined by dynamically modeling the effects of concomitant trends in soil water potential and net primary production on leaf area index (LAI). Model predictions of LAI were compared with satellite‐derived normalized difference vegetation indices (NDVI) for 3 years at two sites along the Kalahari transect. The mean absolute error for the prediction of modeled leaf flush date compared with leaf flush dates estimated from NDVI were 10.0 days for the Maun site and 39.3 days for the Tshane site. Correlations between model predicted 10‐day average LAI and 10‐day composite NDVI for both Maun and Tshane were high (ρ=0.67 and 0.74, respectively, P<0.001), suggesting that this method adequately predicts intra‐annual leaf area dynamics in these dry tropical ecosystems.     

Greater deciduous shrub abundance extends tundra peak season and increases modeled net CO2 uptake

Satellite studies of the terrestrial Arctic report increased summer greening and longer overall growing and peak seasons since the 1980s, which increases productivity and the period of carbon uptake. These trends are attributed to increasing air temperatures and reduced snow cover duration in spring and fall. Concurrently, deciduous shrubs are becoming increasingly abundant in tundra landscapes, which may also impact canopy phenology and productivity. Our aim was to determine the influence of greater deciduous shrub abundance on tundra canopy phenology and subsequent impacts on net ecosystem carbon exchange (NEE) during the growing and peak seasons in the arctic foothills region of Alaska. We compared deciduous shrub‐dominated and evergreen/graminoid‐dominated community‐level canopy phenology throughout the growing season using the normalized difference vegetation index (NDVI). We used a tundra plant‐community‐specific leaf area index (LAI) model to estimate LAI throughout the green season and a tundra‐specific NEE model to estimate the impact of greater deciduous shrub abundance and associated shifts in both leaf area and canopy phenology on tundra carbon flux. We found that deciduous shrub canopies reached the onset of peak greenness 13 days earlier and the onset of senescence 3 days earlier compared to evergreen/graminoid canopies, resulting in a 10‐day extension of the peak season. The combined effect of the longer peak season and greater leaf area of deciduous shrub canopies almost tripled the modeled net carbon uptake of deciduous shrub communities compared to evergreen/graminoid communities, while the longer peak season alone resulted in 84% greater carbon uptake in deciduous shrub communities. These results suggest that greater deciduous shrub abundance increases carbon uptake not only due to greater leaf area, but also due to an extension of the period of peak greenness, which extends the period of maximum carbon uptake.