Biomass estimation using satellite remote sensing data—An investigation on possible approaches for natural forest

Vegetation type and its biomass are considered important components affecting biosphere-atmosphere interactions. The measurements of biomass per unit area and productivity have been set as one of the goals for International Geosphere-Biosphere Programme (IGBP). Ground assessment of biomass, however, has been found insufficient to present spatial extent of the biomass. The present study suggests approaches for using satellite remote sensing data for regional biomass mapping in Madhav National Park (MP). The stratified random sampling in the homogeneous vegetation strata mapped using satellite remote sensing has been effectively utilized to extrapolate the sample point biomass observations in the first approach. In the second approach attempt has been to develop empirical models with satellite measured spectral response and biomass. The results indicate that there is significant relationships with spectral responses. These relationships have seasonal dependency in varying phonological conditions. The relationships are strongest in visible bands and middle infrared bands. However, spectral biomass models developed using middle infrared bands would be more reliable as compared to the visible bands as the later spectral regions are less sensitive to atmospheric changes It was observed that brightness and wetness parameters show very strong relationship with the biomass values. Multiple regression equations using brightness and wetness isolates have been used to predict biomass values. The model used has correlation coefficient of 0.77. Per cent error between observed and predicted biomass was 10.5%. The biomass estimated for the entire national park using stratified and spectral response modelling approaches were compared and showed similarity with the difference of only 4.69%. The results indicate that satellite remote sensing data provide capability of biomass estimation     

基于夜间灯光数据的环杭州湾城市扩张及植被变化

综合运用遥感与GIS技术,基于2000、2007和2013年的DMSP/OLS夜间灯光数据和MODIS NDVI数据,利用灯光阈值提取法、植被指数分析等方法,研究环杭州湾地区城市扩张和建成区植被变化特征.结果表明: 采用最佳阈值方法,能够实现对城市地区用地信息的有效提取;环杭州湾地区城市用地整体围绕杭州湾呈“V”型模式扩展,并表现出面状、线状和点状3种扩张模式;从城市扩张速度、动态度和形态紧凑度来看,各地级市表现出较大的时空差异,但整个研究区的城市扩张速度和动态度普遍呈现降低趋势,平均城市形态紧凑度则经历了先下降后上升的过程.各城市建成区的植被状况也存在显著差异,2000—2007年,除嘉兴市建成区植被状况变差外,其余各地级市建成区植被状况均变好;2007—2013年,所有城市建成区植被状况变差;2000—2013年,城市扩张对建成区植被均产生了不利影响.     

Reconstructing pre-impact vegetation cover in modified landscapes using environmental modelling, historical surveys and remnant vegetation data: a case study in the Fleurieu Peninsula, South Australia

Aim To investigate the application of environmental modelling to reconstructive mapping of pre‐impact vegetation using historical survey records and remnant vegetation data. Location The higher elevation regions of the Fleurieu Peninsula region in South Australia were selected as a case study. The Fleurieu Peninsula is an area typical of many agricultural regions in temperate Australia that have undergone massive environmental transformation since European settlement. Around 9% of the present land cover is remnant vegetation and historical survey records from the ad 1880s exist. It is a region with strong gradients in climate and topography. Methods Records of pre‐impact vegetation distribution made in surveyors’ field notebooks were transcribed into a geographical information system and the spatial and classificatory accuracy of these records was assessed. Maps of remnant vegetation distribution were obtained. Analysis was undertaken to quantify the environmental domains of historical survey record and remnant vegetation data to selected meso‐scaled climatic parameters and topo‐scaled terrain‐related indices at a 20 m resolution. An exploratory analytical procedure was used to quantify the probability of occurrence of vegetation types in environmental domains. Probability models spatially extended to geographical space produce maps of the probability of occurrence of vegetation types. Individual probability maps were combined to produce a pre‐impact vegetation map of the region. Results Surveyors’ field notebook records provide reliable information that is accurately locatable to levels of resolution such that the vegetation data can be spatially correlated with environmental variables generated on 20 m resolution environmental data sets. Historical survey records of vegetation were weakly correlated with the topo‐scaled environmental variables but were correlated with meso‐scaled climate. Remnant vegetation records similarly not only correlated to climate but also displayed stronger relationships with the topo‐scaled environmental variables, particularly slope. Main conclusions A major conclusion of this study is that multiple sources of evidence are required to reconstruct past vegetation patterns in heavily transformed region. Neither the remnant vegetation data nor historical survey records provided adequate data sets on their own to reconstruct the pre‐impact vegetation of the Fleurieu Peninsula. Multiple sources of evidence provide the only means of assessing the environmental and historical representativeness of data sets. The spatial distribution of historical survey records was more environmentally representative than remnant vegetation data, which reflect biases due to land clearance. Historical survey records were also shown to be classificatory and spatially accurate, thus are suitable for quantitative spatial analyses. Analysis of different spatial vegetation data sets in an environmental modelling framework provided a rigorous means of assessing and comparing respective data sets as well as mapping their predicted distributions based on quantitative correlations. The method could be usefully applied to other regions where predictions of pre‐impact vegetation cover are required.     

Relationships among fire frequency, rainfall and vegetation patterns in the wet–dry tropics of northern Australia: an analysis based on NOAA-AVHRR data

Aim To quantify the regional‐scale spatio‐temporal relationships among rainfall, vegetation and fire frequency in the Australian wet–dry tropics (AWDT). Location Northern Australia: Cape York Peninsula, central Arnhem, central Kimberly, Einasleigh Uplands, Gulf Fall Uplands and northern Kimberley. Methods Monthly ‘fraction of photosynthetic active radiation absorbed by green vegetation’ (fAPAR) was decomposed into monthly evergreen (EG) and monthly raingreen (RG) components using time‐series techniques applied to monthly normalized difference vegetation index (NDVI) data from Advanced Very High Resolution Radiometer (AVHRR) imagery. Fire affected areas were independently mapped at the same spatio‐temporal resolution from AVHRR imagery. Weather station records were spatially interpolated to create monthly rainfall surfaces. Vegetation structural classes were derived from a digitized map of northern Australian vegetation communities (1 : 1,000,000). Generalized linear models were used to quantify relationships among the fAPAR, EG and RG signals, vegetation structure, rainfall and fire frequency, for the period November 1996–December 2001. Results The fAPAR and EG signals are positively correlated with annual rainfall and canopy cover, notably: EG_{closed forest} > EG_{open heathland} > EG_{open forest} > EG_woodland > EG_{open woodland} > EG_{low woodland} > EG_{low open woodland} > EG_{open grassland}. Vegetation height and fAPAR are positively correlated, excluding the special case of open heathland. The RG signal is highest where intermediate annual rainfall and strong seasonality in rainfall coincide, and is associated with vegetation structure as follows: RG_{open grassland} > RG_woodland > RG_{open forest} > RG_{open heathland} > RG_{low woodland} > RG_{open woodland} > RG_{low open woodland} > RG_{closed forest}. Monthly RG tracks monthly rainfall. Annual proportion of area burnt (PB) is maximal where high RG coincides with low EG (open grassland, several woodland communities). PB is minimal in vegetation where both RG and EG are low (low open woodland); and in vegetation where EG is high (closed forest, open heathland). Conclusions The RG–EG scheme successfully reflects digitally mapped tree and grass covers in relation to rainfall. RG–EG patterns are strongly associated with fire frequency patterns. PB is maximal in areas of high RG, where high biomass production during the wet season supports abundant fine fuel during the dry season. PB is minimal in areas with high EG, where relatively moist fuel limits fire ignition; and in areas with low EG and RG, where a relative short supply of fuel limits fire spread.     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.     

中国不同植被类型归一化植被指数对气候变化和人类活动的响应

不同植被类型对外界干扰和环境变化的敏感性不同。为厘清中国不同类型植被的动态变化特征及其对外界环境变化的响应,综合利用趋势分析、残差分析和情景模拟方法,在明确2000-2015年间我国不同植被类型归一化植被指数(NDVI)时空变化基础上,对气候变化和人类活动两大驱动要素在不同植被类型NDVI变化中的相对贡献进行了定量评估和归因。研究结果表明:(1)2000-2015年,我国植被NDVI整体呈增加趋势,且其空间占比高达84.1%。其中,森林植被的改善状况最佳,显著增加的面积占到了森林总面积的82.4%;而荒漠植被的改善状况相对较差,仅有22.3%的区域呈显著增加趋势。(2)人类活动在我国植被变化中占主导地位。植被改善区和植被退化区人类活动的相对贡献分别为76.4%和60.0%,且人类活动对植被的影响更多与管理方式而非土地利用类型转变有关。(3)不同类型植被对气候变化和人类活动的响应差异显著。对于植被改善区,除沼泽外,人类活动对各类型植被NDVI变化的贡献率均在70%以上,尤其是对农作物的贡献率最高,达到80.7%;对于植被退化区,人类活动影响较大的植被类型为沼泽和农作物,表明2000-2015年间我国沼泽受到了更强烈人类活动的负面影响。研究有助于增强对不同植被类型对全球变化响应机制的理解,并为促进生态建设和植被恢复工作的有效实施提供科学参考。     

Estimating mixtures of leaf functional types using continental-scale satellite and climatic data

Aim Recent research has shown that much of the variability in leaf gas exchange and leaf longevity can be related to variations in the surface : volume ratio of leaves. The aim of this paper was to develop a theoretical framework and a practical method to extend that result to the vegetation at the continental scale. Location The study was conducted in Australia. Methods We propose that vegetation is composed of a mixture of three basic leaf types, ‘turgor’ (T), ‘mesic’ (M) and ‘sclerophyll’ (S) leaves. Changes in the relative proportions of T, M and S leaves within a vegetation type are visualized using a ternary diagram and differences in vegetation structure are shown to be easily mapped onto the ternary diagram. We estimate the proportions of T, M and S leaves using readily available data. The total amount of PAR absorbed by the vegetation (fPAR) is estimated using continental‐scale satellite observations. The total fPAR is then decomposed into that absorbed by T, M and S leaves. The relative absorption of PAR by T leaves is estimated from the temporal dynamics in the satellite signal, while the relative proportions of M and S leaves are estimated using climatic (solar radiation, rainfall) data. Results When the availability of light, nutrients and water were near‐optimal, the vegetation was composed of predominantly M leaves. In low nutrient environments S leaves predominated. T leaves were dominant in disturbed environments. Conclusions The theoretical framework is used to predict that elevated atmospheric CO₂ would tend to increase the proportion of M and S leaves in an ecosystem and the resulting change means that the proportion of T leaves would decrease. In terms of the TMS scheme, this implies that elevated CO₂ has the same net effect on the vegetation as a decrease in disturbance.     

Univariate analysis of tsetse habitat in the common fly belt of Southern Africa using climate and remotely sensed vegetation data

Abstract Tsetse are vectors of trypanosomes that cause diseases both in humans and livestock. Traditional tsetse surveys, using sampling methods such as Epsilon traps and black screen fly rounds, are often logistically difficult, costly and time-consuming. The distribution of tsetse, as revealed by such survey methods, is strongly influenced by environmental conditions, such as climate and vegetation cover, which may be readily mapped using satellite data. These data may be used to make predictions of the probable distribution of tsetse in unsurveyed areas by determining the environmental characteristics of areas of tsetse presence and absence in surveyed areas. The same methods may also be used to characterize differences between tsetse species and subspecies. In this paper we analyse the distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes in southern Africa with respect to single environmental variables. For G.m.centralis the best predictions were made using the average NDVI (75% correct predictions; range > 0.37) and the average of the maximum temperature (70% correct predictions; 27.0–29.2°C). For G.m.morsitans the best prediction was given by the maximum of the minimum temperature (84% correct predictions; range > 18.8°C), and for G.pallidipes , also by the maximum of the minimum temperature (86% correct predictions; range > 19.6 °C). The following paper compares a range of multivariate techniques for making predictions about the distribution of these species in the same region.     

Estimation of Mediterranean forest transpiration and photosynthesis through the use of an ecosystem simulation model driven by remotely sensed data

Aim This paper investigates the use of an ecosystem simulation model, FOREST‐BGC, to estimate the main ecophysiological processes (transpiration and photosynthesis) of Mediterranean coastal forest areas using remotely sensed data. Location Model testing was carried out at two protected forest sites in central Italy, one of which was covered by Turkey oak (Circeo National Park) and the other by holm‐oak (Castelporziano Estate). Methods At both sites, transpiration and photosynthesis measurements were collected in the field during the growing seasons over a four‐year period (1999 and 2001 for the Turkey oak; 1997, 1999 and 2000 for the holm‐oak). Calibration of the model was obtained through combining information derived from ground measurements and remotely sensed data. In particular, remote sensing estimates of the Leaf Area Index derived from 1 × 1‐km NOAA AVHRR Normalized Difference Vegetation Index data were used to improve the adaptation of the model to local forest conditions. Results The results indicated different strategies regarding water use efficiency, ‘water spending’ for Turkey oak and ‘water saving’ for holm‐oak. The water use efficiency for the holm‐oak was consistently higher than that for the Turkey oak and the relationship between VPD and WUE for the holm‐oak showed a higher coefficient of determination (R² = 0.9238). Comparisons made between the field measurements of transpiration and photosynthesis and the model estimates showed that the integration procedure used for the deciduous oak forest was effective, but that there is a need for further studies regarding the sclerophyllous evergreen forest. In particular, for Turkey oak the simulations of transpiration yielded very good results, with errors lower than 0.3 mm H₂O/day, while the simulation accuracy for photosynthesis was lower. In the case of holm‐oak, transpiration was markedly overestimated for all days considered, while the simulations of photosynthesis were very accurate. Main conclusions Overall, the approach offers interesting operational possibilities for the monitoring of Mediterranean forest ecosystems, particularly in view of the availability of new satellite sensors with a higher spatial and temporal resolution, which have been launched in recent years.     

Detection of trend and seasonal changes in non-stationary remote sensing data: Case study of Tunisia vegetation dynamics

The availability of long-term time series (TS) derived from remote sensing (RS) images is favorable for the analysis of vegetation variation and dynamics. However, the choice of appropriate methods is a challenging task. This article presented an experimental comparison of four methods widely used for the detection of long-term trend and seasonal changes of TS, with a case study in north-western Tunisia. The four methods are the Ensemble Empirical Mode Decomposition (EEMD), Multi-Resolution Analysis-Wavelet transform (MRA-WT), Breaks for Additive Season and Trend (BFAST), and Detecting Breakpoints and Estimating Segments in Trend (DBEST). Their efficiencies were compared by analysing Normalized Difference Vegetation Index (NDVI) TS from 2001 to 2017 in the study area, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The variations of long-term NDVI trends were analysed using non-parametric statistical tests. Results indicated that MRA-WT gave efficient results for both trend and seasonal changes, especially in forest area. Moreover, it exhibited the fastest efficiency in terms of time of execution and thus recommended for detecting detailed features (such as forest fire detection). DBEST also showed a good performance for trend detection in forest area as MRA-WT, however, it was more constrained to a longer computational time of execution. BFAST and EEMD exhibited a better performance in bare soil and cropland areas, and the latter can be taken as an appropriate and fast alternative for a general long-term trend overview with long TS.     

Soil moisture dynamics and restoration of self‐sustaining native vegetation ecosystem on an open‐cut coal mine

Post‐mining landscape reconstruction on open‐cut coal mines aims to support restoration of self‐sustaining native vegetation ecosystems that in perpetuity require no extra inputs relative to unmined analogs. Little is known about the soil moisture retention capacity of the limited layer of topsoil replaced (often <30 cm deep), impacts of deep ripping of the profile, and the combined impacts of these on plant available water during the mine restoration process. We examined changes in soil moisture parameters (soil water potential, Ψ, and soil water content, Θ) daily using automated soil sensors installed at 30 and 45–65 cm depths on mine restoration sites aged between 3 and 22 years and on adjacent remnant vegetation sites following heavy rainfall events at Meandu mine, southeast Queensland, Australia. Consistent patterns in soil moisture attributes were observed among rehabilitated sites with generally marked differences from remnant sites. Remnant site soil profiles had generally higher Θ after drying than rehabilitated sites and maintained high Ψ for extended periods after rain events. There was a relatively rapid decline of Ψ on reconstructed soil profiles compared with remnant sites although the times of decline onset varied. This response indicated that vegetation restoration sites released soil moisture more rapidly than remnant sites but the rate of drying decreased with increasing rehabilitation age and increased with increasing tree stem density. The rapid drying of mine rehabilitated sites may threaten the survival of some remnant forest species, limit tree growth, and delay restoration of self‐sustaining native ecosystem.     

Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables

Switchgrass is being evaluated as a potential feedstock source for cellulosic biofuels and is being cultivated in several regions of the United States. The recent availability of switchgrass land cover maps derived from the National Agricultural Statistics Service cropland data layer for the conterminous United States provides an opportunity to assess the environmental conditions of switchgrass over large areas and across different geographic locations. The main goal of this study is to develop a data-driven multiple regression switchgrass productivity model and identify the optimal climate and environment conditions for the highly productive switchgrass in the Great Plains (GP). Environmental and climate variables used in the study include elevation, soil organic carbon, available water capacity, climate, and seasonal weather. Satellite-derived growing season averaged Normalized Difference Vegetation Index (GSN) was used as a proxy for switchgrass productivity. Multiple regression analyses indicate that there are strong correlations between site environmental variables and switchgrass productivity (r = 0.95). Sufficient precipitation and suitable temperature during the growing season (i.e., not too hot or too cold) are favorable for switchgrass growth. Elevation and soil characteristics (e.g., soil available water capacity) are also an important factor impacting switchgrass productivity. An anticipated switchgrass biomass productivity map for the entire GP based on site environmental and climate conditions and switchgrass productivity model was generated. Highly productive switchgrass areas are mainly located in the eastern part of the GP. Results from this study can help land managers and biofuel plant investors better understand the general environmental and climate conditions influencing switchgrass growth and make optimal land use decisions regarding switchgrass development in the GP.     

盐池县2000-2012年植被变化及其驱动力

荒漠草原区的植被对防治荒漠化、维护生态屏障具有决定性作用,宁夏盐池县作为其典型代表,近13年的植被变化深受气候变化和人类活动的综合影响。基于MODIS NDVI等数据,运用趋势分析、经验模态分解和空间叠置分析等方法,对盐池县2000—2012年的植被动态变化进行研究,结果表明:(1)2000—2012年盐池县NDVI在0.2—0.4之间呈波动上升趋势,上升幅度为0.078/10 a,上升趋势显著;总体来说,植被稳定性低,年际间波动或转换频繁、幅度大;(2)NDVI的波动分量与残余分量方差贡献率各占50%,且NDVI波动呈减弱趋势。促使NDVI波动的主控因子是年降水量,但其影响在减弱;(3)推动NDVI趋势性上升的主要因素是土地利用方式改善和类型变化,但土地利用方式改善对NDVI的贡献远远大于土地利用类型变化对NDVI的贡献。因此,荒漠草原区的生态改善应以保护为主,辅之以必要的生态重建,走以适度开发带动整体保护的道路。     

Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China

The objectives of this study are to explore the relationships between plant phenology and satellite-sensor-derived measures of greenness, and to advance a new procedure for determining the growing season of land vegetation at the regional scale. Three phenological stations were selected as sample sites to represent different climatic zones and vegetation types in northern China. The mixed data set consists of occurrence dates of all observed phenophases for 50–70 kinds of trees and shrubs from 1983 to 1988. Using these data, we calculated the cumulative frequency of phenophases in every 5-day period (pentad) throughout each year, and also drew the cumulative frequency distribution curve for all station-years, in order to reveal the typical seasonal characteristics of these plant communities. The growing season was set as the time interval between 5% and 95% of the phenological cumulative frequency. Average lengths of the growing season varied between 188 days in the northern, to 259 days in the southern part of the research region. The beginning and end dates of the surface growing season were then applied each year as time thresholds, to determine the corresponding 10-day peak greenness values from normalized difference vegetation index curves for 8-km² pixels overlying the phenological stations. Our results show that, at the beginning of the growing season, the largest average greenness value occurs in the southern part, then in the northern, and finally the middle part of the research region. In contrast, at the end of the growing season, the largest average greenness value is measured in the northern part, next in the middle and lastly the southern part of the research region. In future studies, these derived NDVI thresholds can be applied to determine the growing season of similar plant communities at other sites, which lack surface phenological data. Received: 29 November 1999 / Revised: 14 March 2000 / Accepted: 15 March 2000     

生态工程背景下西南喀斯特植被变化主导因素及其空间非平稳性

我国西南喀斯特地区石漠化面积已实现净减少,植被状况具有明显改善。为了更清晰的了解该区植被变化情况及其影响因素的区域差异,采用长时间序列遥感数据,综合运用空间自相关分析、主成分分析(PCA)和地理加权回归(GWR)等研究方法,分析生态工程实施以来滇桂黔喀斯特植被变化及其主要影响因素的空间非平稳性。结果表明:与1982—2000年相比,2001—2011年生长季归一化植被指数(GSN)在整个研究区域都有增加且具有显著的空间集聚性(Ig为0.90),但增加程度在空间上具有差异性(变异系数为43%);影响滇桂黔植被变化的主要因素包括气候因子、土壤质地、人类活动、水分有效性、土壤养分和社会经济条件,且对植被变化的影响程度随地理位置的变化而变化。不同工程地貌类型区内,影响植被变化的主导因素不同,且存在显著的空间差异性,需综合考虑植被变化主导因素的区域差异来调整或改进后续生态工程措施。     

基于MODIS-EVI的西南地区植被覆盖时空变化及驱动因素研究

基于MODIS-EVI和气象数据,利用最大值合成法、像元二分模型、趋势分析和相关分析等方法,探讨了西南地区2001-2015年植被覆盖时空变化特征及其对气候因子的响应,并分析了温度和降水对植被覆盖时空变化的驱动作用。结果表明：（1）2001-2015年,西南地区植被EVI以0.1%/a的变化率呈波动增加趋势,但空间异质性显著,呈现出从东南向西北逐渐递减的趋势;（2）西南地区以高和极高植被覆盖度为主,极低植被覆盖度区域约占研究区总面积的8.6%,植被覆盖度增加的区域集中分布在广西省北海-钦州、贵州省邵通-毕节-遵义、四川省广元-广安以及西藏那曲等地区,植被覆盖度呈减少趋势区域主要集中在西藏拉萨-阿里地区和四川成都-阿坝州-甘孜州等地区;（3）植被EVI与同期温度和降水相关性较好,均以正相关为主。在0.05显著水平下,受降水驱动的区域呈斑块状分布在西藏自治区和青海省交界处,以及云南和广西部分地区,约占研究区总面积的3.4%;受温度驱动的区域零星分布在各省、自治区,约占研究区总面积的1.6%;受温度和降水共同驱动的区域约占研究区总面积的7.2%,主要分布在西藏自治区的阿里地区北部,青海省的三江源地区以及四川和贵州两省交界处的小部分地区;西南地区大部分区域的植被EVI指数变化表现为非气候因素驱动。     

Long-term responses of boreal vegetation to global change: an experimental and modelling investigation

The response of boreal ecosystems to future global change is an uncertain but potentially critical component of the feedback between the terrestrial biosphere and the atmosphere. To reduce some of the uncertainties in predicting the responses of this key ecosystem, the climate change experiment (CLIMEX) exposed an entire undisturbed catchment of boreal vegetation to CO₂ enrichment (560 ppmv) and climate change (+ 5 °C in winter, + 3 °C in summer) for three years (1994–96). This paper describes the leaf metabolic responses of the vegetation to the experimental treatment and model simulations of possible future changes in the hydrological and carbon balance of the site. Randomized intervention analysis of the leaf gas exchange measurements for the dominant species indicated Pinus sylvestris had significantly (P < 0.01) higher photosynthetic rates and Betula pubescens and Vaccinium myrtillus had significantly (P < 0.01) lower stomatal conductances after three years treatment compared to the controls. These responses led to sustained increases in leaf water-use efficiency of all species of trees and ground shrubs, as determined from carbon isotope analyses. Photosynthesis (A) vs. intercellular CO₂ (c_i) response curves (A/c_i responses), RuBisCo analysis and leaf nitrogen data together suggested none of the species investigated exhibited down-regulation in photosynthetic capacity. At the whole ecosystem level, the improved water economy of the plants did not translate into increased catchment runoff. Modelling simulations for the site indicate this was most likely brought about by a compensatory increase in evapotranspiration. In terms of the carbon budget of the site, the ecosystem model indicates that increased CO₂ and temperature would lead to boreal ecosystems of the type used in CLIMEX, and typical of much of southern Norway, acting as moderate net sinks for CO₂.     

Long-term dynamics of water and carbon in semi-arid ecosystems: a gradient analysis in the Patagonian steppe

We used a soil water simulation model and remotely sensed data to study the long-term dynamics of transpiration, evaporation, drainage and net primary production across a precipitation gradient in Northwestern Patagonia (Argentina). The proportion of precipitation transpired, the precipitation use efficiency and the transpiration use efficiency were constant across the gradient that covered a range of 150 to 600 mm. The proportion of water evaporated was higher than the proportion drained at the driest extreme of the gradient. The opposite relationship was observed at the wet extreme.Two important characteristics of arid-semiarid systems dominated by winter precipitation emerged from our analyses: the importance of drainage losses and the asynchrony between evaporation and transpiration fluxes. These characteristics of the water dynamics influence the relative abundance of plant functional types and are crucial to generate heterogeneity at the landscape level. The coefficient of variation (CV) of transpiration, evaporation and ANPP was, in general, lower than the CV of annual precipitation. This pattern suggests a buffering capacity of the ecosystem. The ecosystem would be able to damp at the functional level inter-annual changes in the availability of resources.