A unified vegetation index for quantifying the terrestrial biosphere.

Empirical vegetation indices derived from spectral reflectance data are widely used in remote sensing of the biosphere, as they represent robust proxies for canopy structure, leaf pigment content, and, subsequently, plant photosynthetic potential. Here, we generalize the broad family of commonly used vegetation indices by exploiting all higher-order relations between the spectral channels involved. This results in a higher sensitivity to vegetation biophysical and physiological parameters. The presented nonlinear generalization of the celebrated normalized difference vegetation index (NDVI) consistently improves accuracy in monitoring key parameters, such as leaf area index, gross primary productivity, and sun-induced chlorophyll fluorescence. Results suggest that the statistical approach maximally exploits the spectral information and addresses long-standing problems in satellite Earth Observation of the terrestrial biosphere. The nonlinear NDVI will allow more accurate measures of terrestrial carbon source/sink dynamics and potentials for stabilizing atmospheric CO2 and mitigating global climate change.

Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud.

Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implement a bias-aware Kalman filter method in the Google Earth Engine (GEE) platform to obtain fused images at the Landsat spatial-resolution. The added bias correction in the Kalman filter estimates accounts for the fact that both model and observation errors are temporally auto-correlated and may have a non-zero mean. This approach also enables reliable estimation of the uncertainty associated with the final reflectance estimates, allowing for error propagation analyses in higher level remote sensing products. Quantitative and qualitative evaluations of the generated products through comparison with other state-of-the-art methods confirm the validity of the approach, and open the door to operational applications at enhanced spatio-temporal resolutions at broad continental scales.

Future global productivity will be affected by plant trait response to climate.

Plant traits are both responsive to local climate and strong predictors of primary productivity. We hypothesized that future climate change might promote a shift in global plant traits resulting in changes in Gross Primary Productivity (GPP). We characterized the relationship between key plant traits, namely Specific Leaf Area (SLA), height, and seed mass, and local climate and primary productivity. We found that by 2070, tropical and arid ecosystems will be more suitable for plants with relatively lower canopy height, SLA and seed mass, while far northern latitudes will favor woody and taller plants than at present. Using a network of tower eddy covariance CO2 flux measurements and the extrapolated plant trait maps, we estimated the global distribution of annual GPP under current and projected future plant community distribution. We predict that annual GPP in northern biomes (≥45 °N) will increase by 31% (+8.1 ± 0.5 Pg C), but this will be offset by a 17.9% GPP decline in the tropics (-11.8 ± 0.84 Pg C). These findings suggest that regional climate changes will affect plant trait distributions, which may in turn affect global productivity patterns.

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling.

Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO-EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models.

Vegetation Greening and Climate Change Promote Multidecadal Rises of Global Land Evapotranspiration.

Recent studies showed that anomalous dry conditions and limited moisture supply roughly between 1998 and 2008, especially in the Southern Hemisphere, led to reduced vegetation productivity and ceased growth in land evapotranspiration (ET). However, natural variability of Earth's climate system can degrade capabilities for identifying climate trends. Here we produced a long-term (1982-2013) remote sensing based land ET record and investigated multidecadal changes in global ET and underlying causes. The ET record shows a significant upward global trend of 0.88 mm yr(-2) (P < 0.001) over the 32-year period, mainly driven by vegetation greening (0.018% per year; P < 0.001) and rising atmosphere moisture demand (0.75 mm yr(-2); P = 0.016). Our results indicate that reduced ET growth between 1998 and 2008 was an episodic phenomenon, with subsequent recovery of the ET growth rate after 2008. Terrestrial precipitation also shows a positive trend of 0.66 mm yr(-2) (P = 0.08) over the same period consistent with expected water cycle intensification, but this trend is lower than coincident increases in evaporative demand and ET, implying a possibility of cumulative water supply constraint to ET. Continuation of these trends will likely exacerbate regional drought-induced disturbances, especially during regional dry climate phases associated with strong El Niño events.

Suitable Days for Plant Growth Disappear under Projected Climate Change: Potential Human and Biotic Vulnerability.

Ongoing climate change can alter conditions for plant growth, in turn affecting ecological and social systems. While there have been considerable advances in understanding the physical aspects of climate change, comprehensive analyses integrating climate, biological, and social sciences are less common. Here we use climate projections under alternative mitigation scenarios to show how changes in environmental variables that limit plant growth could impact ecosystems and people. We show that although the global mean number of days above freezing will increase by up to 7% by 2100 under "business as usual" (representative concentration pathway [RCP] 8.5), suitable growing days will actually decrease globally by up to 11% when other climatic variables that limit plant growth are considered (i.e., temperature, water availability, and solar radiation). Areas in Russia, China, and Canada are projected to gain suitable plant growing days, but the rest of the world will experience losses. Notably, tropical areas could lose up to 200 suitable plant growing days per year. These changes will impact most of the world's terrestrial ecosystems, potentially triggering climate feedbacks. Human populations will also be affected, with up to ~2,100 million of the poorest people in the world (~30% of the world's population) highly vulnerable to changes in the supply of plant-related goods and services. These impacts will be spatially variable, indicating regions where adaptations will be necessary. Changes in suitable plant growing days are projected to be less severe under strong and moderate mitigation scenarios (i.e., RCP 2.6 and RCP 4.5), underscoring the importance of reducing emissions to avoid such disproportionate impacts on ecosystems and people.

Exposure of U.S. National Parks to land use and climate change 1900-2100.

Many protected areas may not be adequately safeguarding biodiversity from human activities on surrounding lands and global change. The magnitude of such change agents and the sensitivity of ecosystems to these agents vary among protected areas. Thus, there is a need to assess vulnerability across networks of protected areas to determine those most at risk and to lay the basis for developing effective adaptation strategies. We conducted an assessment of exposure of U.S. National Parks to climate and land use change and consequences for vegetation communities. We first defined park protected-area centered ecosystems (PACEs) based on ecological principles. We then drew on existing land use, invasive species, climate, and biome data sets and models to quantify exposure of PACEs from 1900 through 2100. Most PACEs experienced substantial change over the 20th century (> 740% average increase in housing density since 1940, 13% of vascular plants are presently nonnative, temperature increase of 1 degree C/100 yr since 1895 in 80% of PACEs), and projections suggest that many of these trends will continue at similar or increasingly greater rates (255% increase in housing density by 2100, temperature increase of 2.5 degrees-4.5 degrees C/100 yr, 30% of PACE areas may lose their current biomes by 2030). In the coming century, housing densities are projected to increase in PACEs at about 82% of the rate of since 1940. The rate of climate warming in the coming century is projected to be 2.5-5.8 times higher than that measured in the past century. Underlying these averages, exposure of individual park PACEs to change agents differ in important ways. For example, parks such as Great Smoky Mountains exhibit high land use and low climate exposure, others such as Great Sand Dunes exhibit low land use and high climate exposure, and a few such as Point Reyes exhibit high exposure on both axes. The cumulative and synergistic effects of such changes in land use, invasives, and climate are expected to dramatically impact ecosystem function and biodiversity in national parks. These results are foundational to developing effective adaptation strategies and suggest policies to better safeguard parks under broad-scale environmental change.

Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle.

The land and ocean act as a sink for fossil-fuel emissions, thereby slowing the rise of atmospheric carbon dioxide concentrations. Although the uptake of carbon by oceanic and terrestrial processes has kept pace with accelerating carbon dioxide emissions until now, atmospheric carbon dioxide concentrations exhibit a large variability on interannual timescales, considered to be driven primarily by terrestrial ecosystem processes dominated by tropical rainforests. We use a terrestrial biogeochemical model, atmospheric carbon dioxide inversion and global carbon budget accounting methods to investigate the evolution of the terrestrial carbon sink over the past 30 years, with a focus on the underlying mechanisms responsible for the exceptionally large land carbon sink reported in 2011 (ref. 2). Here we show that our three terrestrial carbon sink estimates are in good agreement and support the finding of a 2011 record land carbon sink. Surprisingly, we find that the global carbon sink anomaly was driven by growth of semi-arid vegetation in the Southern Hemisphere, with almost 60 per cent of carbon uptake attributed to Australian ecosystems, where prevalent La Niña conditions caused up to six consecutive seasons of increased precipitation. In addition, since 1981, a six per cent expansion of vegetation cover over Australia was associated with a fourfold increase in the sensitivity of continental net carbon uptake to precipitation. Our findings suggest that the higher turnover rates of carbon pools in semi-arid biomes are an increasingly important driver of global carbon cycle inter-annual variability and that tropical rainforests may become less relevant drivers in the future. More research is needed to identify to what extent the carbon stocks accumulated during wet years are vulnerable to rapid decomposition or loss through fire in subsequent years.

Patterns of new versus recycled primary production in the terrestrial biosphere.

Nitrogen (N) and phosphorus (P) availability regulate plant productivity throughout the terrestrial biosphere, influencing the patterns and magnitude of net primary production (NPP) by land plants both now and into the future. These nutrients enter ecosystems via geologic and atmospheric pathways and are recycled to varying degrees through the plant-soil-microbe system via organic matter decay processes. However, the proportion of global NPP that can be attributed to new nutrient inputs versus recycled nutrients is unresolved, as are the large-scale patterns of variation across terrestrial ecosystems. Here, we combined satellite imagery, biogeochemical modeling, and empirical observations to identify previously unrecognized patterns of new versus recycled nutrient (N and P) productivity on land. Our analysis points to tropical forests as a hotspot of new NPP fueled by new N (accounting for 45% of total new NPP globally), much higher than previous estimates from temperate and high-latitude regions. The large fraction of tropical forest NPP resulting from new N is driven by the high capacity for N fixation, although this varies considerably within this diverse biome; N deposition explains a much smaller proportion of new NPP. By contrast, the contribution of new N to primary productivity is lower outside the tropics, and worldwide, new P inputs are uniformly low relative to plant demands. These results imply that new N inputs have the greatest capacity to fuel additional NPP by terrestrial plants, whereas low P availability may ultimately constrain NPP across much of the terrestrial biosphere.

Bioenergy potential of the United States constrained by satellite observations of existing productivity.

United States (U.S.) energy policy includes an expectation that bioenergy will be a substantial future energy source. In particular, the Energy Independence and Security Act of 2007 (EISA) aims to increase annual U.S. biofuel (secondary bioenergy) production by more than 3-fold, from 40 to 136 billion liters ethanol, which implies an even larger increase in biomass demand (primary energy), from roughly 2.9 to 7.4 EJ yr(-1). However, our understanding of many of the factors used to establish such energy targets is far from complete, introducing significgant uncertainty into the feasibility of current estimates of bioenergy potential. Here, we utilized satellite-derived net primary productivity (NPP) data-measured for every 1 km(2) of the 7.2 million km(2) of vegetated land in the conterminous U.S.-to estimate primary bioenergy potential (PBP). Our results indicate that PBP of the conterminous U.S. ranges from roughly 5.9 to 22.2 EJ yr(-1), depending on land use. The low end of this range represents the potential when harvesting residues only, while the high end would require an annual biomass harvest over an area more than three times current U.S. agricultural extent. While EISA energy targets are theoretically achievable, we show that meeting these targets utilizing current technology would require either an 80% displacement of current crop harvest or the conversion of 60% of rangeland productivity. Accordingly, realistically constrained estimates of bioenergy potential are critical for effective incorporation of bioenergy into the national energy portfolio.

Drought-induced reduction in global terrestrial net primary production from 2000 through 2009.

Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production.

Simulations show decreasing carbon stocks and potential for carbon emissions in Rocky Mountain forests over the next century.

Climate change has altered the environment in which forests grow, and climate change models predict more severe alterations to come. Forests have already responded to these changes, and the future temperature and precipitation scenarios are of foremost concern, especially in the mountainous western United States, where forests occur in the dry environments that interface with grasslands. The objective of this study was to understand the trade-offs between temperature and water controls on these forested sites in the context of available climate projections. Three temperature and precipitation scenarios from IPCC AR4 AOGCMs ranging in precipitation levels were input to the process model Biome-BGC for key forested sites in the northern U.S. Rocky Mountains. Despite the omission of natural and human-caused disturbances in our simulations, our results show consequential effects from these conservative future temperature and precipitation scenarios. According to these projections, if future precipitation and temperatures are similar to or drier than the dry scenario depicted here, high-elevation forests on both the drier and wetter sites, which have in the absence of disturbance accumulated carbon, will reduce their carbon accumulation. Under the marginally drier climate projections, most forests became carbon sources by the end of the simulation horizon (2089). Under all three scenarios, growing season lengthened, the number of days with snow on the ground decreased, peak snow occurred earlier, and water stress increased through the projection horizon (1950-2089) for all sites, which represent the temperature and precipitation spectrum of forests in this region. The quantity, form, and timing of precipitation ultimately drive the carbon accumulation trajectory of forests in this region.

A new satellite-based methodology for continental-scale disturbance detection.

The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance.

Large seasonal swings in leaf area of Amazon rainforests.

Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation-atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of approximately 25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.

Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration.

We used a terrestrial ecosystem process model, BIOME-BGC, to investigate historical climate change and fire disturbance effects on regional carbon and water budgets within a 357,500 km(2) portion of the Canadian boreal forest. Historical patterns of increasing atmospheric CO2, climate change, and regional fire activity were used as model drivers to evaluate the relative effects of these impacts to spatial patterns and temporal trends in forest net primary production (NPP) and evapotranspiration (ET). Historical trends of increasing atmospheric CO2 resulted in overall 13% and 5% increases in annual NPP and ET from 1994 to 1996, respectively. NPP was found to be relatively sensitive to changes in air temperature (T(a)), while ET was more sensitive to precipitation (P) change within the ranges of observed climate variability (e.g., +/-2 degrees C for T(a) and +/-20% for P). In addition, the potential effect of climate change related warming on NPP is exacerbated or offset depending on whether these changes are accompanied by respective decreases or increases in precipitation. Historical fire activity generally resulted in reductions of both NPP and ET, which consumed an average of approximately 6% of annual NPP from 1959 to 1996. Areas currently occupied by dry conifer forests were found to be subject to more frequent fire activity, which consumed approximately 8% of annual NPP. The results of this study show that the North American boreal ecosystem is sensitive to historical patterns of increasing atmospheric CO2, climate change and regional fire activity. The relative impacts of these disturbances on NPP and ET interact in complex ways and are spatially variable depending on regional land cover and climate gradients.

Mapping and modeling the biogeochemical cycling of turf grasses in the United States.

Turf grasses are ubiquitous in the urban landscape of the United States and are often associated with various types of environmental impacts, especially on water resources, yet there have been limited efforts to quantify their total surface and ecosystem functioning, such as their total impact on the continental water budget and potential net ecosystem exchange (NEE). In this study, relating turf grass area to an estimate of fractional impervious surface area, it was calculated that potentially 163,800 km2 (+/- 35,850 km2) of land are cultivated with turf grasses in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC ecosystem process model, the growth of warm-season and cool-season turf grasses was modeled at a number of sites across the 48 conterminous states under different management scenarios, simulating potential carbon and water fluxes as if the entire turf surface was to be managed like a well-maintained lawn. The results indicate that well-watered and fertilized turf grasses act as a carbon sink. The potential NEE that could derive from the total surface potentially under turf (up to 17 Tg C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per person per day, depending on the modeled water irrigation practices, suggesting that outdoor water conservation practices such as xeriscaping and irrigation with recycled waste-water may need to be extended as many municipalities continue to face increasing pressures on freshwater.