Debating the greening vs. browning of the North American boreal forest: differences between satellite datasets

A number of remote sensing studies have evaluated the temporal trends of the normalized difference vegetation index (NDVI or vegetation greenness) in the North American boreal forest during the last two decades, often getting quite different results. To examine the effect that the use of different datasets might be having on the estimated trends, we compared the temporal trends of recently burned and unburned sites of boreal forest in central Canada calculated from two datasets: the Global Inventory, Monitoring, and Modeling Studies (GIMMS), which is the most commonly used 8 km dataset, and a new 1 km dataset developed by the Canadian Centre for Remote Sensing (CCRS). We compared the NDVI trends of both datasets along a fire severity gradient in order to evaluate the variance in regeneration rates. Temporal trends were calculated using the seasonal Mann–Kendall trend test, a rank‐based, nonparametric test, which is robust against seasonality, nonnormality, heteroscedasticity, missing values, and serial dependence. The results showed contrasting NDVI trends between the CCRS and the GIMMS datasets. The CCRS dataset showed NDVI increases in all recently burned sites and in 50% of the unburned sites. Surprisingly, the GIMMS dataset did not capture the NDVI recovery in most burned sites and even showed NDVI declines in some burned sites one decade after fire. Between 50% and 75% of GIMMS pixels showed NDVI decreases in the unburned forest compared with <1% of CCRS pixels. Being the most broadly used dataset for monitoring ecosystem and carbon balance changes, the bias towards negative trends in the GIMMS dataset in the North American boreal forest has broad implications for the evaluation of vegetation and carbon dynamics in this region and globally.     

基于生态地理分区的大兴安岭植被物候时空变化

植被与气候的关系十分密切,植被物候可作为全球气候变化的指示器.大兴安岭位于我国最北部,对气候变化较为敏感,研究该区植被物候的时空变化对评估全球变化对陆地生态系统的影响具有重要意义.依据中国生态地理区划图,将大兴安岭划分为4个生态研究区域,本文利用GIMMS NDVI 3g遥感数据集分析1982—2012年大兴安岭整体及各生态地理分区植被物候变化.结果表明: 研究期间,所有分区植被生长季开始日期均表现为提前趋势,生长季结束日期均表现为推迟趋势.植被物候对气候因子变化敏感,尤其是对气温的敏感程度高于降水,其中,北段山地落叶针叶林区植被生长季开始日期与春季温度呈显著负相关;除南段草原区外,其他3个分区植被生长季结束日期均与秋季降水呈显著负相关.从整体来看,植被物候随海拔、纬度的变化趋势明显.     

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.     

基于叶面积指数估算植被总初级生产力

长时间序列的陆地碳通量数据在全球生态环境变化研究中具有重要意义。采用MODIS GPP(Gross Primary Productivity)算法,基于GIMMS LAI3g,MODIS15和Improved-MODIS15三种叶面积指数(LAI),估算了全球2000至2010年的植被总初级生产力(GPP)。该估算的GPP数值经过全球20个通量站点的验证,并结合MODIS17分析了它们在时空变化上的异同。结果表明:(1)4种GPP精度如下:GPP_(MOD17)GPP_(impro_MOD15)GPP_(LAI3g)GPP_(MOD15)。(2)4种GPP整体上具有一致的季节波动,冬季和夏季整体好于春季和秋季。GPP_(LAI3g)的4个季节精度较相近,而GPP_(MOD17)除了春秋季外其它季节都较好。(3)GPP_(LAI3g)在中等GPP值分布区的估值相对较高,其全球总GPP大体为(117±1.5)Pg C/a,GPP_(MOD17)和GPP_(impro_MOD15)相近且都低于该值。(4)GPP_(LAI3g)和GPP_(impro_MOD15)在大约63.29%的陆面上呈显著(P0.05)的正相关关系,它们和GPP_(MOD17)在LAI不确定性小的地区呈显著的正相关关系。GPP_(LAI3g)和GPP_(MOD15)正相关分布面积占比为40.61%。     

Multiple afforestation programs accelerate the greenness in the ‘Three North’ region of China from 1982 to 2013

China has launched multiple afforestation programs since 1978, including the ‘Three North’ Shelterbelt Development Program (TNSDP), the Beijing–Tianjin Sand Source Control Program (BSSCP), the Nature Forest Conservation Program (NFCP), and the Grain to Green Program (GTGP). These programs focus on local environment restoration by planting trees in semi-arid and arid regions and by protecting natural forests. However, the effectiveness of these programs has been questioned by several previous studies. Here, we report an increasing trend of greenness in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from GIMMS, GIMMS-3g and MODIS datasets in the past 32 years. The NDVI increase for the ‘Three North’ region was 0.28%–0.38% yr⁻¹ in 1982–2000 and 0.86%–1.12% yr⁻¹ in 2000–2013, which is much higher than the country's means of 0.060%–0.063% yr⁻¹ and 0.27%–0.30% yr⁻¹, respectively. Most of the increase occurred in low and sparsely vegetated areas; and enlarged the moderate vegetated area (growing season mean NDVI above 0.5) from 16.5% to 25.7% for the two time periods, respectively. We also analyzed changes in the length of the growing season and the climate conditions including temperature, precipitation and two drought indices. However, these environmental factors cannot completely explain the changes in vegetation activity. Our study suggests these multiple afforestation programs contributed to the accelerated greening trend in the ‘Three North’ region and highlight the importance of human intervention in regional vegetation growth under climate change condition.     

两代AVHRR GIMMS NDVI数据集的对比分析——以新疆地区为例

最新发布的1981—2012年的AVHRR GIMMS NDVI3g数据为了解区域植被的近期变化状况提供了数据基础。深入理解该版本与老版本GIMMS NDVIg(1981—2006年)之间的关系,对于使用新数据时充分利用已有老版本的研究结果具有重要意义。以我国西北干旱区的典型区域——新疆为例,研究了两个数据集在反映生长季、春季、夏季和秋季植被现状,植被变化趋势及其对气候变化响应方面的异同。研究结果表明:两个数据集在描述植被活动空间分布、变化趋势及其与气候的相关性方面大体相似,但在数值、动态变化率及其对气候变化响应强度等方面存在的差异也不容忽略。NDVI3g数据生长季和各季节NDVI数值多大于NDVIg,尤其是在夏季和在植被覆盖较好的区域。区域尺度,NDVI3g所反映的植被变化趋势更为平稳,尤其是在夏季和较长的时段,这可能与像元尺度NDVI3g显著增加范围小于NDVIg,而显著减少范围多于NDVIg有关。两个数据集对气温、降水量、潜在蒸散发和湿润指数的响应具有大体一致的空间格局,但对气候因子变化的敏感性存在差异,哪一个数据集更为灵敏依赖于不同的气候因子和时段。一般规律是NDVI3g与热量因子显著正相关的区域小于NDVIg,而与水分因子显著正相关的区域则大于NDVIg。利用长期的生态数据集,尽快理清两个数据集在表征植被变化之间的异同并建立两者的转换关系,对于合理开展植被变化、碳平衡、生态系统服务功能评估等广泛利用NDVI数据的相关研究十分重要。     

Strong contribution of autumn phenology to changes in satellite‐derived growing season length estimates across Europe (1982–2011)

Land Surface Phenology (LSP) is the most direct representation of intra‐annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land‐surface fluxes, and is central to accurately parameterizing terrestrial biosphere–atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan‐European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape‐based aggregation scheme. We used indicators of Start‐Of‐Season, End‐Of‐Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982–2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18–24 days decade^?1 over 18–30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing‐season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI‐derived end‐of‐season contributed more to the GSL trend than changes in spring green‐up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.     

Role of African protected areas in maintaining connectivity for large mammals

The African protected area (PA) network has the potential to act as a set of functionally interconnected patches that conserve meta-populations of mammal species, but individual PAs are vulnerable to habitat change which may disrupt connectivity and increase extinction risk. Individual PAs have different roles in maintaining connectivity, depending on their size and location. We measured their contribution to network connectivity (irreplaceability) for carnivores and ungulates and combined it with a measure of vulnerability based on a 30-year trend in remotely sensed vegetation cover (Normalized Difference Vegetation Index). Highly irreplaceable PAs occurred mainly in southern and eastern Africa. Vegetation cover change was generally faster outside than inside PAs and particularly so in southern Africa. The extent of change increased with the distance from PAs. About 5% of highly irreplaceable PAs experienced a faster vegetation cover loss than their surroundings, thus requiring particular conservation attention. Our analysis identified PAs at risk whose isolation would disrupt the connectivity of the PA network for large mammals. This is an example of how ecological spatial modelling can be combined with large-scale remote sensing data to investigate how land cover change may affect ecological processes and species conservation.     

基于MODIS NDVI、SPOT NDVI数据的GIMMS NDVI性能评价

以MODIS NDVI和SPOT NDVI数据为基准对2000—2015年重叠时段的GIMMS NDVI数据进行评价.在全国尺度以及水田、旱地、林地、草地4种土地类型上对比分析3种数据的数值差异、动态一致性、变化趋势差异和两两间相关性.结果表明: GIMMS NDVI在数值上整体高于MODIS NDVI和SPOT NDVI,3种数据在反映植被月动态方面能力相当;研究期内3种NDVI数据在全国大部分区域均呈增加趋势,GIMMS的增加幅度最小,且在我国西北、东北、中南、青藏高原及云贵高原的部分地区与另两套数据差异较大,表明在研究该区域时应对GIMMS NDVI数据的使用有所保留;各数据间两两相关性较强,在全国尺度上MODIS NDVI与SPOT NDVI的相关性更好,旱地GIMMS NDVI与MODIS NDVI的相关性更好,水田、林地、草地MODIS NDVI与SPOT NDVI的相关性更好.     

内蒙古草原区植被净初级生产力及其与气候的关系

利用NOAA/AVHRR GIMMSNDVI数据、土地覆盖分类数据、气象数据等,基于改进的基于光能利用率的净初级生产力(Net Primary productivity,NPP)遥感估算模型对内蒙古草原区1982-2006年的NPP进行估算,并分别以年、季节和月为时间单位,计算基于像元的NPP与降水、温度之间的相关及偏相关系数,分析不同时间单位及尺度上NPP与气候的关系。结果表明,1982-2006年内蒙古草原区NPP总量呈波动增加的趋势,平均增加值为0.861Mt C/a。以年为时间单位,内蒙古草原区年NPP与降水的关系比较明显。以季节为时间单位,年际春季和夏季NPP与降水的关系比较明显,秋季二者关系相对较弱,春季和秋季NPP与温度的相关系数和偏相关系数空间格局比较一致,且相关性明显高于夏季。以月为时间单位的相关水平明显高于年际水平,多年平均年内月NPP与降水、温度的相关程度明显增强,除去降水的影响,月均温对NPP的影响明显下降,且空间格局也有明显的变化,说明以月为时间单位在年内尺度上降水对植被生长的影响比温度要大。而以4、7、10月份为例,在年际尺度上,虽然各月份NPP均受降水的影响较大,但与降水关系最为密切的是4月份和10月份NPP,与之相比,7月份NPP与温度的关系明显高于其他两月。