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Monitoring agriculture by remote sensing enables large‐scale evaluation of biomass production across space and time. The normalized difference vegetation index (NDVI) is used as a proxy for green biomass. Here, we used satellite‐derived NDVI of arable farms in the Netherlands to evaluate changes in biomass following conversion from conventional to organic farming. We compared NDVI and the stability of NDVI across 72 fields on sand and marine clay soils. Thirty‐six of these fields had been converted into organic agriculture between 0 and 50 years ago (with 2017 as reference year), while the other 36 were paired control fields where conventional farming continued. We used high‐resolution images from the Sentinel‐2 satellite to obtain NDVI estimates across 5 years (January 2016–October 2020). Overall, NDVI did not differ between conventional and organic management during the time series, but NDVI stability was significantly higher under organic management. NDVI was lower under organic management in sandy, but not in clay, soils. Organic farms that had been converted less than ~19 years ago had lower NDVI than conventional farms. However, the difference diminished over time and eventually turned positive after ~19 years since the conversion. NDVI, averaged across the 5 years of study, was positively correlated to soil Olsen‐P measured from soil samples collected in 2017. We conclude that NDVI in organic fields was more stable than in conventional fields, and that the lower biomass in the early years since the transition to organic agriculture can be overcome with time. Our study also indicates the role of soil P bioavailability for plant biomass production across the examined fields, and the benefit of combining remote sensing with on‐site soil measurements to develop a more mechanistic understanding that may help us navigate the transition to a more sustainable type of agriculture. [ABSTRACT FROM AUTHOR]

In this Technical Advance, we describe a novel method to improve ecological interpretation of remotely sensed vegetation greenness measurements that involved sampling 24,395 Landsat pixels (30 m) across 639 km of Alaska's central Brooks Range. The method goes well beyond the spatial scale of traditional plot‐based sampling and thereby more thoroughly relates ground‐based observations to satellite measurements. Our example dataset illustrates that, along the boreal‐Arctic boundary, vegetation with the greatest Landsat Normalized Difference Vegetation Index (NDVI) is taller than 1 m, woody, and deciduous; whereas vegetation with lower NDVI tends to be shorter, evergreen, or non‐woody. The field methods and associated analyses advance efforts to inform satellite data with ground‐based vegetation observations using field samples collected at spatial scales that closely match the resolution of remotely sensed imagery. [ABSTRACT FROM AUTHOR]

Global climate change has altered the timing of seasonal events (i.e., phenology) for a diverse range of biota. Within and among species, however, the degree to which alterations in phenology match climate variability differ substantially. To better understand factors driving these differences, we evaluated variation in timing of nesting of eight Arctic‐breeding shorebird species at 18 sites over a 23‐year period. We used the Normalized Difference Vegetation Index as a proxy to determine the start of spring (SOS) growing season and quantified relationships between SOS and nest initiation dates as a measure of phenological responsiveness. Among species, we tested four life history traits (migration distance, seasonal timing of breeding, female body mass, expected female reproductive effort) as species‐level predictors of responsiveness. For one species (Semipalmated Sandpiper), we also evaluated whether responsiveness varied across sites. Although no species in our study completely tracked annual variation in SOS, phenological responses were strongest for Western Sandpipers, Pectoral Sandpipers, and Red Phalaropes. Migration distance was the strongest additional predictor of responsiveness, with longer‐distance migrant species generally tracking variation in SOS more closely than species that migrate shorter distances. Semipalmated Sandpipers are a widely distributed species, but adjustments in timing of nesting relative to variability in SOS did not vary across sites, suggesting that different breeding populations of this species were equally responsive to climate cues despite differing migration strategies. Our results unexpectedly show that long‐distance migrants are more sensitive to local environmental conditions, which may help them to adapt to ongoing changes in climate. [ABSTRACT FROM AUTHOR]

Increasing temperatures and winter precipitation can influence the carbon (C) exchange rates in arctic ecosystems. Feedbacks can be both positive and negative, but the net effects are unclear and expected to vary strongly across the Arctic. There is a lack of understanding of the combined effects of increased summer warming and winter precipitation on the C balance in these ecosystems. Here we assess the short‐term (1–3 years) and long‐term (5–8 years) effects of increased snow depth (snow fences) (on average + 70 cm) and warming (open top chambers; 1–3°C increase) and the combination in a factorial design on all key components of the daytime carbon dioxide (CO2) fluxes in a wide‐spread heath tundra ecosystem in West Greenland. The warming treatment increased ecosystem respiration (ER) on a short‐ and long‐term basis, while gross ecosystem photosynthesis (GEP) was only increased in the long term. Despite the difference in the timing of responses of ER and GEP to the warming treatment, the net ecosystem exchange (NEE) of CO2 was unaffected in the short term and in the long term. Although the structural equation model (SEM) indicates a direct relationship between seasonal accumulated snow depth and ER and GEP, there were no significant effects of the snow addition treatment on ER or GEP measured over the summer period. The combination of warming and snow addition turned the plots into net daytime CO2 sources during the growing season. Interestingly, despite no significant changes in air temperature during the snow‐free time during the experiment, control plots as well as warming plots revealed significantly higher ER and GEP in the long term compared to the short term. This was in line with the satellite‐derived time‐integrated normalized difference vegetation index of the study area, suggesting that more factors than air temperature are drivers for changes in arctic tundra ecosystems. [ABSTRACT FROM AUTHOR]

Climate change is contributing to declines of insects through rising temperatures, altered precipitation patterns, and an increasing frequency of extreme events. The impacts of both gradual and sudden shifts in weather patterns are realized directly on insect physiology and indirectly through impacts on other trophic levels. Here, we investigated direct effects of seasonal weather on butterfly occurrences and indirect effects mediated by plant productivity using a temporally intensive butterfly monitoring dataset, in combination with high‐resolution climate data and a remotely sensed indicator of plant primary productivity. Specifically, we used Bayesian hierarchical path analysis to quantify relationships between weather and weather‐driven plant productivity on the occurrence of 94 butterfly species from three localities distributed across an elevational gradient. We found that snow pack exerted a strong direct positive effect on butterfly occurrence and that low snow pack was the primary driver of reductions during drought. Additionally, we found that plant primary productivity had a consistently negative effect on butterfly occurrence. These results highlight mechanisms of weather‐driven declines in insect populations and the nuances of climate change effects involving snow melt, which have implications for ecological theories linking topographic complexity to ecological resilience in montane systems. [ABSTRACT FROM AUTHOR]

Located at northern latitudes and subject to large seasonal temperature fluctuations, boreal forests are sensitive to the changing climate, with evidence for both increasing and decreasing productivity, depending upon conditions. Optical remote sensing of vegetation indices based on spectral reflectance offers a means of monitoring vegetation photosynthetic activity and provides a powerful tool for observing how boreal forests respond to changing environmental conditions. Reflectance‐based remotely sensed optical signals at northern latitude or high‐altitude regions are readily confounded by snow coverage, hampering applications of satellite‐based vegetation indices in tracking vegetation productivity at large scales. Unraveling the effects of snow can be challenging from satellite data, particularly when validation data are lacking. In this study, we established an experimental system in Alberta, Canada including six boreal tree species, both evergreen and deciduous, to evaluate the confounding effects of snow on three vegetation indices: the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), and the chlorophyll/carotenoid index (CCI), all used in tracking vegetation productivity for boreal forests. Our results revealed substantial impacts of snow on canopy reflectance and vegetation indices, expressed as increased albedo, decreased NDVI values and increased PRI and CCI values. These effects varied among species and functional groups (evergreen and deciduous) and different vegetation indices were affected differently, indicating contradictory, confounding effects of snow on these indices. In addition to snow effects, we evaluated the contribution of deciduous trees to vegetation indices in mixed stands of evergreen and deciduous species, which contribute to the observed relationship between greenness‐based indices and ecosystem productivity of many evergreen‐dominated forests that contain a deciduous component. Our results demonstrate confounding and interacting effects of snow and vegetation type on vegetation indices and illustrate the importance of explicitly considering snow effects in any global‐scale photosynthesis monitoring efforts using remotely sensed vegetation indices. [ABSTRACT FROM AUTHOR]

Over the past several decades, various trends in vegetation productivity, from increases to decreases, have been observed throughout Arctic–Boreal ecosystems. While some of this variation can be explained by recent climate warming and increased disturbance, very little is known about the impacts of permafrost thaw on productivity across diverse vegetation communities. Active layer thickness data from 135 permafrost monitoring sites along a 10° latitudinal transect of the Northwest Territories, Canada, paired with a Landsat time series of normalized difference vegetation index from 1984 to 2019, were used to quantify the impacts of changing permafrost conditions on vegetation productivity. We found that active layer thickness contributed to the observed variation in vegetation productivity in recent decades in the northwestern Arctic–Boreal, with the highest rates of greening occurring at sites where the near‐surface permafrost recently had thawed. However, the greening associated with permafrost thaw was not sustained after prolonged periods of thaw and appeared to diminish after the thaw front extended outside the plants' rooting zone. Highest rates of greening were found at the mid‐transect sites, between 62.4° N and 65.2° N, suggesting that more southernly sites may have already surpassed the period of beneficial permafrost thaw, while more northern sites may have yet to reach a level of thaw that supports enhanced vegetation productivity. These results indicate that the response of vegetation productivity to permafrost thaw is highly dependent on the extent of active layer thickening and that increases in productivity may not continue in the coming decades. [ABSTRACT FROM AUTHOR]

Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late‐successional forests have prompted efforts to restore old‐growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old‐growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old‐growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old‐growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches. [ABSTRACT FROM AUTHOR]

The peak growth of plant in summer is an important indicator of the capacity of terrestrial ecosystem productivity, and ongoing studies have shown its responses to climate warming as represented in the mean temperature. However, the impacts from the asymmetrical warming, that is, different rates in the changes of daytime (Tmax) and nighttime (Tmin) warming were mostly ignored. Using 60 flux sites (674 site‐year in total) measurements and satellite observations from two independent satellite platforms (Global Inventory Monitoring and Modeling Studies [1982–2015]; MODIS [2000–2020]) over the Northern Hemisphere (≥30°N), here we show that the peak growth, as represented by both flux‐based maximum primary productivity and the maximum greenness indices (maximum normalized difference vegetation index and enhanced vegetation index), responded oppositely to daytime and nighttime warming. Tmax−Tmin+ (peak growth showed negative responses to Tmax, but positive responses to Tmin) dominated in most ecosystems and climate types, especially in water‐limited ecosystems, while Tmax+Tmin− (peak growth showed positive responses to Tmax, but negative responses to Tmin) was primarily observed in high latitude regions. These contrasting responses could be explained by the strong association between asymmetric warming and water conditions, including soil moisture, evapotranspiration/potential evapotranspiration, and the vapor pressure deficit. Our results are therefore important to the understanding of the responses of peak growth to climate change, and consequently a better representation of asymmetrical warming in future ecosystem models by differentiating the contributions between daytime and nighttime warming. [ABSTRACT FROM AUTHOR]

Episodes of forest mortality have been observed worldwide associated with climate change, impacting species composition and ecosystem services such as water resources and carbon sequestration. Yet our ability to predict forest mortality remains limited, especially across large scales. Time series of satellite imagery has been used to document ecosystem resilience globally, but it is not clear how well remotely sensed resilience can inform the prediction of forest mortality across continental, multi-biome scales. Here, we leverage forest inventories across the continental United States to systematically assess the potential of ecosystem resilience derived using different data sets and methods to predict forest mortality. We found high resilience was associated with low mortality in eastern forests but was associated with high mortality in western regions. The unexpected resilience–mortality relation in western United States may be due to several factors including plant trait acclimation, insect population dynamics, or resource competition. Overall, our results not only supported the opportunity to use remotely sensed ecosystem resilience to predict forest mortality but also highlighted that ecological factors may have crucial influences because they can reverse the sign of the resilience–mortality relationships. [ABSTRACT FROM AUTHOR]

Phenological mismatch is often cited as a putative driver of population declines in long‐distance migratory birds. The mechanisms and cues utilized to advance breeding ground arrival will impact the adaptability of species to further warming. Furthermore, timing of post‐breeding migration potentially faces diverging selective pressures, with earlier onset of tropical dry seasons favouring migration advancement, while longer growing seasons in temperate areas could facilitate delayed departures. Despite this, few studies exist of migration phenology on the non‐breeding grounds or on post‐breeding passage. Here, we use first arrival and last departure dates of 20 species of trans‐Saharan migratory birds from tropical non‐breeding grounds (The Gambia), between 1964 and 2019. Additionally, we use first arrival and last departure dates, as well as median arrival and departure dates, at an entry/departure site to/from Europe (Gibraltar), between 1991 and 2018. We assess phenological trends in pre‐ and post‐breeding migration, as well as individual species' durations of stay in breeding and non‐breeding areas. Furthermore, we assess the extent to which inter‐annual variation in these timings may be explained by meteorological and ecological variables. We find significant advances in pre‐breeding migration at both locations, while post‐breeding migration is delayed. At Gibraltar, these trends do not differ between first/last and median dates of migration. The combination of these trends suggests substantial changes in the temporal usage of the two continents by migratory birds. Duration of stay (of species, not individuals) within Europe increased by 16 days, on average, over the 27‐year monitoring period. By contrast, duration of species' stays on the non‐breeding range declined by 63 days, on average, over the 56‐year monitoring period. Taken together these changes suggest substantial, previously unreported alterations to annual routines in Afro‐Palaearctic migrants. [ABSTRACT FROM AUTHOR]

The long‐term increase in satellite‐based proxies of vegetation cover is a well‐documented response of seasonally snow‐covered ecosystems to climate warming. However, observed greening trends are far from uniform, and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on above‐treeline ecosystems in the European Alps. NDVI changes in these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We observed widespread greening for the 2000–2020 period, a pattern that is consistent with the overall increase in summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north‐facing slopes between 1900 and 2400 m. Using high‐resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snow melt and green‐up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water‐related habitat amelioration above treeline. [ABSTRACT FROM AUTHOR]

The temporal trend of aboveground net primary production (ANPP) is frequently used to estimate the effect of humans on ecosystems. In water‐limited ecosystems, like most grazing areas in the world, the effect of humans act upon ANPP in combination with environmental variations. Our main objective was to quantify long‐term (1981–2012) changes of ANPP and discriminate the causes of these changes between environmental and human at a subcontinental scale, across vast areas of Patagonia. We estimated ANPP through a radiative model based on remote sensing data. Then, we evaluated the relation between ANPP and environmental interannual variations of two hierarchically related factors: El Niño Southern Oscillation (ENSO) through the Southern Oscillation Index (SOI), and precipitation. We described the effect of humans through the shape of the temporal trends of the residuals (RESTREND) of the environmental model and quantified human relative impact through the RESTREND: ANPP trend ratio. ANPP interannual variation was significantly explained by ENSO (through SOI) and precipitation in 65% of the study area. The SOI had a positive association with annual precipitation. The association between ANPP and annual precipitation was positive. RESTREND analysis was statistically significant in 92% of the area where the tested environmental model worked, representing 60% of the study area, and it was mostly negative. However, its magnitude, revealed through the RESTREND: ANPP trend ratio, was relatively mild. Our analysis revealed that most of ANPP trends were associated with climate and that even when human density is low, its incidence seems to be mainly negative. [ABSTRACT FROM AUTHOR]

Time series of vegetation indices derived from satellite imagery are useful in measuring vegetation response to climate warming in remote northern regions. These indices show that productivity is generally declining in the boreal forest, but it is unclear which components of boreal vegetation are driving these trends. We aimed to compare trends in the normalized difference vegetation index (NDVI) to forest growth and demographic data taken from a 10 ha mapped plot located in a spruce‐dominated boreal peatland. We used microcores to quantify recent growth trends and tree census data to characterize mortality and recruitment rates of the three dominant tree species. We then compared spatial patterns in growth and demography to patterns in Landsat‐derived maximum NDVI trends (1984–2019) in 78 pixels that fell within the plot. We found that NDVI trends were predominantly positive (i.e., "greening") in spite of the ongoing loss of black spruce (the dominant species; 80% of stems) from the plot. The magnitude of these trends correlated positively with black spruce growth trends, but was also governed to a large extent by tree mortality and recruitment. Greening trends were weaker (lower slope) in areas with high larch mortality, and high turnover of spruce and birch, but stronger (higher slope) in areas with high larch recruitment. Larch dominance is currently low (~11% of stems), but it is increasing in abundance as permafrost thaw progresses and will likely have a substantial influence on future NDVI trends. Our results emphasize that NDVI trends in boreal peatlands can be positive even when the forest as a whole is in decline, and that the magnitude of trends can be strongly influenced by the demographics of uncommon species. [ABSTRACT FROM AUTHOR]

Species conservation in a rapidly changing world requires an improved understanding of how individuals and populations respond to changes in their environment across temporal scales. Increased warming in the Arctic puts this region at particular risk for rapid environmental change, with potentially devastating impacts on resident populations. Here, we make use of a parameterized full life cycle, individual‐based energy budget model for wild muskoxen, coupling year‐round environmental data with detailed ontogenic metabolic physiology. We show how winter food accessibility, summer food availability, and density dependence drive seasonal dynamics of energy storage and thus life history and population dynamics. Winter forage accessibility defined by snow depth, more than summer forage availability, was the primary determinant of muskox population dynamics through impacts on calf recruitment and longer term carryover effects of maternal investment. Simulations of various seasonal snow depth and plant biomass and quality profiles revealed that timing of and improved/limited winter forage accessibility had marked influence on calf recruitment (±10–80%). Impacts on recruitment were the cumulative result of condition‐driven reproductive performance at multiple time points across the reproductive period (ovulation to calf weaning) as a trade‐off between survival and reproduction. Seasonal and generational condition effects of snow‐rich winters interacted with age structure and density to cause pronounced long‐term consequences on population growth and structure, with predicted population recovery times from even moderate disturbances of 10 years or more. Our results show how alteration in winter forage accessibility, mediated by snow depth, impacts the dynamics of northern herbivore populations. Further, we present here a mechanistic and state‐based model framework to assess future scenarios of environmental change, such as increased or decreased snowfall or plant biomass and quality to impact winter and summer forage availability across the Arctic. [ABSTRACT FROM AUTHOR]

Tundra dominates two‐thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community‐specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil. [ABSTRACT FROM AUTHOR]

A widespread increase in forest cover is underway in northern Mediterranean forests because of land abandonment and decreased wood demand, but the resilience of these successional forests to climate change remains unresolved. Here we use 18‐year time series of canopy greenness derived from satellite imagery (NDVI) to evaluate the impacts of climate change on Spain's forests. Specifically, we analyzed how NDVI was influenced by the climatic water balance (i.e. Standardized Precipitation‐Evapotranspiration Index, SPEI), using monthly time‐series extracted from 3,100 pixels of forest, categorized into ten forest types. The forests increased in leaf area index by 0.01 per year on average (from 1.7 in 2000 to 1.9 in 2017) but there was enormous variation among years related to climatic water balance. Forest types varied in response to drought events: those dominated by drought‐avoiding species showed strong covariance between greenness and SPEI, while those dominated by drought‐tolerant species showed weak covariance. Native forests usually recovered more than 80% of greenness within the 18 months and the remainder within 5 years, but plantations of Eucalyptus were less resilient. Management to increase the resilience of forests—a key goal of forestry in the Mediterranean region—appears to have had a positive effect: canopy greenness within protected forests was more resilient to drought than within non‐protected forests. In conclusion, many of Spain's successional forests have been resilient to drought over the past 18 years, from the perspective of space. Future studies will need to combine remote sensing with field‐based analyses of physiological tolerances and mortality processes to understand how Mediterranean forests will respond to the rapid climate change predicted for this region in the coming decades. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long‐term atmospheric CO2 concentration measurements at the Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO2 concentrations (ΔCO2) is estimated from the difference of CO2 concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO2 of −4.75 ppm per decade (p <.05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process‐based terrestrial model and inverse model simulations estimate that regional terrestrial carbon uptake increases by up to 18.9 and 8.0 Tg C for the study period, accounting for 13.4% and 5.7% of the average annual domestic carbon emissions, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO2 trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO2 measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible. [ABSTRACT FROM AUTHOR]

In recent decades, many forest die‐off events have been reported in relation to climate‐change‐induced episodes, such as droughts and heat waves. To understand how these extreme climatic events induce forest die‐off, it is important to find a tool to standardize the climatic conditions experienced by different populations during a specific climatic event, taking into account the historic climatic conditions of the site where these populations live (bioclimatic niche). In this study, we used estimates of climatic suitability calculated from species distribution models (SDMs) for such purpose. We studied forest die‐off across France during the 2003 heatwave that affected Western Europe, using 2,943 forest inventory plots dominated by 14 single tree species. Die‐off severity was estimated by Normalized Difference Vegetation Index (NDVI) loss using Moderate‐resolution Imaging Spectroradiometer remote sensor imagery. Climatic suitability at the local level during the historical 1979–2002 period (HCS), the episode time (2003; ECS) and suitability deviance during the historical period (HCS‐SD) were calculated for each species by means of boosted regression tree models using the CHELSA climate database and occurrences extracted from European forest inventories. Low HCS‐SD and high mean annual temperature explained the overall regional pattern of vulnerability to die‐off across different monospecific forests. The combination of high historical and low episode climatic suitability also contributed significantly to overall forest die‐off. Furthermore, we observed different species‐specific relationships between die‐off vulnerability and climatic suitability: Sub‐Mediterranean and Mediterranean species tended to be vulnerable in historically more suitable localities (high HCS), whereas Euro‐Siberian species presented greater vulnerability when the hot drought episode was more intense. We demonstrated that at regional scale, past climatic legacy plays an important role in explaining NDVI loss during the episode. Moreover, we demonstrated that SDMs‐derived indexes, such as HCS, ECS and HCS‐SD, could constitute a tool for standardizing the ways that populations and species experience climatic variability across time and space. [ABSTRACT FROM AUTHOR]

The mountain systems of the Hindu Kush Himalaya (HKH) are changing rapidly due to climatic change, but an overlooked component is the subnival ecosystem (between the treeline and snow line), characterized by short‐stature plants and seasonal snow. Basic information about subnival vegetation distribution and rates of ecosystem change are not known, yet such information is needed to understand relationships between subnival ecology and water/carbon cycles. We show that HKH subnival ecosystems cover five to 15 times the area of permanent glaciers and snow, highlighting their eco‐hydrological importance. Using satellite data from the Landsat 5, 7 and 8 missions, we measured change in the spatial extent of subnival vegetation from 1993 to 2018. The Landsat surface reflectance‐derived Normalized Difference Vegetation Index product was thresholded at 0.1 to indicate the presence/absence of vegetation. Using this product, the strength and direction of time‐series trends in the green pixel fraction were measured within three regions of interest. We controlled for cloud cover, snow cover and evaluated the impact of sensor radiometric differences between Landsat 7 and Landsat 8. Using Google Earth Engine to expedite data processing tasks, we show that there has been a weakly positive increase in the extent of subnival vegetation since 1993. Strongest and most significant trends were found in the height region of 5,000–5,500 m a.s.l. across the HKH extent: R2 =.302, Kendall's τ = 0.424, p <.05, but this varied regionally, with height, and according to the sensors included in the time series. Positive trends at lower elevations occurred on steeper slopes whilst at higher elevations, flatter areas exhibited stronger trends. We validated our findings using online photographs. Subnival ecological changes have likely impacted HKH carbon and water cycles with impacts on millions of people living downstream, but the strength and direction of impacts of vegetation expansion remain unknown. [ABSTRACT FROM AUTHOR]

Fire is a major disturbance in the boreal forest, and has been shown to release significant amounts of carbon (C) to the atmosphere through combustion. However, less is known about the effects on ecosystems following fire, which include reduced productivity and changes in decomposition in the decade immediately following the disturbance. In this study, we assessed the impact of fire on net primary productivity (NPP) in the North American boreal forest using a 17-year record of satellite NDVI observations at 8-km spatial resolution together with a light-use efficiency model. We identified 61 fire scars in the satellite observations using digitized fire burn perimeters from a database of large fires. We studied the postfire response of NPP by analyzing the most impacted pixel within each burned area. NPP decreased in the year following the fire by 60-260g CM-2 yr-1 (30-80%). By comparing pre- and postfire observations, we estimated a mean NPP recovery period for boreal forests of about 9 years, with substantial variability among fires. We incorporated this behavior into a carbon cycle model simulation to demonstrate these effects on net ecosystem production. The disturbance resulted in a release of C to the atmosphere during the first 8 years, followed by a small, but long-lived, sink lasting 150 years. Postfire net emissions were three times as large as from a model run without changing NPP. However, only small differences in the C cycle occurred between runs after 8 years due to the rapid recovery of NPP. We conclude by discussing the effects of fire on the long-term continental trends in satellite NDVI observed across boreal North America during the 1980s and 1990s.

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. Widespread changes in satellite‐observed NDVI values have been recorded across the arctic and boreal region in recent decades. In an effort to characterize these changes, we measured the response of NDVI to changes in community composition and leaf area in two types of boreal peatland ecosystems. We found strong relationships between NDVI and the percent cover of different plant functional types, in particular of shrubs. Our results support recent studies that have shown strong correlations between species cover, productivity, and NDVI in far northern ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: Climate and land‐use change are the major drivers of global biodiversity loss. Their effects are particularly acute for wide‐ranging consumers, but little is known about how these factors interact to affect the abundance of large carnivores and their herbivore prey. We analyzed population densities of a primary and secondary consumer (mule deer, Odocoileus hemionus, and mountain lion, Puma concolor) across a climatic gradient in western North America by combining satellite‐based maps of plant productivity with estimates of animal abundance and foraging area derived from Global Positioning Systems telemetry data (GPS). Mule deer density exhibited a positive, linear relationship with plant productivity (r2 = 0.58), varying by a factor of 18 across the climate‐vegetation gradient (range: 38–697 individuals/100 km2). Mountain lion home range size decreased in response to increasing primary productivity and consequent changes in the abundance of their herbivore prey (range: 20–450 km2). This pattern resulted in a strong, positive association between plant productivity and mountain lion density (r2 = 0.67). Despite varying densities, the ratio of prey to predator remained constant across the climatic gradient (mean ± SE = 363 ± 29 mule deer/mountain lion), suggesting that the determinacy of the effect of primary productivity on consumer density was conserved across trophic levels. As droughts and longer term climate changes reduce the suitability of marginal habitats, consumer home ranges will expand in order for individuals to meet basic nutritional requirements. These changes portend decreases in the abundance of large‐bodied, wide‐ranging wildlife through climatically driven reductions in carrying capacity, as well as increased human–wildlife interactions stemming from anthropogenic land use and habitat fragmentation. [ABSTRACT FROM AUTHOR]

Abstract: Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO2 growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index (NDVI), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant (p < 0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature (γint) and to precipitation (δint). γint is ~1% °C−1 more negative and δint is ~8% 100 mm−1 more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in γint can be explained by background moisture and temperature conditions. Positive γint occurred in wet season where mean temperature is lower than 27°C and precipitation is at least 60 mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity (GPP) estimates (empirical modeling by machine‐learning algorithm applied to flux tower measurements, and nine process‐based carbon cycle models) were examined for the GPP–climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of γint, while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis–climate relationship and thus the projection for impacts of climate change on tropical carbon cycle. [ABSTRACT FROM AUTHOR]

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

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems. [ABSTRACT FROM AUTHOR]

South Asia experienced a weakening of summer monsoon circulation in the past several decades, resulting in rainfall decline in wet regions. In comparison with other tropical ecosystems, quantitative assessments of the extent and triggers of vegetation change are lacking in assessing climate-change impacts over South Asia dominated by crops. Here, we use satellite-based Normalized Difference Vegetation Index ( NDVI) to quantify spatial-temporal changes in vegetation greenness, and find a widespread annual greening trend that stands in contrast to the weakening of summer monsoon circulation particularly over the last decade. We further show that moisture supply is the primary factor limiting vegetation activity during dry season or in dry region, and cloud cover or temperature would become increasingly important in wet region. Enhanced moisture conditions over dry region, coinciding with the decline in monsoon, are mainly responsible for the widespread greening trend. This result thereby cautions the use of a unified monsoon index to predict South Asia's vegetation dynamics. Current climate-carbon models in general correctly reproduce the dominant control of moisture in the temporal characteristics of vegetation productivity. But the model ensemble cannot exactly reproduce the spatial pattern of satellite-based vegetation change mainly because of biases in climate simulations. The moisture-induced greening over South Asia, which is likely to persist into the wetter future, has significant implications for regional carbon cycling and maintaining food security. [ABSTRACT FROM AUTHOR]

Episodes of forest mortality have been observed worldwide associated with climate change, impacting species composition and ecosystem services such as water resources and carbon sequestration. Yet our ability to predict forest mortality remains limited, especially across large scales. Time series of satellite imagery has been used to document ecosystem resilience globally, but it is not clear how well remotely sensed resilience can inform the prediction of forest mortality across continental, multi-biome scales. Here, we leverage forest inventories across the continental United States to systematically assess the potential of ecosystem resilience derived using different data sets and methods to predict forest mortality. We found high resilience was associated with low mortality in eastern forests but was associated with high mortality in western regions. The unexpected resilience-mortality relation in western United States may be due to several factors including plant trait acclimation, insect population dynamics, or resource competition. Overall, our results not only supported the opportunity to use remotely sensed ecosystem resilience to predict forest mortality but also highlighted that ecological factors may have crucial influences because they can reverse the sign of the resilience-mortality relationships., (© 2022 John Wiley & Sons Ltd.)

Despite the recognition that some species might quickly adapt to new conditions under climate change, demonstrating and predicting such a fundamental response is challenging. Morphological variations in response to climate may be caused by evolutionary changes or phenotypic plasticity, or both, but teasing apart these processes is difficult. Here, we built on the number of thoracic vertebrae ( NTV) in ectothermic vertebrates, a known genetically based feature, to establish a link with body size and evaluate how climate change might affect the future morphological response of this group of species. First, we show that in old-world salamanders, NTV variation is strongly related to changes in body size. Secondly, using 22 salamander species as a case study, we found support for relationships between the spatial variation in selected bioclimatic variables and NTV for most of species. For 44% of species, precipitation and aridity were the predominant drivers of geographical variation of the NTV. Temperature features were dominant for 31% of species, while for 19% temperature and precipitation played a comparable role. This two-step analysis demonstrates that ectothermic vertebrates may evolve in response to climate change by modifying the number of thoracic vertebrae. These findings allow to develop scenarios for potential morphological evolution under future climate change and to identify areas and species in which the most marked evolutionary responses are expected. Resistance to climate change estimated from species distribution models was positively related to present-day species morphological response, suggesting that the ability of morphological evolution may play a role for species' persistence under climate change. The possibility that present-day capacity for local adaptation might help the resistance response to climate change can be integrated into analyses of the impact of global changes and should also be considered when planning management actions favouring species persistence. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Cities are growing rapidly worldwide, yet a mechanistic understanding of the impact of urbanization on biodiversity is lacking. We assessed the impact of urbanization on arthropod diversity (species richness and evenness) and abundance in a study of six cities and nearby intensively managed agricultural areas. Within the urban ecosystem, we disentangled the relative importance of two key landscape factors affecting biodiversity, namely the amount of vegetated area and patch isolation. To do so, we a priori selected sites that independently varied in the amount of vegetated area in the surrounding landscape at the 500-m scale and patch isolation at the 100-m scale, and we hold local patch characteristics constant. As indicator groups, we used bugs, beetles, leafhoppers, and spiders. Compared to intensively managed agricultural ecosystems, urban ecosystems supported a higher abundance of most indicator groups, a higher number of bug species, and a lower evenness of bug and beetle species. Within cities, a high amount of vegetated area increased species richness and abundance of most arthropod groups, whereas evenness showed no clear pattern. Patch isolation played only a limited role in urban ecosystems, which contrasts findings from agro-ecological studies. Our results show that urban areas can harbor a similar arthropod diversity and abundance compared to intensively managed agricultural ecosystems. Further, negative consequences of urbanization on arthropod diversity can be mitigated by providing sufficient vegetated space in the urban area, while patch connectivity is less important in an urban context. This highlights the need for applying a landscape ecological approach to understand the mechanisms shaping urban biodiversity and underlines the potential of appropriate urban planning for mitigating biodiversity loss. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date ( DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models. [ABSTRACT FROM AUTHOR]

Global climate change is already having significant impacts on arctic and alpine ecosystems, and ongoing increases in temperature and altered precipitation patterns will affect the strong seasonal patterns that characterize these temperature-limited systems. The length of the potential growing season in these tundra environments is increasing due to warmer temperatures and earlier spring snow melt. Here, we compare current and projected climate and ecological data from 20 Northern Hemisphere sites to identify how seasonal changes in the physical environment due to climate change will alter the seasonality of arctic and alpine ecosystems. We find that although arctic and alpine ecosystems appear similar under historical climate conditions, climate change will lead to divergent responses, particularly in the spring and fall shoulder seasons. As seasonality changes in the Arctic, plants will advance the timing of spring phenological events, which could increase plant nutrient uptake, production, and ecosystem carbon (C) gain. In alpine regions, photoperiod will constrain spring plant phenology, limiting the extent to which the growing season can lengthen, especially if decreased water availability from earlier snow melt and warmer summer temperatures lead to earlier senescence. The result could be a shorter growing season with decreased production and increased nutrient loss. These contrasting alpine and arctic ecosystem responses will have cascading effects on ecosystems, affecting community structure, biotic interactions, and biogeochemistry. [ABSTRACT FROM AUTHOR]

The Mongolian Steppe is one of the largest remaining grassland ecosystems. Recent studies have reported widespread decline of vegetation across the steppe and about 70% of this ecosystem is now considered degraded. Among the scientific community there has been an active debate about whether the observed degradation is related to climate, or over-grazing, or both. Here, we employ a new atmospheric correction and cloud screening algorithm ( MAIAC) to investigate trends in satellite observed vegetation phenology. We relate these trends to changes in climate and domestic animal populations. A series of harmonic functions is fitted to Moderate Resolution Imaging Spectroradiometer ( MODIS) observed phenological curves to quantify seasonal and inter-annual changes in vegetation. Our results show a widespread decline (of about 12% on average) in MODIS observed normalized difference vegetation index ( NDVI) across the country but particularly in the transition zone between grassland and the Gobi desert, where recent decline was as much as 40% below the 2002 mean NDVI. While we found considerable regional differences in the causes of landscape degradation, about 80% of the decline in NDVI could be attributed to increase in livestock. Changes in precipitation were able to explain about 30% of degradation across the country as a whole but up to 50% in areas with denser vegetation cover ( P < 0.05). Temperature changes, while significant, played only a minor role ( r2 = 0.10, P < 0.05). Our results suggest that the cumulative effect of overgrazing is a primary contributor to the degradation of the Mongolian steppe and is at least partially responsible for desertification reported in previous studies. [ABSTRACT FROM AUTHOR]

Mountain plants are considered among the species most vulnerable to climate change, especially at high latitudes where there is little potential for poleward or uphill dispersal. Satellite monitoring can reveal spatiotemporal variation in vegetation activity, offering a largely unexploited potential for studying responses of montane ecosystems to temperature and predicting phenological shifts driven by climate change. Here, a novel remote-sensing phenology approach is developed that advances existing techniques by considering variation in vegetation activity across the whole year, rather than just focusing on event dates (e.g. start and end of season). Time series of two vegetation indices (VI), normalized difference VI ( NDVI) and enhanced VI (EVI) were obtained from the moderate resolution imaging spectroradiometer MODIS satellite for 2786 Scottish mountain summits (600-1344 m elevation) in the years 2000-2011. NDVI and EVI time series were temporally interpolated to derive values on the first day of each month, for comparison with gridded monthly temperatures from the preceding period. These were regressed against temperature in the previous months, elevation and their interaction, showing significant variation in temperature sensitivity between months. Warm years were associated with high NDVI and EVI in spring and summer, whereas there was little effect of temperature in autumn and a negative effect in winter. Elevation was shown to mediate phenological change via a magnification of temperature responses on the highest mountains. Together, these predict that climate change will drive substantial changes in mountain summit phenology, especially by advancing spring growth at high elevations. The phenological plasticity underlying these temperature responses may allow long-lived alpine plants to acclimate to warmer temperatures. Conversely, longer growing seasons may facilitate colonization and competitive exclusion by species currently restricted to lower elevations. In either case, these results show previously unreported seasonal and elevational variation in the temperature sensitivity of mountain vegetation activity. [ABSTRACT FROM AUTHOR]

Russia's boreal (taiga) biome will likely contract sharply and shift northward in response to 21st century climatic change, yet few studies have examined plant response to climatic variability along the northern margin. We quantified climate dynamics, trends in plant growth, and growth-climate relationships across the tundra shrublands and Cajander larch ( Larix cajanderi Mayr.) woodlands of the Kolyma river basin (657 000 km2) in northeastern Siberia using satellite-derived normalized difference vegetation indices ( NDVI), tree ring-width measurements, and climate data. Mean summer temperatures ( T s) increased 1.0 °C from 1938 to 2009, though there was no trend ( P > 0.05) in growing year precipitation or climate moisture index ( CMI gy). Mean summer NDVI ( NDVIs) increased significantly from 1982 to 2010 across 20% of the watershed, primarily in cold, shrub-dominated areas. NDVIs positively correlated ( P < 0.05) with T s across 56% of the watershed ( r = 0.52 ± 0.09, mean ± SD), principally in cold areas, and with CMI gy across 9% of the watershed ( r = 0.45 ± 0.06), largely in warm areas. Larch ring-width measurements from nine sites revealed that year-to-year (i.e., high-frequency) variation in growth positively correlated ( P < 0.05) with June temperature ( r = 0.40) and prior summer CMI ( r = 0.40) from 1938 to 2007. An unexplained multi-decadal (i.e., low-frequency) decline in annual basal area increment ( BAI) occurred following the mid-20th century, but over the NDVI record there was no trend in mean BAI ( P > 0.05), which significantly correlated with NDVIs ( r = 0.44, P < 0.05, 1982-2007). Both satellite and tree-ring analyses indicated that plant growth was constrained by both low temperatures and limited moisture availability and, furthermore, that warming enhanced growth. Impacts of future climatic change on forests near treeline in Arctic Russia will likely be influenced by shifts in both temperature and moisture, which implies that projections of future forest distribution and productivity in this area should take into account the interactions of energy and moisture limitations. [ABSTRACT FROM AUTHOR]

We combine satellite and ground observations during 1950-2011 to study the long-term links between multiple climate (air temperature and cryospheric dynamics) and vegetation (greenness and atmospheric CO2 concentrations) indicators of the growing season of northern ecosystems (>45°N) and their connection with the carbon cycle. During the last three decades, the thermal potential growing season has lengthened by about 10.5 days ( P < 0.01, 1982-2011), which is unprecedented in the context of the past 60 years. The overall lengthening has been stronger and more significant in Eurasia (12.6 days, P < 0.01) than North America (6.2 days, P > 0.05). The photosynthetic growing season has closely tracked the pace of warming and extension of the potential growing season in spring, but not in autumn when factors such as light and moisture limitation may constrain photosynthesis. The autumnal extension of the photosynthetic growing season since 1982 appears to be about half that of the thermal potential growing season, yielding a smaller lengthening of the photosynthetic growing season (6.7 days at the circumpolar scale, P < 0.01). Nevertheless, when integrated over the growing season, photosynthetic activity has closely followed the interannual variations and warming trend in cumulative growing season temperatures. This lengthening and intensification of the photosynthetic growing season, manifested principally over Eurasia rather than North America, is associated with a long-term increase (22.2% since 1972, P < 0.01) in the amplitude of the CO2 annual cycle at northern latitudes. The springtime extension of the photosynthetic and potential growing seasons has apparently stimulated earlier and stronger net CO2 uptake by northern ecosystems, while the autumnal extension is associated with an earlier net release of CO2 to the atmosphere. These contrasting responses may be critical in determining the impact of continued warming on northern terrestrial ecosystems and the carbon cycle. [ABSTRACT FROM AUTHOR]

Land cover changes may affect climate and the energy balance of the Earth through their influence on the greenhouse gas composition of the atmosphere (biogeochemical effects) but also through shifts in the physical properties of the land surface (biophysical effects). We explored how the radiation budget changes following the replacement of temperate dry forests by crops in central semiarid Argentina and quantified the biophysical radiative forcing of this transformation. For this purpose, we computed the albedo and surface temperature for a 7-year period (2003-2009) from MODIS imagery at 70 paired sites occupied by native forests and crops and calculated the radiation budget at the tropopause and surface levels using a columnar radiation model parameterized with satellite data. Mean annual black-sky albedo and diurnal surface temperature were 50% and 2.5 °C higher in croplands than in dry forests. These contrasts increased the outgoing shortwave energy flux at the top of the atmosphere in croplands by a quarter (58.4 vs. 45.9 W m−2) which, together with a slight increase in the outgoing longwave flux, yielded a net cooling of −14 W m−2. This biophysical cooling effect would be equivalent to a reduction in atmospheric CO2 of 22 Mg C ha−1, which involves approximately a quarter to a half of the typical carbon emissions that accompany deforestation in these ecosystems. We showed that the replacement of dry forests by crops in central Argentina has strong biophysical effects on the energy budget which could counterbalance the biogeochemical effects of deforestation. Underestimating or ignoring these biophysical consequences of land-use changes on climate will certainly curtail the effectiveness of many warming mitigation actions, particularly in semiarid regions where high radiation load and smaller active carbon pools would increase the relative importance of biophysical forcing. [ABSTRACT FROM AUTHOR]

Animal responses to global climate variation might be spatially inconsistent. This may arise from spatial variation in factors limiting populations' growth or from differences in the links between global climate patterns and ecologically relevant local climate variation. For example, the North Atlantic Oscillation ( NAO) has a spatially consistent relation to temperature, but inconsistent spatial relation to snow depth in Scandinavia. Furthermore, there are multiple mechanistic ways by which climate may limit animal populations, involving both direct effects through thermoregulation and indirect pathways through trophic interactions. It is conceptually appealing to directly model the predicted mechanistic links. This includes the use of climate variables mimicking such interactions, for example, to use growing degree days ( GDD) as a proxy for plant growth rather than average monthly temperature. Using a unique database of autumn body mass of 83331 domestic lambs from the period 1992-2007 in four alpine ranges in Norway, we demonstrate the utility of hierarchical, mechanistic path models fitted using a Bayesian approach to analyse explicitly predicted relationships among environmental variables and between lamb body mass and the environmental variables. We found large spatial variation in strength of responses of autumn lamb body mass to the NAO, to a proxy for plant growth in spring (the Normalized Difference Vegetation Index, NDVI) and effects even differed in direction to local summer climate. Average local temperature outperformed GDD as a predictor of the NDVI, whereas the NAO index in two areas outperformed local weather variables as a predictor of lamb body mass, despite the weaker mechanistic link. Our study highlights that spatial variation in strength of herbivore responses may arise from several processes. Furthermore, mechanistically more appealing measures do not always increase predictive power due to scale of measurement and since global measures may provide more relevant 'weather packages' for larger scales. [ABSTRACT FROM AUTHOR]

A shift in the magnitude and timing of animal migrations is one of the most documented ecological effects of climate change. Although migrations are largely driven by spatial variation in resource gradients, few studies connect expected changes in primary production with geographic patterns in migratory behavior. Here, we link lake primary production to the occurrence of sea migrations in the partially anadromous salmonid Arctic char ( Salvelinus alpinus L.). We compiled presence/absence records of anadromous char populations spanning productivity and temperature gradients along the Norwegian coast. The probability of anadromy decreased with increasing migration distance, maximum slope of the migration route and lake productivity. There was a significant interaction between lake productivity and migration distance. The negative effect of longer migration distances was more severe in lakes with higher productivity, indicating reduced relative profitability of migration with increased feeding opportunities in freshwater. Lake productivity was mainly driven by terrestrial primary production in the catchment. We predicted future distributions of anadromous char given downscaled temperature and precipitation changes projected by two different emission scenarios and global climate models ( GCMs). Projected increases in temperature and precipitation in 2071-2100 increased terrestrial primary production and, compared to the control scenario (1961-1990), decreased the range of anadromous populations. The prevalence of anadromy decreased by 53% in the HadAm3H GCM with the A2 emission scenario, 61% in HadAm3H with the B2 scenario and 22% in ECHAM4 with the B2 scenario. Cross-ecosystem studies (e.g., terrestrial to freshwater) are critical for understanding ecological impacts of climate change. In this case, climate-driven increases in terrestrial primary production are expected to increase primary production in lakes and ultimately reduce the prevalence of anadromy in Arctic char populations. [ABSTRACT FROM AUTHOR]

Riverine transport of organic carbon (OC) to the ocean is a significant component in the global carbon (C) cycle and the concentration of total organic carbon (TOC) in rivers and lakes is vital for ecosystem properties and water quality for human use. By use of a large dataset comprising chemical variables and detailed catchment information in ∼1000 Norwegian pristine lakes covering a wide climatic range, we were able to predict TOC concentrations with high accuracy. We further predict, using a 'space-for-time' approach and a downscaled, moderate, climate change scenario, that northern, boreal regions likely will experience strong increases in OC export from catchments to surface waters. Median concentrations of OC in these lakes will increase by 65%, from the current median of 2.0-3.3 mg C L. This is a long-term effect, primarily mediated by increased terrestrial vegetation cover in response to climate change. This increase OC will have severe impacts on food-webs, productivity and human use. Given the robustness of the estimates and the general applicability of the parameters, we suggest that these findings would be relevant to boreal areas in general. [ABSTRACT FROM AUTHOR]

Growth in arctic vegetation is generally expected to increase under a warming climate, particularly among deciduous shrubs. We analyzed annual ring growth for an abundant and nearly circumpolar erect willow ( Salix lanata L.) from the coastal zone of the northwest Russian Arctic (Nenets Autonomous Okrug). The resulting chronology is strongly related to summer temperature for the period 1942–2005. Remarkably high correlations occur at long distances (>1600 km) across the tundra and taiga zones of West Siberia and Eastern Europe. We also found a clear relationship with photosynthetic activity for upland vegetation at a regional scale for the period 1981–2005, confirming a parallel ‘greening’ trend reported for similarly warming North American portions of the tundra biome. The standardized growth curve suggests a significant increase in shrub willow growth over the last six decades. These findings are in line with field and remote sensing studies that have assigned a strong shrub component to the reported greening signal since the early 1980s. Furthermore, the growth trend agrees with qualitative observations by nomadic Nenets reindeer herders of recent increases in willow size in the region. The quality of the chronology as a climate proxy is exceptional. Given its wide geographic distribution and the ready preservation of wood in permafrost, S. lanata L. has great potential for extended temperature reconstructions in remote areas across the Arctic. [ABSTRACT FROM AUTHOR]

Forest inventories from the intact rainforests of the Amazon indicate increasing rates of carbon gain over the past three decades. However, such estimates have been questioned because of the poor spatial representation of the sampling plots and the incomplete understanding of purported mechanisms behind the increases in biomass. Ecosystem models, when used in conjunction with satellite data, are useful in examining the carbon budgets in regions where the observations of carbon flows are sparse. The purpose of this study is to explain observed trends in normalized difference vegetation index (NDVI) using climate observations and ecosystem models of varying complexity in the western Amazon basin for the period of 1984–2002. We first investigated trends in NDVI and found a positive trend during the study period, but the positive trend in NDVI was observed only in the months from August to December. Then, trends in various climate parameters were calculated, and of the climate variables considered, only shortwave radiation was found to have a corresponding significant positive trend. To compare the impact of each climate component, as well as increasing carbon dioxide (CO2) concentrations, on evergreen forests in the Amazon, we ran three ecosystem models (CASA, Biome-BGC, and LPJ), and calculated monthly net primary production by changing a climate component selected from the available climate datasets. As expected, CO2 fertilization effects showed positive trends throughout the year and cannot explain the positive trend in NDVI, which was observed only for the months of August to December. Through these simulations, we demonstrated that the positive trend in shortwave radiation can explain the positive trend in NDVI observed for the period from August to December. We conclude that the positive trend in shortwave radiation is the most likely driver of the increasing trend in NDVI and the corresponding observed increases in forest biomass. [ABSTRACT FROM AUTHOR]

There are multiple paths via which environmental variation can impact herbivore ecology and this makes the identification of drivers challenging. Researchers have used diverse approaches to describe the association between environmental variation and ecology, including local weather, large-scale patterns of climate, and satellite imagery reflecting plant productivity and phenology. However, it is unclear to what extent it is possible to find a single measure that captures climatic effects over broad spatial scales. There may, in fact, be no a priori reason to expect populations of the same species living in different areas to respond in the same way to climate as their population may experience limiting factors at different times of the year, and the forms of regulation may differ among populations. Here, we examine whether the same environmental indices [seasonal Real Bioclimatic Index (RBI), seasonal Normalized Difference Vegetation Index (NDVI) and winter North Atlantic Oscillation (NAO)] influence body size in different populations of a large ungulate living in Mediterranean Spain, Western Scotland and Norway. We found substantial differences in the pattern of weight change over time in adult female red deer among study areas as well as different environmental drivers associated with variation in weight. The lack of general patterns for a given species at a continental scale suggest that detailed knowledge regarding the way climate affects local populations is often necessary to successfully predict climate impact. We caution against extrapolation of results from localized climate–population studies to broad spatial scales. [ABSTRACT FROM AUTHOR]

Increase in rainfall variability has important consequences for organisms in arid and semiarid regions around the world. In South American and Australian deserts, the El Niño/Southern Oscillation (ENSO) phenomenon greatly influences rainfall patterns, and therefore the dynamics of plant communities. However, the field data needed to assess the effect of climate change on vegetational patterns is difficult to obtain because of the large spatial scale required for such studies. Normalized Difference Vegetation Index (NDVI) characteristics allow the use of several indexes related to vegetational structure. Due to its direct relationship with primary productivity, it is possible to obtain several measures of annual productivity. These include annual plant yield, annual maximum yield, onset of ‘greening-up’ and senescence phases, length of the ‘green’ season, vegetation peak, and therefore, the periods when more or less food is available for herbivores. After verification with ground-truth measures, we used NDVI data from two semiarid localities in north-central Chile (Fray Jorge and Aucó) to determine the relationship between rainfall patterns and vegetation cover and productivity related to El Niño phenomenon. With this information we gauge the influence of climatic processes on primary productivity in western South America, an area subject to strong climate variability. We predict significant variation in Chilean semiarid regions due to climate change, affecting mainly the extent and timing of annual growth season of vegetation, and also including a shorter and delayed greening-up season. Also, we predict that important decreases in rainfall levels will not have strong effects on primary production in these semiarid ecosystems. [ABSTRACT FROM AUTHOR]

Using Advanced Very High Resolution Radiometer data spanning 1981–2006 and calibrated for long-term analyses of vegetation dynamics, we examine whether vegetation cover has increased across Australia and whether there has been a differential response of vegetation functional types in response to changes in climatic growing conditions. Trends in vegetation cover are interpreted within Budyko's energy – water limitation framework. Results from an Australia-wide analysis indicate that vegetation cover (as described by the fraction of Photosynthetically Active Radiation absorbed by vegetation; fPAR) has increased, on average, by 0.0007 per year – an increase of ∼8% over the 26 years. The majority of this change is due to a 0.0010 per year increase in persistent fPAR (representing nondeciduous perennial vegetation types; up 21%). In contrast, recurrent fPAR (representing deciduous, annual and ephemeral vegetation types) decreased, on average, by 0.0003 per year (down 7%), the trends of which are highly seasonal. Over the same period, Australian average annual precipitation increased by 1.3 mm yr−2 (up 7%). A site-based analysis using 90 long-term meteorological stations with minimal localized land-cover changes showed that energy-limited sites where total fPAR increased generally experienced decreases in precipitation, and water-limited sites that experienced decreases in cover were almost always associated with decreases in precipitation. Interestingly, where vegetation cover increased at water-limited sites, precipitation trends were variable indicating that this is not the only factor driving vegetation response. As Australia is a generally highly water-limited environment, these findings indicate that the effective availability of water to plants has increased on average over the study period. Results also show that persistent vegetation types have benefited more than recurrent types from recent changes in growing conditions. Regardless of what has been driving these changes, the overall response of vegetation over the past 2–3 decades has resulted in an observable greening of the driest inhabited continent on Earth. [ABSTRACT FROM AUTHOR]

Wildfires have major effects on forest dynamics, succession and the carbon cycle in the boreal biome. They are a significant source of carbon emissions, and current observed changes in wildfire regimes due to changes in climate could affect the balance of the boreal carbon pool. A better understanding of postwildfire vegetation dynamics in boreal forests will help predict the future role of boreal forests as a carbon sink or source. Time series of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Shortwave Infrared Index (NDSWIR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite were used to investigate whether characteristic temporal patterns exist for stands of different ages in the Siberian boreal forests and whether their postwildfire dynamics are influenced by variables such as prewildfire vegetation cover. Two types of forests, evergreen needle-leaf (ENF) and deciduous needle-leaf (DNF), were studied by analysing a sample of 78 burned forest areas. In order to study a longer time frame, a chronosequence of burned areas of different ages was built by coupling information on location and age provided by a forest burned area database (from 1992 to 2003) to MODIS NDVI and NDSWIR time series acquired from 2001 to 2005. For each of the burned areas, an adjacent unburned control plot representing the same forest type was selected, with the aim of separating the interannual variations caused by climate from changes in NDVI and NDSWIR behaviour due to a wildfire. The results suggest that it takes more than 13 years for the temporal NDVI and NDSWIR signal to recover fully after wildfire. NDSWIR, which is associated to canopy moisture, needs a longer recovery period than NDVI, which is associated to vegetation greenness. The results also suggest that variability observed in postwildfire NDVI and NDSWIR can be explained partially by the dominant forest type: while 13 years after a fire NDVI and NDSWIR are similar for ENF and DNF, the initial impact appears to be greater on the NDVI and NDSWIR of ENF, suggesting a faster recovery by ENF. [ABSTRACT FROM AUTHOR]