Response of NDVI, biomass, and ecosystem gas exchange to long-term warming and fertilization in wet sedge tundra

Goose grubbing and warming suppress summer net ecosystem CO2 uptake differentially across high-Arctic tundra habitats

Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by ~55%, while warming increased them by ~35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above ~70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

The give and take of Arctic greening: differential responses of the carbon sink-to-source threshold to light and temperature in tussock tundra may be influenced by vegetation cover

A significant warming effect on arctic tundra is greening. Although this increase in predominantly woody vegetation has been linked to increases in gross primary productivity, increasing temperatures also stimulate ecosystem respiration. We present a novel analysis from small-scale plot measurements showing that the shape of the temperature- and light-dependent sink-to-source threshold (where net ecosystem exchange (NEE) equals zero) differs between two tussock tundra ecosystems differing in leaf area index (LAI). At the higher LAI site, the threshold is exceeded (i.e the ecosystem becomes a source) at relatively higher temperatures under low light but at lower temperatures under high light. At the lower LAI site, the threshold is exceeded at relatively lower temperatures under low light but at higher temperatures under high light. We confirmed this response at a single site where LAI was experimentally increased. This suggests the carbon balance of the tundra may be sensitive to small increases in temperature under low light, but that this effect may be significantly offset by increases in LAI. Importantly, we found that this LAI effect is reversed under high light, and so in a warming tundra, greater vegetation cover could have a progressively negative effect on net carbon uptake.

Phosphorus Interactions with Iron in Undisturbed and Disturbed Arctic Tundra Ecosystems

Phosphorus (P) limitation often constrains biological processes in Arctic tundra ecosystems. Although adsorption to soil minerals may limit P bioavailability and export from soils into aquatic systems, the contribution of mineral phases to P retention in Arctic tundra is poorly understood. Our objective was to use X-ray absorption spectroscopy to characterize P speciation and associations with soil minerals along hillslope toposequences and in undisturbed and disturbed low-lying wet sedge tundra on the North Slope, AK. Biogenic mats comprised of short-range ordered iron (Fe) oxyhydroxides were prevalent in undisturbed wet sedge meadows. Upland soils and pond sediments impacted by gravel mining or thermokarst lacked biogenic Fe mats and were comparatively iron poor. Phosphorus was primarily contained in organic compounds in hillslope soils but associated with Fe(III) oxyhydroxides in undisturbed wet sedge meadows and calcium (Ca) in disturbed pond sediments. We infer that phosphate mobilized through organic decomposition binds to Fe(III) oxyhydroxides in wet sedge, but these associations are disrupted by physical disturbance that removes Fe mats. Increasing disturbances of the Arctic tundra may continue to alter the mineralogical composition of soils at terrestrial-aquatic interfaces and binding mechanisms that could inhibit or promote transport of bioavailable P from soils to aquatic ecosystems.

Influence of climate variability and land cover dynamics on the spatio-temporal NDVI patterns in western hydrological regions of Bangladesh

Analyzing vegetation greenness considering climate and land cover changes is crucial for Bangladesh given the historically drier North-West and South-West regions of Bangladesh have shown prominent climatic and hydrological variations. Therefore, this study assessed the spatial and temporal variation of NDVI and its relationship with climate and land cover changes from 2000 to 2022 for these regions. In this study, Moran's I and Getis Ord Gi* were employed for spatial autocorrelation and Mann-Kendall, Sen's slope test along with Innovative Trend Analysis were deployed to identify temporal trends of NDVI. RMSE, MAE and R-squared values were assessed between computed and observed PET. Correlation of NDVI with climate variables were assessed through multivariate correlation analysis and correlation mapping. Additionally, Pearson product moment correlation was applied between different types of land cover and NDVI. Spatial autocorrelation outcomes showed that NDVI values have been clustered in distinct hotspots and cold-spots over the years. Temporal trend detection results indicate that NDVI values are rising significantly all over the regions. Multivariate correlation analysis identified no climate variable to be the limiting factor for NDVI changes. Similarly, the precipitation-NDVI correlation map displayed no significant correlation. Nonetheless, temperature-NDVI correlation map illustrated varying degrees of mostly moderate and strong positive correlations with distinct negative correlation results in the Sundarbans of South-West region. Land cover pattern analysis with NDVI showed a positive correlation to forest, cropland and vegetation area increasing and negative correlation to grassland and barren area decreasing. In this regard, Rangpur division exhibited stronger correlations than Rajshahi division in North-West. The findings indicate that NDVI changes in the regions are largely dependent on land cover changes in comparison to climate trends. This can instigate further research in other hydrological regions to explore the natural and man-made factors that can affect the greenery and vegetation density in specific regions.

Trends and drivers of Arctic-boreal fire intensity between 2003 and 2022

Climate change has disproportional effects on Arctic-boreal ecosystems, as the increase of air temperatures in these northern regions is several times higher than the global average. Ongoing warming and drying have resulted in recent record-breaking fire years in Arctic-boreal ecosystems, resulting in substantial carbon emissions that might accelerate climate change. While recent trends in Arctic-boreal burned area have been well documented, it is still unclear how fire intensity has changed. Fire intensity relates to the energy release from combustion and to a large extent drives the impact of a fire on the vegetation and soils, the emission of various gasses and the combustion completeness of different fuels. Here, we used the active fire product from the Moderate Resolution Imaging Spectroradiometer (MODIS) to examine trends in fire radiative power (FRP) over the entire Arctic-boreal region. We found a significant increase in annual median fire intensity between 2003 and 2022 in Eurasian boreal forests, for both daytime (increase of 0.392 MW/km2 per year, R2 = 0.56, p < 0.001) and nighttime fires (increase of 0.175 MW/km2 per year, R2 = 0.47, p < 0.001), while no general trend in FRP was observed in boreal North America. This increase in FRP in Eurasian boreal forests was strongly associated with simultaneous increases in air temperature, vapour pressure deficit, fire weather and fuel availability. We estimated that for Eurasia with each degree increase in air temperature, annual median daytime FRP increases with 1.58 MW/km2 in the tundra and 0.94 MW/km2 in the taiga. Climate change has thus resulted in a widespread and clear increase in fire intensity in central and eastern Eurasia while we could not discern clear trends in Arctic-boreal North America. Arctic-boreal fire intensity may further increase with climate change, with potentially major consequences for fire regimes, carbon emissions and society.

Evolutionary history shapes variation of wood density of tree species across the world

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

NDVI as a potential tool for forecasting changes in geographical range of sycamore (Acer pseudoplatanus L.)

Determining the natural range of Acer pseudoplatanus and the future directions of its spread is not clear. Modern technological achievements, including tools related to remote sensing, provide new opportunities to assess the degree of spread and adaptation of species to a changing climate. The aim of the work was to demonstrate the possibility of using NDVI to assess the habitat conditions of sycamore in Poland and the possibility of its natural expansion. The data analysis was divided into 2 parts. The first covered the characteristics of all sycamore stands occurring in Poland. In the second part, the analysis of sycamore stands using NDVI was made. The results of the study show that the highest average NDVI values are found in sycamore stands in the northern part of Poland, which has so far been considered less favorable for sycamore. This may suggest the potential for an increase in the share of sycamore towards the north. The results also confirm the forecasts given in the literature regarding the spread of sycamore towards Lithuania, Latvia and Estonia. The results also point to Denmark and the western part of the British Isles as potentially favorable habitats for sycamore.

Catchment characteristics control boreal mire nutrient regime and vegetation patterns over ~5000 years of landscape development

Vegetation holds the key to many properties that make natural mires unique, such as surface microtopography, high biodiversity values, effective carbon sequestration and regulation of water and nutrient fluxes across the landscape. Despite this, landscape controls behind mire vegetation patterns have previously been poorly described at large spatial scales, which limits the understanding of basic drivers underpinning mire ecosystem services. We studied catchment controls on mire nutrient regimes and vegetation patterns using a geographically constrained natural mire chronosequence along the isostatically rising coastline in Northern Sweden. By comparing mires of different ages, we can partition vegetation patterns caused by long-term mire succession (<5000 years) and present-day vegetation responses to catchment eco-hydrological settings. We used the remote sensing based normalized difference vegetation index (NDVI) to describe mire vegetation and combined peat physicochemical measures with catchment properties to identify the most important factors that determine mire NDVI. We found strong evidence that mire NDVI depends on nutrient inputs from the catchment area or underlying mineral soil, especially concerning phosphorus and potassium concentrations. Steep mire and catchment slopes, dry conditions and large catchment areas relative to mire areas were associated with higher NDVI. We also found long-term successional patterns, with lower NDVI in older mires. Importantly, the NDVI should be used to describe mire vegetation patterns in open mires if the focus is on surface vegetation, since the canopy cover in tree-covered mires completely dominated the NDVI signal. With our study approach, we can quantitatively describe the connection between landscape properties and mire nutrient regime. Our results confirm that mire vegetation responds to the upslope catchment area, but importantly, also suggest that mire and catchment aging can override the role of catchment influence. This effect was clear across mires of all ages, but was strongest in younger mires.

Assessing multiple limiting factors of seasonal biomass production and N content in a grassland with a year-round production

There is little evidence on the extent that multiple factors simultaneously limit ecosystem function of grasslands with year-round production. Here we test if multiple factors simultaneously limit (i.e., more than one factor at a time) grassland functioning in different seasons and how they interacted with N availability. In a Flooding Pampa grassland, we ran a separate factorial experiment in spring, summer, and winter with several treatments: control, mowing, shading, P addition, watering (only in summer), and warming (only in winter), each of them crossed with two nitrogen treatments: control and N addition. Grassland functioning was assessed by aboveground net primary productivity (ANPP), green and standing dead biomass, and N content at the species group level. Out of 24 potential cases (three seasons by eight response variables), 13 corresponded to just one limiting factor, 4 to multiple limiting factors, and the other 7 to no evidence of limitation. In conclusion, grassland functioning in each season was most often limited by just one factor, while multiple limiting factors were rarer. Nitrogen was the prevailing limiting factor. Our study expands our knowledge of limitations imposed by factors associated with disturbance and stress, such as mowing, shading, water availability, and warming in grasslands with year-round production.

Microbial iron cycling is prevalent in water-logged Alaskan Arctic tundra habitats, but sensitive to disturbance

Water logged habitats in continuous permafrost regions provide extensive oxic-anoxic interface habitats for iron cycling. The iron cycle interacts with the methane and phosphorus cycles, and is an important part of tundra biogeochemistry. Our objective was to characterize microbial communities associated with the iron cycle within natural and disturbed habitats of the Alaskan Arctic tundra. We sampled aquatic habitats within natural, undisturbed and anthropogenically disturbed areas and sequenced the 16S rRNA gene to describe the microbial communities, then supported these results with process rate and geochemical measurements. Undisturbed habitats have microbial communities that are significantly different than disturbed habitats. Microbial taxa known to participate in the iron and methane cycles are significantly associated with natural habitats, whereas they are not significantly associated with disturbed sites. Undisturbed habitats have significantly higher extractable iron and are more acidic than disturbed habitats sampled. Iron reduction is not measurable in disturbed aquatic habitats and is not stimulated by the addition of biogenic iron mats. Our study highlights the prevalence of Fe-cycling in undisturbed water-logged habitats, and demonstrates that anthropogenic disturbance of the tundra, due to legacy gravel mining, alters the microbiology of aquatic habitats and disrupts important biogeochemical cycles in the Arctic tundra.

NDVI changes in the Arctic: Functional significance in the moist acidic tundra of Northern Alaska

The Normalized Difference Vegetation Index (NDVI), derived from reflected visible and infrared radiation, has been critical to understanding change across the Arctic, but relatively few ground truthing efforts have directly linked NDVI to structural and functional properties of Arctic tundra ecosystems. To improve the interpretation of changing NDVI within moist acidic tundra (MAT), a common Arctic ecosystem, we coupled measurements of NDVI, vegetation structure, and CO2 flux in seventy MAT plots, chosen to represent the full range of typical MAT vegetation conditions, over two growing seasons. Light-saturated photosynthesis, ecosystem respiration, and net ecosystem CO2 exchange were well predicted by NDVI, but not by vertically-projected leaf area, our nondestructive proxy for leaf area index (LAI). Further, our data indicate that NDVI in this ecosystem is driven primarily by the biochemical properties of the canopy leaves of the dominant plant functional types, rather than purely the amount of leaf area; NDVI was more strongly correlated with top cover and repeated cover of deciduous shrubs than other plant functional types, a finding supported by our data from separate "monotypic" plots. In these pure stands of a plant functional type, deciduous shrubs exhibited higher NDVI than any other plant functional type. Likewise, leaves from the two most common deciduous shrubs, Betula nana and Salix pulchra, exhibited higher leaf-level NDVI than those from the codominant graminoid, Eriophorum vaginatum. Our findings suggest that recent increases in NDVI in MAT in the North American Arctic are largely driven by expanding deciduous shrub canopies, with substantial implications for MAT ecosystem function, especially net carbon uptake.

Spatiotemporal Evolution and Driving Forces of Vegetation Cover in the Urumqi River Basin

It is important to determine long-term changes in vegetation cover, and the associated driving forces, to better understand the natural and human-induced factors affecting vegetation growth. We calculated the fractional vegetation coverage (FVC) of the Urumqi River basin and selected seven natural factors (the clay and sand contents of surface soils, elevation, aspect, slope, precipitation and temperature) and one human factor (land use type). We then used the Sen-Man-Kendall method to calculate the changing trend of the FVC from 2000 to 2020. We used the optimal parameters-based geographical detector (OPGD) model to quantitatively analyze the influence of each factor on the change in vegetation coverage in the basin. The FVC of the Urumqi River basin fluctuated from 2000 to 2020, with average values between 0.22 and 0.33. The areas with no and low vegetation coverage accounted for two-thirds of the total area, whereas the areas with a medium, medium-high and high FVC accounted for one-third of the total area. The upper reaches of the river basin are glacial and forest areas with no vegetation coverage and a high FVC. The middle reaches are concentrated in areas of urban construction with a medium FVC. The lower reaches are in unstable farmland with a medium and high FVC and deserts with a low FVC and no vegetation. From the perspective of the change trend, the areas with an improved FVC accounted for 62.54% of the basin, stable areas accounted for 5.66% and degraded areas accounted for 31.8%. The FVC showed an increasing trend in the study area. The improvement was mainly in the areas of urban construction and desert. Degradation occurred in the high-elevation areas, whereas the transitional zone was unchanged. The analysis of driving forces showed that the human factor explained more of the changes in the FVC than the natural factors in the order: land use type (0.244) > temperature (0.216) > elevation (0.205) > soil clay content (0.172) > precipitation (0.163) > soil sand content (0.138) > slope (0.059) > aspect (0.014). Apart from aspect, the explanatory power (Q value) of the interaction of each factor was higher than that of the single factor. Risk detection showed that each factor had an interval in which the change in the FVC was inhibited or promoted. The optimum elevation interval of the study area was 1300-2700 m and the greatest inhibition of the FVC was seen above 3540 m. Too much or too little precipitation inhibited vegetation coverage.

Angolan highlands peatlands: Extent, age and growth dynamics

The Angolan highlands are hydrologically and ecologically important, supporting peatland deposits. Peatlands are carbon rich ecosystems and are the largest terrestrial carbon store. We present a first estimate of the extent of peatlands in the Angolan Highlands, using Google Earth Engine. Our conservative estimate of peatland coverage is 1634 km², 2.65% of a mapped area spanning approximately 61,590 km². This is a crucial first step in providing the peatland carbon inventory for the region and to facilitate conservation and management strategies. We include the peatland characteristics with respect to topographic data and common remote sensing indices of Normalised Difference Vegetation Index and Normalised Difference Water Index. The results suggest that Angolan Highlands peatland is highly variable in terms of elevation, slope, vegetation cover and standing water occurrence. Radiocarbon dating of riparian peatlands suggest two stages of peatland initiation: one about 7100 cal. yr BP, during the African humid period, and another from about 1100 cal. yr BP to present after the African humid period ended. The temporal control of riparian peat formation is river dynamics and the formation of terraces. Source lake peatland is slightly younger and has average maximum age of 890 cal. yr BP. The Angolan Highlands ecosystem and peatlands are possibly under strain from anthropogenic influence and climate change, making this peatland deposit a potential carbon emission source.

Microscale drivers of summer CO2 fluxes in the Svalbard High Arctic tundra

High-Arctic ecosystems are strongly affected by climate change, and it is still unclear whether they will become a carbon source or sink in the next few decades. In turn, such knowledge gaps on the drivers and the processes controlling CO₂ fluxes and storage make future projections of the Arctic carbon budget a challenging goal. During summer 2019, we extensively measured CO₂ fluxes at the soil–vegetation–atmosphere interface, together with basic meteoclimatic variables and ecological characteristics in the Bayelva river basin near Ny Ålesund, Spitzbergen, Svalbard (NO). By means of multi-regression models, we identified the main small-scale drivers of CO₂ emission (Ecosystem Respiration, ER), and uptake (Gross Primary Production, GPP) in this tundra biome, showing that (i) at point scale, the temporal variability of fluxes is controlled by the classical drivers, i.e. air temperature and solar irradiance respectively for ER and GPP, (ii) at site scale, the heterogeneity of fractional vegetation cover, soil moisture and vegetation type acted as additional source of variability for both CO₂ emissions and uptake. The assessment of the relative importance of such drivers in the multi-regression model contributes to a better understanding of the terrestrial carbon dioxide exchanges and of Critical Zone processes in the Arctic tundra.

Permafrost response to temperature rise in carbon and nutrient cycling: Effects from habitat-specific conditions and factors of warming

Permafrost is experiencing climate warming at a rate that is two times faster than the rest of the Earth's surface. However, it is still lack of a quantitative basis for predicting the functional stability of permafrost ecosystems in carbon (C) and nutrient cycling. We compiled the data of 708 observations from 89 air-warming experiments in the Northern Hemisphere and characterized the general effects of temperature increase on permafrost C exchange and balance, biomass production, microbial biomass, soil nutrients, and vegetation N dynamics through a meta-analysis. Also, an investigation was made on how responses might change with habitat-specific (e.g., plant functional groups and soil moisture status) conditions and warming variables (e.g., warming phases, levels, and timing). The net ecosystem C exchange (NEE) was found to be downregulated by warming as a result of a stronger sensitivity to warming in respiration (15.6%) than in photosynthesis (6.2%). Vegetation usually responded to warming by investing more C to the belowground, as belowground biomass increased much more (30.1%) than aboveground biomass (2.9%). Warming had a minor effect on microbial biomass. Warming increased soil ammonium and nitrate concentrations. What's more, a synthesis of 70 observations from 11 herbs and 9 shrubs revealed a 2.5% decline of N in green leaves. Compared with herbs, shrubs had a stronger response to respiration and had a decline in green leaf N to a greater extent. Not only in dry condition did green leaf N decline with warming but also in wet conditions. Warming in nongrowing seasons would negatively affect soil water, C uptake, and biomass production during growing seasons. Permafrost C loss and vegetation N decline may increase with warming levels and timing. Overall, these findings suggest that besides a positive C cycling-climate feedback, there will be a negative feedback between permafrost nutrient cycling and climate warming.

Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery

The net primary productivity (NPP) and aboveground biomass mapping of crops based on remote sensing technology are not only conducive to understanding the growth and development of crops but can also be used to monitor timely agricultural information, thereby providing effective decision making for agricultural production management. To solve the saturation problem of the NDVI in the aboveground biomass mapping of crops, the original CASA model was improved using narrow-band red-edge information, which is sensitive to vegetation chlorophyll variation, and the fraction of photosynthetically active radiation (FPAR), NPP, and aboveground biomass of winter wheat and maize were mapped in the main growing seasons. Moreover, in this study, we deeply analyzed the seasonal change trends of crops’ biophysical parameters in terms of the NDVI, FPAR, actual light use efficiency (LUE), and their influence on aboveground biomass. Finally, to analyze the uncertainty of the aboveground biomass mapping of crops, we further discussed the inversion differences of FPAR with different vegetation indices. The results demonstrated that the inversion accuracies of the FPAR of the red-edge normalized vegetation index (NDVIred-edge) and red-edge simple ratio vegetation index (SRred-edge) were higher than those of the original CASA model. Compared with the reference data, the accuracy of aboveground biomass estimated by the improved CASA model was 0.73 and 0.70, respectively, which was 0.21 and 0.13 higher than that of the original CASA model. In addition, the analysis of the FPAR inversions of different vegetation indices showed that the inversion accuracies of the red-edge vegetation indices NDVIred-edge and SRred-edge were higher than those of the other vegetation indices, which confirmed that the vegetation indices involving red-edge information can more effectively retrieve FPAR and aboveground biomass of crops.

Vegetation responses to extreme climatic indices in coastal China from 1986 to 2015

Climate extremes have resulted in substantial vegetation changes in the marine-terrestrial transitional zone. As a climatically-sensitive region, coastal China is currently experiencing prominent environmental climate change. To identify how climatic extremes affect ecosystem function, we calculated eleven indices of climatic extremes and four mean indices for six sub-regions of coastal China. Deseasonalized thirty-year (1986-2015) net primary productivity (NPP) was used as an indicator of ecosystem productivity, and its relationships with the climate indices were investigated at multiple scales (annual and seasonal) explicitly. The results demonstrated that: (1) annual NPP indicated an overall greening trend (in 73.71% of the study area) and partial degradation (in 26.29% of the study area) over the last thirty decades years; (2) coastal areas had experienced warming overall, with higher increases in nighttime temperatures relative to daytime temperatures; (3) in southern areas, maximum/ minimum daily maximum temperature had driven increases in NPP, whereas in northern areas, this effect varied between vegetation types; (4) Diurnal temperature range (DTR) and NPP were negatively correlated in the north and positively correlated in the south; and (5) Maximum 1-day precipitation promoted vegetation production across the whole study area. Maximum 5-day precipitation promoted vegetation growth in the north but had the opposite effect in the south. Our study advances understanding of vegetation dynamics and its driving mechanisms, and provides support for scientifically informed ecological management practices in coastal China.

Prediction of the Kiwifruit Decline Syndrome in Diseased Orchards by Remote Sensing

Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing root rot, has already affected more than 25% of the area under kiwifruit cultivation in Italy. Diseased plants are characterised by severe decay of the fine roots and sudden wilting of the canopy, which is only visible after the season’s first period of heat (July–August). The swiftness of symptom appearance prevents correct timing and positioning for sampling of the disease, and is therefore a barrier to aetiological studies. The aim of this study is to test the feasibility of thermal and multispectral imaging for the detection of KD using an unsupervised classifier. Thus, RGB, multispectral and thermal data from a kiwifruit orchard, with healthy and diseased plants, were acquired simultaneously during two consecutive growing seasons (2017–2018) using an Unmanned Aerial Vehicle (UAV) platform. Data reduction was applied to the clipped areas of the multispectral and thermal data from the 2017 survey. Reduced data were then classified with two unsupervised algorithms, a K-means and a hierarchical method. The plant vigour (canopy size and presence/absence of wilted leaves) and the health shifts exhibited by asymptomatic plants between 2017 and 2018 were evaluated from RGB data via expert assessment and used as the ground truth for cluster interpretation. Multispectral data showed a high correlation with plant vigour, while temperature data demonstrated a good potential use in predicting health shifts, especially in highly vigorous plants that were asymptomatic in 2017 and became symptomatic in 2018. The accuracy of plant vigour assessment was above 73% when using multispectral data, while clustering of the temperature data allowed the prediction of disease outbreak one year in advance, with an accuracy of 71%. Based on our results, the unsupervised clustering of remote sensing data could be a reliable tool for the identification of sampling areas, and can greatly improve aetiological studies of this new disease in kiwifruit.

Determining the contributions of climate change and human activities to vegetation dynamics in agro-pastural transitional zone of northern China from 2000 to 2015

The vegetation in the agro-pastoral transitional zone of northern China (APTZNC) was significantly restored, and both climate change and ecological restoration projects contributed to vegetation activities with varied proportion. Since few decades ago, APTZNC has undergone significant land degradation and climate change, threatening regional sustainable development, and in response to such ecological crises, multiple ecological restoration projects were implemented, which have caused a profound impact on the terrestrial ecosystem. Taking agro-pastural transitional zone of northern China (APTZNC) as the study area, this study used 16-year (2000-2015) net primary productivity (NPP) as an important indicator of the arid and semi-arid ecosystem's productivity, combing meteorological data in same period to (1) monitor the vegetation dynamics affected by both climate and ecological restoration projects; (2) detect climate changing trend, including annual precipitation, air temperature, and sunlight hours; (3) explicitly distinguish driving forces of climate change and ecological restoration projects on vegetation dynamics based on correlation analysis. The results demonstrated that (1) the annual NPP indicated overall greening (48.77% significant restoration) and partial degradation (0.39% significant degradation) in APTZNC; (2) the annual precipitation was the main factor that widely influences vegetation growth, and the area with significant influence accounted for 55.53%; however, the area with significant temperature influence only accounted for 1%, and the area affected significantly by sunshine hours accounted for 14.33%; (3) In the area of significant greening with proportion of 48.77%, of 26.93% was related to climate change, of 19.80% was related to ecological conservation programs, and of 2.05% was related to multiple factors. In the significantly degraded area with proportion of 0.39%, of 0.1% is related to climate change and of 0.29% is abnormally degraded. Our study is expected to accelerate the understanding of vegetation dynamics and its driving mechanisms, and provide support for scientifically formulating and adjusting ecological restoration projects in APTZNC.

Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches

In this study, we focused on three species that have proven to be vulnerable to winter stress: Empetrum nigrum,Vaccinium vitis-idaea and Hylocomium splendens. Our objective was to determine plant traits suitable for monitoring plant stress as well as trait shifts during spring. To this end, we used a combination of active and passive handheld normalized difference vegetation index (NDVI) sensors, RGB indices derived from ordinary cameras, an optical chlorophyll and flavonol sensor (Dualex), and common plant traits that are sensitive to winter stress, i.e. height, specific leaf area (SLA). Our results indicate that NDVI is a good predictor for plant stress, as it correlates well with height (r = 0.70, p < 0.001) and chlorophyll content (r = 0.63, p < 0.001). NDVI is also related to soil depth (r = 0.45, p < 0.001) as well as to plant stress levels based on observations in the field (r = −0.60, p < 0.001). Flavonol content and SLA remained relatively stable during spring. Our results confirm a multi-method approach using NDVI data from the Sentinel-2 satellite and active near-remote sensing devices to determine the contribution of understory vegetation to the total ecosystem greenness. We identified low soil depth to be the major stressor for understory vegetation in the studied plots. The RGB indices were good proxies to detect plant stress (e.g. Channel G%: r = −0.77, p < 0.001) and showed high correlation with NDVI (r = 0.75, p < 0.001). Ordinary cameras and modified cameras with the infrared filter removed were found to perform equally well.

A mechanism of expansion: Arctic deciduous shrubs capitalize on warming-induced nutrient availability

Warming-induced nutrient enrichment in the Arctic may lead to shifts in leaf-level physiological properties and processes with potential consequences for plant community dynamics and ecosystem function. To explore the physiological responses of Arctic tundra vegetation to increasing nutrient availability, we examined how a set of leaf nutrient and physiological characteristics of eight plant species (representing four plant functional groups) respond to a gradient of experimental nitrogen (N) and phosphorus (P) enrichment. Specifically, we examined a set of chlorophyll fluorescence measures related to photosynthetic efficiency, performance and stress, and two leaf nutrient traits (leaf %C and %N), across an experimental nutrient gradient at the Arctic Long Term Ecological Research site, located in the northern foothills of the Brooks Range, Alaska. In addition, we explicitly assessed the direct relationships between chlorophyll fluorescence and leaf %N. We found significant differences in physiological and nutrient traits between species and plant functional groups, and we found that species within one functional group (deciduous shrubs) have significantly greater leaf %N at high levels of nutrient addition. In addition, we found positive, saturating relationships between leaf %N and chlorophyll fluorescence measures across all species. Our results highlight species-specific differences in leaf nutrient traits and physiology in this ecosystem. In particular, the effects of a gradient of nutrient enrichment were most prominent in deciduous plant species, the plant functional group known to be increasing in relative abundance with warming in this ecosystem.

Forest dynamics in relation to meteorology and soil in the Gulf Coast of Mexico

Forest dynamics is complex, and the complexity could be a synthetic result of climate change. Specifically studying 11 forest type groups of the Gulf of Mexico coast region defined, we intended to explore and model the direct and indirect impacts of climate change on underlying forest dynamics. This study utilized normalized difference of vegetation index (NDVI) as a measurement indicator of forest dynamics, referring to the dynamics of canopy structure and phenology of forests, and for a given type of forests, seasonal and yearly NDVI values were applied to the quantification of its growth across the Gulf Coast. By utilizing geographically weighted regression (GWR) method, we related normalized difference vegetation index (NDVI) to precipitation, temperature, and silt and clay fractions in the soil. This study demonstrated an explanatory power of soil, besides the common macroclimate factors of precipitation, temperature, on explaining forest dynamics, which also revealed that the presence of spatiotemporal heterogeneity would affect model performance. Our results indicated that the model performance varied by forest type groups and seasons. The meteorology-soil model presented the best overall fit performance for White/Red/Jack Pine forests concerning R² (0.952), adjusted R² (0.905), Akaike information criterion (AIC, -1100) and residual sum of squares (RSS, 0.053) values. The comparative analysis of model performance also indicated that the meteorology-soil model has the best fit of data in summer. This study advanced the understanding of forests dynamics under conditions of climate change by highlighting the significance of soil, which is a significant confounding variable influencing forest activities but is often missed in forest-climate dynamics analysis.

NDVI Changes Show Warming Increases the Length of the Green Season at Tundra Communities in Northern Alaska: A Fine-Scale Analysis

A warming Arctic has been associated with increases in aboveground plant biomass, specifically shrubs, and changes in vegetation cover. However, the magnitude and direction of changes in NDVI have not been consistent across different tundra types. Here we examine the responsiveness of fine-scale NDVI values to experimental warming at eight sites in northern Alaska, United States. Warming in our eight sites ranged in duration from 2‑23 seasons. Dry, wet and moist tundra communities were monitored for canopy surface temperatures and NDVI in ambient and experimentally-warmed plots at near-daily frequencies during the summer of 2017 to assess the impact of the warming treatment on the magnitude and timing of greening. Experimental warming increased canopy-level surface temperatures across all sites (+0.47 to +3.14˚C), with the strongest warming effect occurring during June and July and for the southernmost sites. Green-up was accelerated by warming at six sites, and autumn senescence was delayed at five sites. Warming increased the magnitude of peak NDVI values at five sites, decreased it at one site, and at two sites it did not change. Warming resulted in earlier peak NDVI at three sites and no significant change in the other sites. Shrub and graminoid cover was positively correlated with the magnitude of peak NDVI (r=0.37 to 0.60) while cryptogam influence was mixed. The magnitude and timing of peak NDVI showed considerable variability across sites. Warming extended the duration of the summer green season at most sites due to accelerated greening in the spring and delayed senescence in the autumn. We show that in a warmer Arctic (as simulated by our experiment) the timing and total period of carbon gain may change. Our results suggest these changes are dependent on community composition and abundance of specific growth forms and therefore will likely impact net primary productivity and trophic interactions.

Dynamic Monitoring and Analysis of Ecological Quality of Pingtan Comprehensive Experimental Zone, a New Type of Sea Island City, Based on RSEI

Islands face increasingly prominent environmental problems with rapid urbanization. Hence, timely and objective monitoring and evaluation of island ecology is of great significance. This study took the Pingtan Comprehensive Experimental Zone (PZ) in the east sea of Fujian Province of China as the research object. Based on remote sensing technology, four Landsat images from 2007 to 2017 and the remote sensing ecological index (RSEI) were used to explore the ecological status and space–time change. The results showed that from 2007 to 2011, the average RSEI decreased from 0.519 to 0.506, indicating that the ecological quality generally showed a slight downward trend, mainly due to large-scale development brought by the construction; by 2014, although the ecology of the original area improved, the overall ecology was still declining with 0.502 mean RSEI mainly because of large-scale reclamation projects; by 2017, the average RSEI rebounded to 0.523, which was attributed to the fact that ecological construction and protection were emphasized in the construction of PZ, especially in reclamation areas. In conclusion, the increase of large area bare soil will lead to the decline of regional ecology, but the implementation of scientific ecological planning is conducive to ecological restoration and construction.

Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing

Peatlands, which account for approximately 15% of land surface across the arctic and boreal regions of the globe, are experiencing a range of ecological impacts as a result of climate change. Factors that include altered hydrology resulting from drought and permafrost thaw, rising temperatures, and elevated levels of atmospheric carbon dioxide have been shown to cause plant community compositional changes. Shifts in plant composition affect the productivity, species diversity, and carbon cycling of peatlands. We used hyperspectral remote sensing to characterize the response of boreal peatland plant composition and species diversity to warming, hydrologic change, and elevated CO2. Hyperspectral remote sensing techniques offer the ability to complete landscape-scale analyses of ecological responses to climate disturbance when paired with plot-level measurements that link ecosystem biophysical properties with spectral reflectance signatures. Working within two large ecosystem manipulation experiments, we examined climate controls on composition and diversity in two types of common boreal peatlands: a nutrient rich fen located at the Alaska Peatland Experiment (APEX) in central Alaska, and an ombrotrophic bog located in northern Minnesota at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. We found a strong effect of plant functional cover on spectral reflectance characteristics. We also found a positive relationship between species diversity and spectral variation at the APEX field site, which is consistent with other recently published findings. Based on the results of our field study, we performed a supervised land cover classification analysis on an aerial hyperspectral dataset to map peatland plant functional types (PFTs) across an area encompassing a range of different plant communities. Our results underscore recent advances in the application of remote sensing measurements to ecological research, particularly in far northern ecosystems.

Impacts of climate change and human activities on grassland vegetation variation in the Chinese Loess Plateau

China initiated the "Grain for Green Project" in 1999 to mitigate soil erosion. The vegetation cover of the Chinese Loess Plateau, one of the most erosive regions in the world, has been greatly increased. However, studies on quantitatively investigating the climate change and human activities on vegetation coverage change were rare. In this study, spatio-temporal changes in vegetation coverage were investigated using MODIS normalized difference vegetation index (NDVI) data over 2000-2016. And a new method was introduced using Net Primary Productivity (NPP) model and relationship between NPP and NDVI to quantitatively and spatially distinguish the NDVI affected by climate change and human activities. Results showed that mean NDVI value over 2009-2016 were 14.46% greater than that over 2000-2007. In order to quantify the contribution of climate change and human activities to vegetation change, an NPP model suitable for the grassland of the Chinese Loess Plateau was identified using biomass observations from field survey and literature. The NDVI affected by climate change (NDVI_climate) was estimated by the NPP model and the relationship between NPP and NDVI. And the NDVI affected by human activities (NDVI_human) was calculated by actual NDVI minus NDVI_climate. Comparison of the two stages showed that human activities and climate change contributed 42.35% and 57.65% respectively to the ΔNDVI on grassland in the Loess Plateau. After analysis of numerous NDVI_human related factors, the slopes restored by the "Grain for Green Project" was considered the main influence factor of human activities.

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.

Delayed herbivory by migratory geese increases summer-long CO2 uptake in coastal western Alaska

The advancement of spring and the differential ability of organisms to respond to changes in plant phenology may lead to "phenological mismatches" as a result of climate change. One potential for considerable mismatch is between migratory birds and food availability in northern breeding ranges, and these mismatches may have consequences for ecosystem function. We conducted a three-year experiment to examine the consequences for CO₂ exchange of advanced spring green-up and altered timing of grazing by migratory Pacific black brant in a coastal wetland in western Alaska. Experimental treatments represent the variation in green-up and timing of peak grazing intensity that currently exists in the system. Delayed grazing resulted in greater net ecosystem exchange (NEE) and gross primary productivity (GPP), while early grazing reduced CO₂ uptake with the potential of causing net ecosystem carbon (C) loss in late spring and early summer. Conversely, advancing the growing season only influenced ecosystem respiration (ER), resulting in a small increase in ER with no concomitant impact on GPP or NEE. The experimental treatment that represents the most likely future, with green-up advancing more rapidly than arrival of migratory geese, results in NEE changing by 1.2 µmol m^-2  s^-1 toward a greater CO₂ sink in spring and summer. Increased sink strength, however, may be mitigated by early arrival of migratory geese, which would reduce CO₂ uptake. Importantly, while the direct effect of climate warming on phenology of green-up has a minimal influence on NEE, the indirect effect of climate warming manifest through changes in the timing of peak grazing can have a significant impact on C balance in northern coastal wetlands. Furthermore, processes influencing the timing of goose migration in the winter range can significantly influence ecosystem function in summer habitats.

Recovery Rates of Wetland Vegetation Greenness in Severely Burned Ecosystems of Alaska Derived from Satellite Image Analysis

The analysis of wildfire impacts at the scale of less than a square kilometer can reveal important patterns of vegetation recovery and regrowth in freshwater Arctic and boreal regions. For this study, NASA Landsat burned area products since the year 2000, and a near 20-year record of vegetation green cover from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor were combined to reconstruct the recovery rates and seasonal profiles of burned wetland ecosystems in Alaska. Region-wide breakpoint analysis results showed that significant structural change could be detected in the 250-m normalized difference vegetation index (NDVI) time series for the vast majority of wetland locations in the major Yukon river drainages of interior Alaska that had burned at high severity since the year 2001. Additional comparisons showed that wetland cover locations across Alaska that have burned at high severity subsequently recovered their green cover seasonal profiles to relatively stable pre-fire levels in less than 10 years. Negative changes in the MODIS NDVI, namely lower greenness in 2017 than pre-fire and incomplete greenness recovery, were more commonly detected in burned wetland areas after 2013. In the years prior to 2013, the NDVI change tended to be positive (higher greenness in 2017 than pre-fire) at burned wetland elevations lower than 400 m, whereas burned wetland locations at higher elevation showed relatively few positive greenness recovery changes by 2017.

Large herbivores surf waves of green-up during spring

The green wave hypothesis (GWH) states that migrating animals should track or 'surf' high-quality forage at the leading edge of spring green-up. To index such high-quality forage, recent work proposed the instantaneous rate of green-up (IRG), i.e. rate of change in the normalized difference vegetation index over time. Despite this important advancement, no study has tested the assumption that herbivores select habitat patches at peak IRG. We evaluated this assumption using step selection functions parametrized with movement data during the green-up period from two populations each of bighorn sheep, mule deer, elk, moose and bison, totalling 463 individuals monitored 1-3 years from 2004 to 2014. Accounting for variables that typically influence habitat selection for each species, we found seven of 10 populations selected patches exhibiting high IRG-supporting the GWH. Nonetheless, large herbivores selected for the leading edge, trailing edge and crest of the IRG wave, indicating that other mechanisms (e.g. ruminant physiology) or measurement error inherent with satellite data affect selection for IRG. Our evaluation indicates that IRG is a useful tool for linking herbivore movement with plant phenology, paving the way for significant advancements in understanding how animals track resource quality that varies both spatially and temporally.

Clipping has stronger effects on plant production than does warming in three alpine meadow sites on the Northern Tibetan Plateau

The relative effects of warming and clipping on vegetation growth are not fully understood. Therefore, we compared the relative effects of experimental warming and clipping on the normalised difference vegetation index (NDVI), green NDVI (GNDVI), soil-adjusted vegetation index (SAVI), aboveground biomass (AGB) and gross primary production (GPP) in three alpine meadow sites (A, B and C) on the Northern Tibetan Plateau from 2013 to 2015. There were no obvious effects of experimental warming on the NDVI, GNDVI, SAVI, AGB and GPP at the three sites, which were most likely attributed to experimental warming-induced warming and drying conditions. In contrast, clipping significantly decreased the NDVI, SAVI and AGB by 27.8%, 31.3% and 18.2% at site A, by 27.1%, 31.8% and 27.7% at site B, and by 12.3%, 15.1% and 17.6% at site C, respectively. Clipping also significantly reduced the GNDVI and GPP by 11.1% and 28.2% at site A and by 18.9% and 33.7% at site B, respectively. Clipping marginally decreased the GNDVI by 8.7% (p = 0.060) and GPP (p = 0.082) by 14.4% at site C. Therefore, clipping had stronger effects on vegetation growth than did warming in the three alpine meadow sites on the Tibetan Plateau.

Nonlinear CO2 flux response to 7 years of experimentally induced permafrost thaw

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss. Using data from 7 years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO₂ flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (R_eco ), gross primary productivity (GPP), and net summer CO₂ storage (NEE). Over 7 years R_eco , GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, R_eco , GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated microsites and suppressed R_eco , GPP, and NEE. However R_eco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher R_eco in deeply thawed areas during summer months was balanced by GPP. Summer CO₂ flux across treatments fit a single quadratic relationship that captured the functional response of CO₂ flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO₂ flux: plant growth and water table dynamics. Nonsummer R_eco models estimated that the area was an annual CO₂ source during all years of observation. Nonsummer CO₂ loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO₂ source.

Spatiotemporal dynamics of grassland aboveground biomass on the Qinghai-Tibet Plateau based on validated MODIS NDVI

Spatiotemporal dynamics of aboveground biomass (AGB) is a fundamental problem for grassland environmental management on the Qinghai-Tibet Plateau (QTP). Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data can feasibly be used to estimate AGB at large scales, and their precise validation is necessary to utilize them effectively. In our study, the clip-harvest method was used at 64 plots in QTP grasslands to obtain actual AGB values, and a handheld hyperspectral spectrometer was used to calculate field-measured NDVI to validate MODIS NDVI. Based on the models between NDVI and AGB, AGB dynamics trends during 2000–2012 were analyzed. The results showed that the AGB in QTP grasslands increased during the study period, with 70% of the grasslands undergoing increases mainly in the Qinghai Province. Also, the meadow showed a larger increasing trend than steppe. Future AGB dynamic trends were also investigated using a combined analysis of the slope values and the Hurst exponent. The results showed high sustainability of AGB dynamics trends after the study period. Predictions indicate 60% of the steppe and meadow grasslands would continue to increase in AGB, while 25% of the grasslands would remain in degradation, with most of them distributing in Tibet.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

A gradient of nutrient enrichment reveals nonlinear impacts of fertilization on Arctic plant diversity and ecosystem function

Rapid environmental change at high latitudes is predicted to greatly alter the diversity, structure, and function of plant communities, resulting in changes in the pools and fluxes of nutrients. In Arctic tundra, increased nitrogen (N) and phosphorus (P) availability accompanying warming is known to impact plant diversity and ecosystem function; however, to date, most studies examining Arctic nutrient enrichment focus on the impact of relatively large (>25x estimated naturally occurring N enrichment) doses of nutrients on plant community composition and net primary productivity. To understand the impacts of Arctic nutrient enrichment, we examined plant community composition and the capacity for ecosystem function (net ecosystem exchange, ecosystem respiration, and gross primary production) across a gradient of experimental N and P addition expected to more closely approximate warming-induced fertilization. In addition, we compared our measured ecosystem CO ₂ flux data to a widely used Arctic ecosystem exchange model to investigate the ability to predict the capacity for CO ₂ exchange with nutrient addition. We observed declines in abundance-weighted plant diversity at low levels of nutrient enrichment, but species richness and the capacity for ecosystem carbon uptake did not change until the highest level of fertilization. When we compared our measured data to the model, we found that the model explained roughly 30%-50% of the variance in the observed data, depending on the flux variable, and the relationship weakened at high levels of enrichment. Our results suggest that while a relatively small amount of nutrient enrichment impacts plant diversity, only relatively large levels of fertilization-over an order of magnitude or more than warming-induced rates-significantly alter the capacity for tundra CO ₂ exchange. Overall, our findings highlight the value of measuring and modeling the impacts of a nutrient enrichment gradient, as warming-related nutrient availability may impact ecosystems differently than single-level fertilization experiments.

Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site

Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-decades. In the Alaskan Arctic, the 25-year record of warming of air temperature revealed no significant trend, yet environmental and ecological changes prove that warming is affecting the ecosystem. The useful indicators are deep permafrost temperatures, vegetation and shrub biomass, satellite measures of canopy reflectance (NDVI), and chemical measures of soil weathering. In contrast, the 18-year record in the Greenland Arctic revealed an extremely high summer air-warming of 1.3 °C/decade; the cover of some plant species increased while the cover of others decreased. Useful indicators of change are NDVI and the active layer thickness.

Environmental Humidity Regulates Effects of Experimental Warming on Vegetation Index and Biomass Production in an Alpine Meadow of the Northern Tibet

Uncertainty about responses of vegetation index, aboveground biomass (AGB) and gross primary production (GPP) limits our ability to predict how climatic warming will influence plant growth in alpine regions. A field warming experiment was conducted in an alpine meadow at a low (4313 m), mid- (4513 m) and high elevation (4693 m) in the Northern Tibet since May 2010. Growing season vapor pressure deficit (VPD), soil temperature (T_s) and air temperature (T_a) decreased with increasing elevation, while growing season precipitation, soil moisture (SM), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), AGB and GPP increased with increasing elevation. The growing season T_a, T_s and VPD in 2015 was greater than that in 2014, while the growing season precipitation, SM, NDVI, SAVI, AGB and GPP in 2015 was lower than that in 2014, respectively. Compared to the mean air temperature and precipitation during the growing season in 1963–2015, it was a warmer and wetter year in 2014 and a warmer and drier year in 2015. Experimental warming increased growing season T_s, T_a,VPD, but decreased growing season SM in 2014–2015 at all the three elevations. Experimental warming only reduced growing season NDVI, SAVI, AGB and GPP at the low elevation in 2015. Growing season NDVI, SAVI, AGB and GPP increased with increasing SM and precipitation, but decreased with increasing VPD, indicating vegetation index and biomass production increased with environmental humidity. The VPD explained more variation of growing season NDVI, SAVI, AGB and GPP compared to T_s, T_a and SM at all the three elevations. Therefore, environmental humidity regulated the effect of experimental warming on vegetation index and biomass production in alpine meadows on the Tibetan Plateau.

Effects of long-term nutrient additions on Arctic tundra, stream, and lake ecosystems: beyond NPP

Primary producers form the base of food webs but also affect other ecosystem characteristics, such as habitat structure, light availability, and microclimate. Here, we examine changes caused by 5-30+ years of nutrient addition and resulting increases in net primary productivity (NPP) in tundra, streams, and lakes in northern Alaska. The Arctic provides an important opportunity to examine how ecosystems characterized by low diversity and low productivity respond to release from nutrient limitation. We review how responses of algae and plants affect light availability, perennial biotic structures available for consumers, oxygen levels, and temperature. Sometimes, responses were similar across all three ecosystems; e.g., increased NPP significantly reduced light to the substrate following fertilization. Perennial biotic structures increased in tundra and streams but not in lakes, and provided important new habitat niches for consumers as well as other producers. Oxygen and temperature responses also differed. Life history traits (e.g., longevity) of the primary producers along with the fate of detritus drove the responses and recovery. As global change persists and nutrients become more available in the Arctic and elsewhere, incorporating these factors as response variables will enable better prediction of ecosystem changes and feedbacks in this biome and others.

Net ecosystem exchange of CO2 with rapidly changing high Arctic landscapes

High Arctic landscapes are expansive and changing rapidly. However, our understanding of their functional responses and potential to mitigate or enhance anthropogenic climate change is limited by few measurements. We collected eddy covariance measurements to quantify the net ecosystem exchange (NEE) of CO2 with polar semidesert and meadow wetland landscapes at the highest latitude location measured to date (82°N). We coupled these rare data with ground and satellite vegetation production measurements (Normalized Difference Vegetation Index; NDVI) to evaluate the effectiveness of upscaling local to regional NEE. During the growing season, the dry polar semidesert landscape was a near-zero sink of atmospheric CO2 (NEE: -0.3 ± 13.5 g C m(-2) ). A nearby meadow wetland accumulated over 300 times more carbon (NEE: -79.3 ± 20.0 g C m(-2) ) than the polar semidesert landscape, and was similar to meadow wetland NEE at much more southerly latitudes. Polar semidesert NEE was most influenced by moisture, with wetter surface soils resulting in greater soil respiration and CO2 emissions. At the meadow wetland, soil heating enhanced plant growth, which in turn increased CO2 uptake. Our upscaling assessment found that polar semidesert NDVI measured on-site was low (mean: 0.120-0.157) and similar to satellite measurements (mean: 0.155-0.163). However, weak plant growth resulted in poor satellite NDVI-NEE relationships and created challenges for remotely detecting changes in the cycling of carbon on the polar semidesert landscape. The meadow wetland appeared more suitable to assess plant production and NEE via remote sensing; however, high Arctic wetland extent is constrained by topography to small areas that may be difficult to resolve with large satellite pixels. We predict that until summer precipitation and humidity increases enough to offset poor soil moisture retention, climate-related changes to productivity on polar semideserts may be restricted.

Coupled long-term summer warming and deeper snow alters species composition and stimulates gross primary productivity in tussock tundra

Climate change is expected to increase summer temperature and winter precipitation throughout the Arctic. The long-term implications of these changes for plant species composition, plant function, and ecosystem processes are difficult to predict. We report on the influence of enhanced snow depth and warmer summer temperature following 20 years of an ITEX experimental manipulation at Toolik Lake, Alaska. Winter snow depth was increased using snow fences and warming was accomplished during summer using passive open-top chambers. One of the most important consequences of these experimental treatments was an increase in active layer depth and rate of thaw, which has led to deeper drainage and lower soil moisture content. Vegetation concomitantly shifted from a relatively wet system with high cover of the sedge Eriophorum vaginatum to a drier system, dominated by deciduous shrubs including Betula nana and Salix pulchra. At the individual plant level, we observed higher leaf nitrogen concentration associated with warmer temperatures and increased snow in S. pulchra and B. nana, but high leaf nitrogen concentration did not lead to higher rates of net photosynthesis. At the ecosystem level, we observed higher GPP and NEE in response to summer warming. Our results suggest that deeper snow has a cascading set of biophysical consequences that include a deeper active layer that leads to altered species composition, greater leaf nitrogen concentration, and higher ecosystem-level carbon uptake.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models.

Remote sensing of ecosystem health: opportunities, challenges, and future perspectives

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

The influence of weather and lemmings on spatiotemporal variation in the abundance of multiple avian guilds in the arctic

Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010-2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between weather, spring snow cover, lemming abundance, and spatiotemporal variations in Arctic-breeding birds.