Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO₂ concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO₂ concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO₂ concentration and air temperature performed well (R²~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the ‘CO₂ fertilization effect’ on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes.     

Spatial variation in regional CO2 exchange for the Kuparuk River Basin, Alaska over the summer growing season

The spatial and temporal patterns in CO₂ flux for the Kuparuk River Basin, a 9200‐km² watershed located in NE Alaska were estimated using the Regional Arctic CO₂ Exchange Simulator (RACES) for the 1994–1995 growing seasons. RACES uses non‐linear models and a Geographical Information System database (GIS) consisting of the normalized difference vegetation index (NDVI) and dynamic temperature and radiation maps. The spatial and temporal patterns in the NDVI during both growing seasons suggest that ecosystem development occurred 2–4 weeks earlier and was relatively more rapid in the southern portion of the Kuparuk River Basin. Rates of gross primary production (GPP) and whole‐ecosystem respiration (R) were 2–4 fold higher in the southern basin than along the arctic coastal plain depending on time of year. The higher rate of GPP estimated for the southern basin was primarily due to higher NDVI values, while the higher R estimated for the southern basin was due in part to higher temperature and the NDVI. While GPP and R showed strong latitudinal trends, spatial and temporal trends in net ecosystem CO₂ exchange (NEE) were much more variable. Thus, while spatial trends in carbon gain (GPP) and loss (R) were highly correlated, small spatial and temporal differences in these large fluxes (GPP and/or R) lead to corresponding large spatial variations in the NEE.     

Comparison of the mass and energy exchange of a pasture and a mature transitional tropical forest of the southern Amazon Basin during a seasonal transition

This research utilized tower‐based eddy covariance to quantify the trends in net ecosystem mass (CO₂ and H₂O vapor) and energy exchange of important land‐cover types of NW Mato Grosso during the March–December 2002 seasonal transition. Measurements were made in a mature transitional (ecotonal) tropical forest near Sinop, Mato Grosso, and a cattle pasture near Cotriguaçú, Mato Grosso, located 500 km WNW of Sinop. Pasture net ecosystem CO₂ exchange (NEE) was considerably more variable than the forest NEE over the seasonal transition, and the pasture had significantly higher rates of maximum gross primary production in every season except the dry–wet season transition (September–October). The pasture also had significantly higher rates of whole‐ecosystem dark respiration than the forest during the wetter times of the year. Average (±95% CI) rates of total daily NEE during the March–December 2002 measurement period were 26±15 mmol m^?2 day^?1 for the forest (positive values indicate net CO₂ loss by the ecosystem) and ?38±26 mmol m^?2 day^?1 for the pasture. While both ecosystems partitioned more net radiation (R_n) into latent heat flux (L_e), the forest had significantly higher rates of L_e and lower rates of sensible heat flux (H) than the pasture; a trend that became more extreme during the onset of the dry season. Large differences in pasture and forest mass and energy exchange occurred even though seasonal variations in micrometeorology (air temperature, humidity, and radiation) were relatively similar for both ecosystems. While the short measurement period and lack of spatial replication limit the ability to generalize these results to pasture and forest regions of the Amazon Basin, these results suggest important differences in the magnitude and seasonal variation of NEE and energy partitioning for pasture and transitional tropical forest.     

Net biome production of the Amazon Basin in the 21st century

Global change includes multiple stressors to natural ecosystems ranging from direct climate and land‐use impacts to indirect degradation processes resulting from fire. Humid tropical forests are vulnerable to projected climate change and possible synergistic interactions with deforestation and fire, which may initiate a positive feedback to rising atmospheric CO₂. Here, we present results from a multifactorial impact analysis that combined an ensemble of climate change models with feedbacks from deforestation and accidental fires to quantify changes in Amazon Basin carbon cycling. Using the LPJmL Dynamic Global Vegetation Model, we modelled spatio‐temporal changes in net biome production (NBP); the difference between carbon fluxes from fire, deforestation, soil respiration and net primary production. By 2050, deforestation and fire (with no CO₂ increase or climate change) resulted in carbon losses of 7.4–20.3 Pg C with the range of uncertainty depending on socio‐economic storyline. During the same time period, interactions between climate and land use either compensated for carbon losses due to wetter climate and CO₂ fertilization or exacerbated carbon losses from drought‐induced forest mortality (?20.1 to +4.3 Pg C). By the end of the 21st century, depending on climate projection and the rate of deforestation (including its interaction with fire), carbon stocks either increased (+12.6 Pg C) or decreased (?40.6 Pg C). The synergistic effect of deforestation and fire with climate change contributed up to 26–36 Pg C of the overall decrease in carbon stocks. Agreement between climate projections (n=9), not accounting for deforestation and fire, in 2050 and 2098 was relatively low for the directional change in basin‐wide NBP (19–37%) and aboveground live biomass (13–24%). The largest uncertainty resulted from climate projections, followed by implementation of ecosystem dynamics and deforestation. Our analysis partitions the drivers of tropical ecosystem change and is relevant for guiding mitigation and adaptation policy related to global change.     

Change in winter snow depth and its impacts on vegetation in China

Snow on land is an important component of the global climate system, but our knowledge about the effects of its changes on vegetation are limited, particularly in temperate regions. In this study, we use daily snow depth data from 279 meteorological stations across China to investigate the distribution of winter snow depth (December–February) from 1980 to 2005 and its impact on vegetation growth, here approximated by satellite‐derived vegetation greenness index observations [Normalized Difference Vegetation Index (NDVI)]. The snow depth trends show strong geographical heterogeneities. An increasing trend (>0.01 cm yr^?1) in maximum and mean winter snow depth is found north of 40°N (e.g. Northeast China, Inner Mongolia, and Northwest China). A declining trend (?1) is observed south of 40°N, particularly over Central and East China. The effect of changes in snow depth on vegetation growth was examined for several ecosystem types. In deserts, mean winter snow depth is significantly and positively correlated with NDVI during both early (May and June) and mid‐growing seasons (July and August), suggesting that winter snow plays a critical role in regulating desert vegetation growth, most likely through persistent effects on soil moisture. In grasslands, there is also a significant positive correlation between winter snow depth and NDVI in the period May–June. However, in forests, shrublands, and alpine meadow and tundra, no such correlation is found. These ecosystem‐specific responses of vegetation growth to winter snow depth may be due to differences in growing environmental conditions such as temperature and rainfall.     

Impacts of climate change on natural forest productivity – evidence since the middle of the 20th century

Changes to forest production drivers (light, water, temperature, and site nutrient) over the last 55 years have been documented in peer‐reviewed literature. The main objective of this paper is to review documented evidence of the impacts of climate change trends on forest productivity since the middle of the 20th century. We first present a concise overview of the climate controls of forest production, provide evidence of how the main controls have changed in the last 55 years, followed by a core section outlining our findings of observed and documented impacts on forest productivity and a brief discussion of the complications of interpreting trends in net primary production (NPP). At finer spatial scales, a trend is difficult to decipher, but globally, based on both satellite and ground‐based data, climatic changes seemed to have a generally positive impact on forest productivity when water was not limiting. Of the 49 papers reporting forest production levels we reviewed, 37 showed a positive growth trend, five a negative trend, three reported both a positive and a negative trend for different time periods, one reported a positive and no trend for different geographic areas, and two reported no trend. Forests occupy ≈52% of the Earth's land surface and tend to occupy more temperature and radiation‐limited environments. Less than 7% of forests are in strongly water‐limited systems. The combined and interacting effects of temperature, radiation, and precipitation changes with the positive effect of CO₂, the negative effects of O₃ and other pollutants, and the presently positive effects of N will not be elucidated with experimental manipulation of one or a few factors at a time. Assessments of the greening of the biosphere depend on both accurate measurements of rates (net ecosystem exchange, NPP), how much is stored at the ecosystem level (net ecosystem production) and quantification of disturbances rates on final net biome production.     

Observed change of the standardized precipitation index, its potential cause and implications to future climate change in the Amazon region

Observations show that the standard precipitation index (SPI) over the southern Amazon region decreased in the period of 1970-1999 by 0.32 per decade, indicating an increase in dry conditions. Simulations of constant pre-industrial climate with recent climate models indicate a low probability (p=0%) that the trends are due to internal climate variability. When the 23 models are forced with either anthropogenic factors or both anthropogenic and external natural factors, approximately 13% of sampled 30-year SPI trends from the models are found to be within the range of the observed SPI trend at 95% confidence level. This suggests a possibility of anthropogenic and external forcing of climate change in the southern Amazon. On average, the models project no changes in the frequency of occurrence of low SPI values in the future; however, those models which produce more realistic SPI climatology, variability and trend over the period 1970-1999 show more of a tendency towards more negative values of SPI in the future. The analysis presented here suggests a potential anthropogenic influence on Amazon drying, which warrants future, more in-depth, study.     

An objective tropical Atlantic sea surface temperature gradient index for studies of south Amazon dry-season climate variability and change

Future changes in meridional sea surface temperature (SST) gradients in the tropical Atlantic could influence Amazon dry-season precipitation by shifting the patterns of moisture convergence and vertical motion. Unlike for the El Niño-Southern Oscillation, there are no standard indices for quantifying this gradient. Here we describe a method for identifying the SST gradient that is most closely associated with June–August precipitation over the south Amazon. We use an ensemble of atmospheric general circulation model (AGCM) integrations forced by observed SST from 1949 to 2005. A large number of tropical Atlantic SST gradient indices are generated randomly and temporal correlations are examined between these indices and June–August precipitation averaged over the Amazon Basin south of the equator. The indices correlating most strongly with June–August southern Amazon precipitation form a cluster of near-meridional orientation centred near the equator. The location of the southern component of the gradient is particularly well defined in a region off the Brazilian tropical coast, consistent with known physical mechanisms. The chosen index appears to capture much of the Atlantic SST influence on simulated southern Amazon dry-season precipitation, and is significantly correlated with observed southern Amazon precipitation.We examine the index in 36 different coupled atmosphere–ocean model projections of climate change under a simple compound 1% increase in CO₂. Within the large spread of responses, we find a relationship between the projected trend in the index and the Amazon dry-season precipitation trends. Furthermore, the magnitude of the trend relationship is consistent with the inter-annual variability relationship found in the AGCM simulations. This suggests that the index would be of use in quantifying uncertainties in climate change in the region.     

Sensitivity of Global and Regional Terrestrial Carbon Storage to the Direct CO2 Effect and Climate Change Based on the CMIP5 Model Intercomparison

Global and regional land carbon storage has been significantly affected by increasing atmospheric CO₂ concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO₂ concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO₂ concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.     

The response of boreal peatland community composition and NDVI to hydrologic change,warming, and elevated carbon dioxide

Widespread changes in arctic and boreal Normalized Difference Vegetation Index (NDVI) values captured by satellite platforms indicate that northern ecosystems are experiencing rapid ecological change in response to climate warming. Increasing temperatures and altered hydrology are driving shifts in ecosystem biophysical properties that, observed by satellites, manifest as long‐term changes in regional NDVI. In an effort to examine the underlying ecological drivers of these changes, we used field‐scale remote sensing of NDVI to track peatland vegetation in experiments that manipulated hydrology, temperature, and carbon dioxide (CO₂) levels. In addition to NDVI, we measured percent cover by species and leaf area index (LAI). We monitored two peatland types broadly representative of the boreal region. One site was a rich fen located near Fairbanks, Alaska, at the Alaska Peatland Experiment (APEX), and the second site was a nutrient‐poor bog located in Northern Minnesota within the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. We found that NDVI decreased with long‐term reductions in soil moisture at the APEX site, coincident with a decrease in photosynthetic leaf area and the relative abundance of sedges. We observed increasing NDVI with elevated temperature at the SPRUCE site, associated with an increase in the relative abundance of shrubs and a decrease in forb cover. Warming treatments at the SPRUCE site also led to increases in the LAI of the shrub layer. We found no strong effects of elevated CO₂ on community composition. Our findings support recent studies suggesting that changes in NDVI observed from satellite platforms may be the result of changes in community composition and ecosystem structure in response to climate warming.     

百年尺度地球系统模式模拟的陆地生态系统碳通量对CO2浓度升高和气候变化的响应

利用了加拿大地球系统模式CanE SM2(Canadian Earth System Model of the CCCma)的结果,针对百年尺度大气CO_2浓度升高和气候变化如何影响陆地生态系统碳通量这一问题,分析了1850—1989年间陆地生态系统碳通量趋势对二者响应,以及与关键气候系统变量的关系。结果表明,140年间,当仅仅考虑CO_2浓度升高影响时,陆地生态系统净初级生产力(NPP)增加了117.1 gC m~(-2)a~(-1),土壤呼吸(Rh)增加了98.4 gC m~(-2)a~(-1),净生态系统生产力(NEP)平均增加了18.7 gC m~(-2)a~(-1)。相同情景下,全球陆地生态系统的NPP呈显著增加的线性趋势(约为0.30 PgC/a~2),Rh同样呈显著增加线性趋势(约为0.25 PgC/a~2)。仅仅考虑气候变化单独影响时,NPP平均减少了19.3 gC/m~2,土壤呼吸减少了8.5 gC/m~2,NEP减少了10.8 gC/m~2。在此情景下,整个陆地生态系统的NPP线性变化趋势约为-0.07 PgC/a~2(P0.05),Rh线性变化趋势约为-0.04 PgC/a~2(P0.05)。综合二者的影响,前者是决定陆地生态系统碳通量变化幅度和空间分布的最重要影响因子,其影响明显大于气候变化。值得注意的是,CanE SM2并没有考虑氮素的限制作用,所以CO_2浓度升高对植被的助长作用可能被高估。此外,气候变化的贡献也不容忽视,特别是在亚马逊流域,由于当温度升高、降水和土壤湿度减少,NPP和Rh均呈显著减少趋势。     

The greening and browning of Alaska based on 1982–2003 satellite data

Aim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km² pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.     

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982–2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17–36% of all productive areas depending on the NDVI metric used. For only 1–2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO₂ sequestration capacity.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

1982-2012年中亚地区植被时空变化特征及其与气候变化的相关分析

干旱区植被生态系统对气候变化极为敏感,并且干旱区的植被变化研究对全球碳循环具有重要意义。然而近几十年来,中亚干旱区植被对气候变化的响应机制尚不甚明朗。利用归一化植被指数NDVI数据集和MERRA（Modern-Era Retrospective Analysis for Research and Applications）气象数据,采用经验正交函数（EOF,Empirical Orthogonal Function）和最小二乘法等方法系统分析了31a（1982-2012年）来中亚地区NDVI在不同时间尺度的时空变化特征。进一步分析和研究NDVI与气温和降水的相关性,结果表明：1982-2012年,中亚地区年NDVI总体呈现缓慢增长趋势,而1994年以后年NDVI呈现明显下降趋势,尤其在哈萨克斯坦北部草原地区下降趋势尤为突出。这可能是由于过去30年间,中亚地区降水累计量的持续减少造成的。NDVI的季节变化表明春季NDVI增长最为明显,冬季则显著下降。与平原区相比,中亚山区的NDVI值增长幅度最大,并且山区年NDVI与季节NDVI呈现显著增加趋势（P < 0.05）。中亚地区年NDVI与年降水量正相关,而年NDVI与气温变化存在弱负相关。年NDVI和气温的正相关中心在中亚南部地区,负相关中心则出现在哈萨克斯坦的西部和北部地区;NDVI和降水的相关性中心刚好与气温相反。此外,在近30年间的每年6月至9月,中亚地区NDVI与气温存在近一个月的时间延迟现象。本研究为中亚干旱区生态系统变化和中亚地区碳循环的估算提供科学依据。     

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan‐tropical belt (30°N–30°S). We analyzed decadal‐scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982–2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid‐1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time‐dependent regression parameters to study the time evolution of NDVI–climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature‐induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global‐scale effects of climate warming and associated moisture stresses.     

Change in terrestrial ecosystem water‐use efficiency over the last three decades

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem‐scale water‐use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data‐driven models derived from satellite observations and process‐oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m^?2 mm^?1 yr^?1 under the single effect of rising CO₂ (‘CO₂’), climate change (‘CLIM’) and nitrogen deposition (‘NDEP’), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE‐CO₂ shows global increases, (ii) EWUE‐CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE‐NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data‐driven MTE model, however, shows a slight decline of EWUE during the same period (?0.0005 g C m^?2 mm^?1 yr^?1), which differs from process‐model (0.0064 g C m^?2 mm^?1 yr^?1) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO₂ reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data‐driven model and the process‐oriented models across different ecosystems. Change in water‐use efficiency defined from transpiration‐based WUE_t (GPP/TR) and inherent water‐use efficiency (IWUE_t, GPP×VPD/TR) in response to rising CO₂, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon–water interactions over terrestrial ecosystems under global change.     

Time lag and negative responses of forest greenness and tree growth to warming over circumboreal forests

The terrestrial forest ecosystems in the northern high latitude region have been experiencing significant warming rates over several decades. These forests are considered crucial to the climate system and global carbon cycle and are particularly vulnerable to climate change. To obtain an improved estimate of the response of vegetation activity, e.g., forest greenness and tree growth, to climate change, we investigated spatiotemporal variations in two independent data sets containing the dendroecological information for this region over the past 30 years. These indices are the normalized difference vegetation index (NDVI3g) and the tree‐ring width index (RWI), both of which showed significant spatial variability in past trends and responses to climate changes. These trends and responses to climate change differed significantly in the ecosystems of the circumarctic (latitude higher than 67°N) and the circumboreal forests (latitude higher and lower than 50°N and 67°N, respectively), but the way in which they differed was relatively similar in the NDVI3g and the RWI. In the circumarctic ecosystem, the climate variables of the current summer were the main climatic drivers for the positive response to the increase in temperatures showed by both the NDVI3g and the RWI indices. On the other hand, in the circumboreal forest ecosystem, the climate variables of the previous year (from summer to winter) were also important climatic drivers for both the NDVI3g and the RWI. Importantly, both indices showed that the temperatures in the previous year negatively affected the ecosystem. Although such negative responses to warming did not necessarily lead to a past negative linear trend in the NDVI3g and the RWI over the past 30 years, future climate warming could potentially cause severe reduction in forest greenness and tree growth in the circumboreal forest ecosystem.     

Detection and attribution of vegetation greening trend in China over the last 30 years

The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite‐derived Leaf Area Index (LAI) datasets for detection as well as five different process‐based ecosystem models for attribution. Rising atmospheric CO₂ concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing‐season LAI trend (LAI_GS) estimated by satellite datasets (average trend of 0.0070 yr^?1, ranging from 0.0035 yr^?1 to 0.0127 yr^?1), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAI_GS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai–Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAI_GS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAI_GS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO₂ concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.     

1982-2016年东北黑土区植被NDVI动态及其对气候变化的响应

植被是陆地生态系统的重要组成部分,在调节气候、水土保持等方面具有重要作用,因此,监测植被生长变化并探讨其与气候变化之间的关系,在全球变化研究中具有重要意义。基于MODIS NDVI和GIMMS NDVI数据集,并通过一致性检验,在区域和像元两个空间尺度上,利用一元线性回归模型,研究东北黑土区1982-2016年植被生长动态,分析植被生长对气温和降水量的响应程度。结果表明：区域尺度上,1982-2016年东北黑土区植被生长季NDVI变化分为3个阶段（先增加继而减少最后再增加）,区域植被的生长在气温、降水量的共同作用下,呈现出明显季节差异;像元尺度上,1982-2016年东北黑土区NDVI总体趋势为改善状态,主要改善植被类型为草原、森林和农业植被,鹤岗市、绥化市和长春市改善面积较大;多年平均NDVI值与同期气温和降水量具有一定的相关关系,平原地区植被NDVI与气温主要呈显著正相关关系,植被类型主要为耕地;平原地区边缘和山地地区的植被NDVI与降水量以显著正相关关系为主,主要植被类型为森林和草地。