Enrichment of land-cover polygons with eco-climatic information derived from MODIS NDVI imagery

Aim The FAO land‐cover classification system (LCCS) represents an innovative approach to standardizing and harmonizing land‐cover classifications based on remote sensing data. The thematic information considered by the LCCS, however, is intrinsically related to vegetation physiognomy and does not report important eco‐climatic features. Our aim is to develop a methodology to enrich LCCS maps with information on vegetation productivity and phenology derived from Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data. Location The LCCS has recently been applied in East Africa by the Africover project. The proposed methodology is developed and tested in Tanzania using MODIS NDVI data for a 5‐year period (2001–05). Methods Annual NDVI profiles of Africover polygons were extracted from MODIS imagery. These profiles, composed of 23 NDVI values per year, were averaged over the study period, purified for possible land‐cover errors and converted into a more manageable format composed of 24 half‐month values. The resulting NDVI profiles were first analysed visually and then evaluated statistically against rainfall measurements taken at 12 Tanzanian stations. The steps involved were as follows: NDVI values were aggregated on a monthly basis and represented with a one‐digit integer to obtain an extended code; a subset of parameters describing vegetation development and phenology was identified, thus obtaining a restricted codification; and finally, the information loss resulting from both the extended and restricted codification was evaluated with respect to the original NDVI profiles. Results NDVI profiles of different Africover classes can differ in mean values but tend to have a similar shape, linked to the seasonality of local vegetation. Both NDVI annual averages and seasonal variations are strictly dependent on rainfall patterns, particularly in arid zones. The tested codifications effectively summarize the eco‐climatic information contained in the polygon NDVI profiles, with the extended and restricted codifications retaining > 90% and 80% of such information, respectively. Main conclusions The proposed methodology is capable of enriching LCCS polygons with eco‐climatic information derived from MODIS NDVI data. Such information is related to vegetation development and seasonality, and can be efficiently condensed at various levels of detail.     

Macro‐scale bird species richness patterns of the East Asian mainland and islands: energy,area and isolation

Aim To create a map of bird species richness (BSR) in East Asia and to examine the effect of area, isolation, primary productivity, topographic heterogeneity, and human population density on BSR. Location East Asia (from 70° E to 180° E longitude), including the eastern half of the Palaearctic Region, the entire Oriental Region, and the entire Wallacea Subregion. Methods The breeding ranges of 2406 terrestrial bird species were mapped and overlaid to create a species richness map. The BSR map was transformed into a 100 × 100 km quadrat system, and BSR was analysed in relation to land area, average normalized difference vegetation index (NDVI), elevation range, and average population density. Results In general, BSR declined from the Tropics to the Arctic. In mainland East Asia, however, BSR was highest around the Tropic of Cancer, and fluctuated between 30° and 50° N. Islands had lower BSR than adjacent mainland areas. The NDVI was strongly positively correlated with BSR in mainland areas and on islands. For mainland areas, NDVI explained 65% of the BSR variation, and topographic heterogeneity explained an additional 6% in ordinary least‐squares regression. On islands, NDVI explained 66% of BSR variation, island area explained 13%, and distance to mainland accounted for 1%. Main conclusions In East Asia, we suggest that primary productivity is the key factor underpinning patterns of BSR. Primary productivity sets the upper limits of the capacity of habitats to support bird species. In isolated areas such as islands and peninsulas, however, BSR might not reach the richness limits set by primary productivity because the degree of isolation and area size also can affect species richness. Other factors, such as spatial heterogeneity, biotic interactions, and perturbations, may also affect species richness. However, their effects are secondary and are not as strong as primary productivity, isolation, and area size.     

NDVI is not reliable as a surrogate of forage abundance for a large herbivore in tropical forest habitat

Remotely sensed vegetation indices are increasingly being used in wildlife studies but field‐based support for their utility as a measure of forage availability comes largely from open‐canopy habitats. We assessed whether normalized difference vegetation index (NDVI) represents forage availability for Asian elephants in a southern Indian tropical forest. We found that the number of food species was a small percentage of all plant species. NDVI was not a good measure of food abundance in any vegetation category partly because of (a) small to moderate proportional abundances of food species relative to the total abundance of all species in that category (herbs and shrubs), (b) abundant overstory vegetation resulting in low correlations between NDVI and food abundance, despite a high proportional abundance of food species and a concordance between total abundance and food species abundance (graminoids), and (c) the relevant variables measured and important as food at the ground level (count and GBH) not being related to primary productivity (trees and recruits). NDVI had a negative relationship with the total abundance of graminoids, which represent a bulk of elephant and other herbivore diet, because of negative interaction with other vegetation and canopy cover that positively explained NDVI. Spatially interpolated total graminoid abundance modeled from field data outperformed NDVI in predicting total graminoid abundance, although interpolation models of food graminoid abundance were not satisfactory. Our results reject the utility of NDVI in mapping elephant forage abundance in tropical forests, a finding that has implications for studies of other herbivores also. Abstract in Kannada is available with online material.     

表征亚热带常绿林光合作用季节变化特征的多种植被指数

利用遥感方法可以在区域尺度反演地表植被的光合生理状况和生产力变化,但亚热带常绿林冠层结构季节变化较小,传统的光谱植被指数对植被光合作用难以准确捕捉。利用2014—2015年中国科学院广东省鼎湖山森林生态试验站多角度自动光谱观测系统的光谱反射数据,分别反演传统冠层结构型植被指数(NDVI)、光合生理生化型植被指数(CCI)和叶绿素荧光型植被指数(NDFI_(685)和NDFI_(760)),并利用不同类型植被指数的组合,构建多元线性回归模型。结果表明:亚热带常绿针阔混交林三种类型植被指数均与GPP的动态变化有显著的相关性,其中,NDVI是表征GPP较优的植被指数(R~2=0.60,P0.01),其次为CCI(R~2=0.55,P0.01),而NDFI能够作为辅助指数,有效提高NDVI(R~2=0.68,P0.001)和CCI(R~2=0.67,P0.001)表征GPP的程度。多个植被指数参与构建的多元回归模型能够有效提高亚热带地区常绿林GPP季节动态变化的拟合精度,提升遥感精确评估亚热带森林生产力的能力。     

Hierarchical global plant biophysical regions as potential analysis units

Regional and global vegetation simulations can be problematic when analysis units to which parameters are assigned do not align with plant productivity and phenology. Having a suite of predefined biophysical regions at a variety of scales that correspond to differences in plant productivity and phenology would allow analysts to select a set of analysis units at the scale needed. In other cases, environmental or social responses may be hypothesized to be related to differences in plant dynamics. One may compare the discrimination in such data that biophysical regions at different scales provide to determine which best distinguishes the responses in question, such that like responses fall within the same regions to the degree possible. If those relationships are significant, the responses may then be extrapolated based on the biophysical regions. I defined hierarchical biophysical regions based on plant productivity and phenology by clustering global 0.083 degree resolution normalized difference vegetation indices (NDVI) over a 10 year period. Agglomerative average‐linkage distances based on squared error between clusters were conducted using an iterative sampling approach to merge more than 2 million clusters into fewer and fewer clusters based on NDVI greenness profiles comprised of 240 values over 10 years, until all cells were in a single cluster. Greater and greater differences in greenness profiles were ignored at higher levels of the hierarchy. Using a difference increment of 0.1, 253 non‐duplicative sets of clusters were created, and 107 of those were included in animations that may be used to explore differences in global plant dynamics. Differences in clusters were quantified based on comparing the focal set of cluster results with 10 other cluster sets. Analysts may use the hierarchical clusters to improve the alignment of their parameter sets that inform plant growth and other dynamics with real‐world plant dynamics.     

Vegetation productivity patterns at high northern latitudes: a multi‐sensor satellite data assessment

Satellite‐derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long‐term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long‐term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR‐based GIMMS‐NDVI version G (GIMMS_g) series, and its recent successor version 3g (GIMMS_3g), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT‐VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS_3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMS_g), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMS_g, particularly in Eurasia where greening is especially pronounced in the GIMMS_3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem‐response to climate change using satellite‐derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.     

Landscape,soil and meteorological influences on canopy dynamics of northern flooding Pampa grasslands,Argentina

Question: How do meteorological variations at seasonal, interannual scales differentially affect the canopy dynamics of four contrasting landscape units within a region? Location: Flooding Pampa, Buenos Aires, Argentina. 5000 km². Central point: 35°15′S, 57°45′W. Methods: We used a 19‐year series of the normalized difference vegetation index (NDVI) derived from NOAA‐AVHRR PAL (Pathfinder AVHRR Land) images and meteorological data provided by a nearby weather station. The NDVI was used as surrogate of canopy photosynthetic status. The relationship between annually integrated NDVI and meteorological conditions was explored by stepwise multiple regressions for each defined unit. PC A was performed to compare units and growing seasons on a multivariate basis. Results: Mean seasonal NDVI curve was similarly shaped among landscapes. However, the absolute values differed widely. There was high interannual variation so that the mean seasonal pattern was seldom observed in any particular year. Annually integrated NDVI of all landscapes was negatively associated with summer temperature and positively with previous year precipitation. It was also directly related with current year winter precipitation in two landscapes and with summer precipitation in the others. NDVI response to September and March precipitation accounted for some of the differences in interannual variation among landscapes. Conclusions: Our results revealed a strong intra‐regional variation of canopy dynamics, closely linked to landscape (vegetation‐soil) and water availability (mainly in summer and during the previous year). These links may be used to predict forage production rates for livestock.     

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

Questions: What are the patterns of remotely sensed vegetation phenology, including their inter‐annual variability, across South Africa? What are the phenological attributes that contribute most to distinguishing the different biomes? How well can the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Location: South Africa. Method: Ten‐day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing season and estimates of productivity, based on small and large integral (SI, LI) of NDVI curve, were extracted and long‐term means calculated. A random forest regression tree was run using the metrics as the input variables and the biomes as the dependent variable. A map of the predicted biomes was reproduced and the differentiating importance of each metric assessed. Results: The phenology metrics (e.g. start of growing season) showed a clear relationship with the seasonality of rainfall, i.e. winter and summer growing seasons. The distribution of the productivity metrics, LI and SI were significantly correlated with mean annual precipitation. The regression tree initially split the biomes based on vegetation production and then by the seasonality of growth. A regression tree was used to produce a predicted biome map with a high level of accuracy (73%). Main conclusion: Regression tree analysis based on remotely sensed metrics performed as good as, or better than, previous climate‐based predictors of biome distribution. The results confirm that the remotely sensed metrics capture sufficient functional diversity to classify and map biome level vegetation patterns and function.     

Breeding bird species richness in Taiwan: distribution on gradients of elevation, primary productivity and urbanization

Aim To examine the richness of breeding bird species in relation to elevation, primary productivity and urbanization. Location The island of Taiwan (120°–122° E, 22°–25° N). Methods We arranged bird species richness (BSR) data from 288 bird censuses undertaken in Taiwan into a 2 × 2 km quadrat system and calculated average values of elevation, primary productivity [surrogated by normalized difference vegetation index (NDVI)], and urbanization (surrogated by road density and percentage of built area) for each 2 × 2 km quadrat. Results Bird species richness showed a hump‐shaped relationship with elevation. It increased with elevation from sea level (10–64 species per 2 × 2 km quadrat), peaked around 2000 m (43–76 species), and then decreased with elevation towards its minimum at the highest elevation. Road density and percentage of built area decreased with elevation, and NDVI showed a hump‐shaped relationship with elevation and inverse relationships with road density and percentage of built area. BSR increased with NDVI and decreased with road density and percentage of built area. Linear and cubic terms of elevation together explained 31.3% of the variance in BSR, and road density explained additional 3.4%. The explanatory power of NDVI on BSR was insignificant after the effects of elevation and road density had been justified. Main conclusions We argue that urbanization plays an important role in the BSR of Taiwan. Urbanization might indirectly decrease BSR through decreasing primary productivity and therefore change the hypothetical inverse relationship between BSR and elevation into a hump‐shaped relationship. We also propose a time hypothesis that the biotic communities in the mid‐elevation zone of Taiwan had relatively longer periods of existence during the Pleistocene glacial cycles, which might be one underlying process of the observed hump‐shaped relationship between species diversity and elevation.     

Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover

Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad‐scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape‐scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite‐measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time‐series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation–environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation‐ and community‐specific patterns of vegetation dynamics across the gradient. Main conclusions In addition to the environmental factors usually considered – climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance – woody plant cover, a broad‐scale proxy of many vegetation–environment interactions, represents an ecological dimension that provides additional process‐related understanding of landscape‐scale patterns of vegetation function.     

Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio‐temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time‐series of Normalized Difference Vegetation Index (NDVI). Drought spatio‐temporal variability was analyzed using a Principal Component Analysis, leading to the identification of four major drought events between 1999 and 2010 in Europe. Correspondence Analysis showed that at the continental scale the productivity and phenology reacted differently to the identified drought events depending on ecosystem and land cover. Northern and Mediterranean ecosystems proved to be more resilient to droughts in terms of vegetation phenology and productivity developments. Western Atlantic regions and Eastern Europe showed strong agglomerations of decreased productivity and shorter vegetation growing season length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.     

Spatial heterogeneity of tundra vegetation response to recent temperature changes

The spatial heterogeneity of recent decadal dynamics in vegetation greenness and biomass in response to changes in summer warmth index (SWI) was investigated along spatial gradients on the Arctic Slope of Alaska. Image spatial analysis was used to examine the spatial pattern of greenness dynamics from 1991 to 2000 as indicated by variations of the maximum normalized difference vegetation index (Peak NDVI) and time‐integrated NDVI (TI‐NDVI) along latitudinal gradients. Spatial gradients for both the means and temporal variances of the NDVI indices for 0.1° latitude intervals crossing three bioclimate subzones were analyzed along two north–south Arctic transects. NDVI indices were generally highly variable over the decade, with great heterogeneity across the transects. The greatest variance in TI‐NDVI was found in low shrub vegetation to the south (68.7–68.8°N) and corresponded to high fractional cover of shrub tundra and moist acidic tundra (MAT), while the greatest variance in Peak‐NDVI predominately occurred in areas dominated by wet tundra (WT) and moist nonacidic tundra (MNT). Relatively high NDVI temporal variances were also related to specific transitional areas between dominant vegetation types. The regional temporal variances of NDVI from 1991 to 2000 were largely driven by meso‐scale climate dynamics. The spatial heterogeneity of the NDVI variance was mostly explained by the fractional land cover composition, different responses of each vegetation type to climate change, and patterned ground features. Aboveground plant biomass exhibited similar spatial heterogeneity as TI‐NDVI; however, spatial patterns are slightly different from NDVI because of their nonlinear relationship.     

日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_(GPP))为第63天,生长季结束时间(EOS_(GPP))为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_(GPP)31天,植被指数EOS滞后EOS_(GPP)10—17天。虽然基于3种遥感指数估算的春季和秋季物候都滞后于通量GPP的物候期,但是卫星SIF的物候信息能够更好地捕捉常绿针叶林的生长阶段。同时,春季温度是影响森林生长季开始时间的最重要因素;秋季水分和辐射是影响生长季结束时间的关键因素。由此可见,SIF估算的亚热带常绿针叶林的春季和秋季物候的滞后时间要短于传统植被指数,能更好地追踪常绿林光合作用的季节性,为深入研究陆地生态系统碳循环及其对气候变化的响应提供重要的基础。     

Breeding phenology in relation to NDVI variability in free-ranging African elephant

The phenology of reproduction is often correlated with resource availability and is hypothesized to be shaped by selective forces in order to maximize lifetime reproductive success. African elephants have the distinctive life history traits of a 22 month gestation and extended offspring investment, necessitating a long-term strategy of energy acquisition and reproductive expenditure to ensure successful offspring recruitment.
We investigated the relationship between the reproductive phenology of a wild elephant population and resource availability using remotely sensed Normalized Differential Vegetation Index (NDVI) data as a measure of time-specific primary productivity and hence forage quality.
The initiation of female elephants' 3+yr reproductive bout was dependent on conditions during the season of conception but timed so parturition occurred during the most likely periods of high primary productivity 22 months later. Thus, the probability of conception is linked to the stochastic variation in seasonal quality and the phenology of parturition is related to the predictable seasonality of primary productivity, indicating elephants integrate information on known current and expected future conditions when reproducing.
Juvenile mortality was not correlated with ecological variability, hence female fecundity rather than calf mortality appears to drive demographic processes in the study population.
Extreme climatic events, such as those associated with the El Niño-Southern-Oscillation (ENSO), acted to synchronize female fecundity in the population. This study suggests that the relationship between fecundity and ecological variability instigates the characteristic demographic fluctuations in elephant populations, rather than the mortality-driven fluctuations observed in many ungulate populations.     

The role of landscape characteristics for forage maturation and nutritional benefits of migration in red deer

Large herbivores gain nutritional benefits from following the sequential flush of newly emergent, high‐quality forage along environmental gradients in the landscape, termed green wave surfing. Which landscape characteristics underlie the environmental gradient causing the green wave and to what extent landscape characteristics alone explain individual variation in nutritional benefits remain unresolved questions. Here, we combine GPS data from 346 red deer (Cervus elaphus) from four partially migratory populations in Norway with the satellite‐derived normalized difference vegetation index (NDVI), an index of plant phenology. We quantify whether migratory deer had access to higher quality forage than resident deer, how landscape characteristics within summer home ranges affected nutritional benefits, and whether differences in landscape characteristics could explain differences in nutritional gain between migratory and resident deer. We found that migratory red deer gained access to higher quality forage than resident deer but that this difference persisted even after controlling for landscape characteristics within the summer home ranges. There was a positive effect of elevation on access to high‐quality forage, but only for migratory deer. We discuss how the landscape an ungulate inhabits may determine its responses to plant phenology and also highlight how individual behavior may influence nutritional gain beyond the effect of landscape.     

Land surface phenology and temperature variation in the International Geosphere–Biosphere Program high-latitude transects

The International Geosphere–Biosphere Program has delineated five study areas that form a northern high‐latitude network for the analyses of vegetation and carbon dynamics. We examined the magnitude and significance of changes in the land surface phenologies of ecoregions within these transects using the NASA Pathfinder Advanced Very High‐Resolution Radiometer Land dataset. We applied the seasonal Mann–Kendall (SMK) trend test, a robust and nonparametric approach, to determine the significance of trends in the normalized difference vegetation index (NDVI) over the five transects. The SMK trend test provides an important alternative over the frequently used but unreliable trend analysis based on linear regression. In addition, we modeled the land surface phenology using quadratic or nonlinear spherical models to relate the NDVI data to accumulated growing degree‐days (base 0°C). Nonlinear spherical models parsimoniously describe the green‐up dynamics in taiga and tundra ecoregions. Models for each ecoregion within each transect were fitted separately for two time periods (1985–1988 and 1995–1999) and their parameter coefficient estimates were compared. In 10 of 24 ecoregions that comprise 72% of the land area in the transects, the date of the peak NDVI value was significantly earlier (range 2–18 days) in the second study period than in the first study period. This progression was more pronounced in North America than in Siberia (weighted average of 9.3 vs. 6.3 days earlier). Understanding of what constitutes significant change in land surface phenology amidst background variation is a critical component of global change science. A diversity of datasets, techniques, and study areas has led to a range of conclusions about boreal phenology. We discuss statistical pitfalls in standard analyses and offer a framework to conduct statistically reliable change assessments of land surface phenologies.     

Northern hemisphere photosynthetic trends 1982–99

We examined trends in the averaged May–September AVHRR normalized difference vegetation index (NDVI) from 1982 to 1999 for the northern hemisphere. NDVI is closely related to the amount of absorbed photosynthetically active radiation; hence, trends in NDVI reflect trends in photosynthetic activity of land‐surface vegetation. Linear and nonlinear trend analysis techniques were applied to four differently processed and corrected Advanced Very High Resolution Radiometer (AVHRR) NDVI data sets. The results were compared in order to evaluate the effects of trends in NDVI unrelated to vegetation activity. We consistently found significant positive trends in averaged NDVI for latitude bands above 35°N in all but one data set; this one data set lacked corrections for sensor drift and instrument calibration. An impressive improvement in data quality was achieved by applying calibration and corrections for atmospheric effects. Conservative estimates of the trends over the 1982–99 period range from 0.0015 to 0.0045 NDVI units year^?1 for global latitude bands from 35 to 75°N, with trends generally higher in the 1990s than in the 1980s; trends in NDVI were larger than trends explained by artefacts. In the 1980s, North American and Eurasian trends were roughly comparable, whereas in the 1990s the North American trends were generally higher. A pixel‐level analysis shows the trends to be widespread, with large areas of Canada, Europe and northern Asia experiencing significant positive increases across all vegetated landcovers.     

Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere

The inter-annual shift of spring vegetation phenology relative to per unit change of preseason temperature, referred to as temperature sensitivity (days °C⁻¹), quantifies the response of spring phenology to temperature change. Temperature sensitivity was found to differ greatly among vegetation from different environmental conditions. Understanding the large-scale spatial pattern of temperature sensitivity and its underlying determinant will greatly improve our ability to predict spring phenology. In this study, we investigated the temperature sensitivity for natural ecosystems over the North Hemisphere (north of 30°N), based on the vegetation phenological date estimated from NDVI time-series data provided by the Advanced Very High Resolution Radiometer (AVHRR) and the corresponding climate dataset. We found a notable longitudinal change pattern with considerable increases of temperature sensitivity from inlands to most coastal areas and a less obvious latitudinal pattern with larger sensitivity in low latitude area. This general spatial variation in temperature sensitivity is most strongly associated with the within-spring warming speed (WWS; r = 0.35, p < 0.01), a variable describing the increase speed of daily mean temperature during spring within a year, compared with other factors including the mean spring temperature, spring precipitation and mean winter temperature. These findings suggest that the same magnitude of warming will less affect spring vegetation phenology in regions with higher WWS, which might partially reflect plants’ adaption to local climate that prevents plants from frost risk caused by the advance of spring phenology. WWS accounts for the spatial variation in temperature sensitivity and should be taken into account in forecasting spring phenology and in assessing carbon cycle under the projected climate warming.     

Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

Aims 1. To characterize ecosystem functioning by focusing on above‐ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location Western portion of the Patagonian steppes in Argentina (39°30′ S to 45°27′ S). Methods We used remotely‐sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM‐derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely‐sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.     

Returning home after fire: how fire may help us manage the persistence of scrub-steppe specialist bird populations

Semi-natural open habitats have drastically changed in the last few decades due to agricultural intensification and rural depopulation. Steppe-birds, and especially those adapted to primary stages of vegetation succession, are threatened by an increase in scrub cover, and management actions are being applied to reverse scrub encroachment and restore habitat suitability in semi-natural open habitats. In this paper we evaluated for the first time, the long-term effects of a wildfire on habitat structure, vegetation productivity, and the associated response of an endangered scrub-steppe specialist bird, the Dupont’s Lark Chersophilus duponti. Wildfire occurred in a Mediterranean steppe of central Spain dominated by permanent community of dwarf cushions scrubs. Bird abundance was evaluated by line transects in the burnt and unburnt areas 3 years prior to the fire and 4 and 7 years after the fire. We quantified changes in habitat structure at fine scale level through vegetation sampling points and in vegetation productivity by estimating the Normalized Difference Vegetation Index (NDVI). Fire had strong effects for at least up to 4 years after the fire, when lower NDVI values, less scrub cover and fewer, but not significant, number of males were detected in the burnt area with respect to the pre-fire conditions. Seven years after fire most vegetation variables measured did not differ between areas, number of males detected within the burnt area was recovered and NDVI values in burnt area were slightly recovered but were significantly lower than in control area. Slow regeneration of the scrub cover after fire explained the unsuccessful occupation of the burnt area by the Dupont’s Lark up to several years after fire. The more dispersed and shorter habitat created by fire 7 years after the fire seems to be more suitable for the species than that in control areas. The large number of males around the burnt area may have played a role in the recolonization process. In sum, vegetation recovery and the presence of a low scrub-steppe specialist, as the Dupont’s lark, suggests that fire management could be integrated into conservation plans to effectively manage scrub encroachment processes in Mediterranean scrub-steppes.