Terrestrial Primary Production Research Articles

Evaluating the dynamics of grassland net primary productivity in response to climate change in China

Net primary productivity (NPP) has been considered as a direct indicator to access the terrestrial primary production. However, considerable uncertainties remain toward the response mechanism of NPP to climate change across annual and seasonal scales, especially for grassland ecosystems. In this study, the spatiotemporal dynamics of grassland NPP and its prominent climate-controlling factor were evaluated based on the CASA model and ground-based meteorological data across annual and seasonal scales in China from 1982 to 2016. Results showed that the annual mean grassland NPP was 294.58 gC·m−2·a−1 over the 35 years; the largest annual mean NPP was observed in Alpine sub-alpine meadow (235.72 ± 13.21 gC·m−2·a−1), while the smallest annual mean NPP value occurred in Desert grassland (97.27 ± 9.64 gC·m−2·a−1). Moreover, the multiyear mean grassland NPP showed a decreasing trend from the southeast to the northwest spatially. Temporally, grassland NPP exhibited a significant increasing trend (slope = 2.4 gC·m−2·a−1; p < 0.0001) over the whole study period; an abrupt change point across the grassland NPP time series was observed in 1999. Specially, 66.34% of the grassland area showed an increasing trend in NPP, and the areas with a significant increasing trend were concentrated in Qinghai-Tibet Plateau and the northern area of Xinjiang. Further climate factor analysis with NPP indicated that NPP positively correlated with precipitation and negatively correlated with temperature for the whole grassland area. In particular, the temperature was a dominant driver in NPP variations for Alpine sub-alpine meadow, Slope grassland and Alpine sub-alpine grassland, while precipitation controlled the most in NPP variations for Plain grassland and Desert grassland. The accumulation of grassland NPP in spring and autumn benefits from the increase in temperature, and precipitation promoted the accumulated NPP in summer and winter.

Hydrogen isotope assimilation and discrimination in green turtles.

Although hydrogen isotopes (δ2H) are commonly used as tracers of animal movement, minimal research has investigated the use of δ2H as a proxy to quantify resource and habitat use. While carbon and nitrogen are ultimately derived from a single source (food), the proportion of hydrogen in consumer tissues originates from two distinct sources: body water and food. Before hydrogen isotopes can be effectively used as a resource and habitat tracer, we need estimates of (net) discrimination factors (Δ2HNet) that account for the physiologically mediated differences in the δ2H values of animal tissues relative to that of the food and water sources they use to synthesize tissues. Here, we estimated Δ2HNet in captive green turtles (Chelonia mydas) by measuring the δ2H values of tissues (epidermis and blood components) and dietary macromolecules collected in two controlled feeding experiments. Tissue δ2H and Δ2HNet values varied systematically among tissues, with epidermis having higher δ2H and Δ2HNet values than blood components, which mirrors patterns between keratinaceous tissues (feathers, hair) and blood in birds and mammals. Serum/plasma of adult female green turtles had significantly lower δ2H values compared with juveniles, likely due to increased lipid mobilization associated with reproduction. This is the first study to quantify Δ2HNet values in a marine ectotherm, and we anticipate that our results will further refine the use of δ2H analysis to better understand animal resource and habitat use in marine ecosystems, especially coastal areas fueled by a combination of marine (e.g. micro/macroalgae and seagrass) and terrestrial (e.g. mangroves) primary production.

Instrumentation sensitivities for tower-based solar-induced fluorescence measurements

Solar-induced chlorophyll fluorescence (SIF) has been widely cited as a proxy for photosynthesis and is being incorporated as a common input in terrestrial primary productivity models. Though satellite-based SIF products show close relationships with terrestrial gross primary productivity (GPP), there is wide variability in the magnitude of published SIF retrievals made at intermediate scales. In a meta-analysis of the tower-based and airborne SIF literature, we found that mean SIF retrievals from unstressed vegetation spanned a wide range, from 0.041 mW m−2 nm−1 sr−1 to 14.8 mW m−2 nm−1 sr−1, with a majority of values falling below 4 mW m−2 nm−1 sr−1. We compiled information on reported spectrometer calibration procedures, hardware characterizations, and associated corrections from these same papers, and found inconsistent reporting on if and how key calibration methodology was performed. In order to quantify the importance of such methodological differences on final SIF retrievals made at a proximal scale, we performed radiometric calibrations and corrections for electronic dark current, detector noise, atmospheric O2 absorbance, and cosine corrector effects on three field-deployed spectrometers. We found dramatic changes in SIF retrieval magnitude before and after applying calibrations and corrections, as well as significant differences between instrument performance in the field and expected performance based on laboratory characterizations. Based on these tests, and on a Monte Carlo simulation of uncertainty estimates associated with each of these corrections, it is likely that calibration methodologies and hardware characterizations explain some of the observed variability in published SIF retrievals. This wide range in baseline SIF retrieval methodologies and resultant magnitudes severely limit researchers' ability to synthesize and advance the utility of SIF in modeling GPP across scales. Further, variability in calibration and correction methodology may explain the weak SIF-GPP relationship across studies at tower scales.

Developmental and biophysical determinants of grass leaf size worldwide.

One of the most notable ecological trends-described more than 2,300years ago by Theophrastus-is the association of small leaves with dry and cold climates, which has recently been recognized for eudicotyledonous plants at a global scale1-3. For eudicotyledons, this pattern has been attributed to the fact that small leaves have a thinner boundary layer that helps to avoid extreme leaf temperatures4 and theirleaf development results in vein traits that improve water transport under cold or dry climates5,6. However, the global distribution of leaf size and its adaptive basis have not been tested in the grasses, which represent a diverse lineage that is distinct in leaf morphology and that contributes 33% of terrestrial primary productivity (including the bulk of crop production)7. Here we demonstrate that grasses have shorter and narrower leaves under colder and drier climates worldwide. We show that small grass leaves have thermal advantages and vein development that contrast with those of eudicotyledons, but that also explain the abundance of small leaves in cold and dry climates. The worldwide distribution of leaf size in grasses exemplifies how biophysical and developmental processes result in convergence across major lineages in adaptation to climate globally, and highlights the importance of leaf size and venation architecture for grass performance in past, present and future ecosystems.

Minimum levels of atmospheric oxygen from fossil tree roots imply new plant−oxygen feedback

The appearance and subsequent evolution of land plants is among the most important events in the earth system. Plant resulted in a change of earth surface albedo and the hydrological cycle, as well as increased rock weatherability thereby causing a persistent change in atmospheric CO2 and O2. Land plants are, however, themselves dependent on O2 for respiration and long‐term survival, something not considered in current geochemical models. In this perspective, we highlight two aspects of land plants’ dependency on O2 relevant for the geobiological community: (a) fossil root systems can be used as a proxy for minimum levels of past atmospheric O2 consistent with a given fossil root depth; and (b) by identifying a positive feedback mechanism involving atmospheric O2, root intensity, terrestrial primary production and organic carbon burial. As an example, we consider archaeopterid fossil root systems, resembling those of modern mature conifers. Our soil–plant model suggest that atmospheric O2 with 1 SD probably reached pressures of 18.2 ± 1.9 kPa and 16.8 ± 2.1 kPa by the Middle and Late Devonian, respectively, that is 86 ± 9% and 79 ± 10% of the present‐day 21.2 kPa.

Evolution of the structure and impact of Earth’s biosphere

Life on Earth has existed for over 3.5 billion years and has caused fundamental changes in Earth’s biogeochemistry. However, the timing and impact of major events in the evolution of the biosphere are hotly contested, owing partially to the inherent difficulty in studying events that occurred in deep time. In this Review, we discuss the evolving structure of Earth’s biosphere and major changes in its capacity to alter geochemical cycles. We describe evidence that oxygenic photosynthesis evolved relatively early, but contend that marine primary productivity was low, surface oxygen was scarce and marine anoxia was prevalent for the majority of Earth’s history. Anoxygenic phototrophs were likely a key part of the marine biosphere in these low-oxygen oceans, and nutrient uptake by these organisms was one factor limiting the extent of marine oxygenic photosynthesis. Moreover, there are potential issues with the commonly held idea that the diversification of eukaryotes fundamentally altered ocean nutrient cycling and transformed the marine biological pump. Furthermore, we argue that terrestrial primary productivity was a substantial mode of biological carbon fixation following the widespread emergence of continental land masses, even before the rise of land plants, impacting carbon cycling on a global scale.

Drivers of tropical soil invertebrate community composition and richness across tropical secondary forests using DNA metasystematics

Tropical forests are fundamental ecosystems, essential for providing terrestrial primary productivity, global nutrient cycling, and biodiversity. Despite their importance, tropical forests are currently threatened by deforestation and associated activities. Moreover, tropical regions are now mostly represented by secondary forest regrowth, with half of the remaining tropical forests as secondary forest. Soil invertebrates are an important component to the functioning and biodiversity of these soil ecosystems. However, it remains unclear how these past land-use activities and subsequent secondary forest developments have altered the soil invertebrate communities and any potential ecological consequences associated with this. DNA metabarcoding offers an effective approach to rapidly monitor soil invertebrate communities under different land-use practices and within secondary forests. In this study, we used DNA metabarcoding to detect community-based patterns of soil invertebrate composition across a primary forest, a 23-year-old secondary forest, and a 33-year-old secondary forest and the associated soil environmental drivers of the soil invertebrate community structure in the Maquenque National Wildlife Refuge of Costa Rica (MNWR). We also used a species contribution analysis (SIMPER) to determine which soil invertebrate groups may be an indication of these soils reaching a pre-disturbed state such as a primary forest. We found that the soil invertebrate community composition at class, order, family, and ESV level were mostly significantly different across that habitats. We also found that the primary forest had a greater richness of soil invertebrates compared to the 23-year-old and 33-year-old secondary forest. Moreover, a redundancy analysis indicated that soil moisture influenced soil invertebrate community structure and explained up to 22% of the total variation observed in the community composition across the habitats; whereas soil invertebrate richness was structured by soil microbial biomass carbon (C) (Cmic) and explained up to 52% of the invertebrate richness across the primary and secondary forests. Lastly, the SIMPER analysis revealed that Naididae, Entomobryidae, and Elateridae could be important indicators of soil and forest recuperation in the MNWR. This study adds to the increasing evidence that soil invertebrates are intimately linked with the soil microbial biomass carbon (Cmic) and that even after 33 years of natural regrowth of a forest, these land use activities can still have persisting effects on the overall composition and richness of the soil invertebrate communities.

Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States

The CONterminous United States (CONUS) presents a large range of climate conditions and biomes where terrestrial primary productivity and its inter-annual variability are controlled regionally by rainfall and/or temperature. Here, the response of ecosystem productivity to those climate variables was investigated across different biomes from 2010 to 2018 using three climate datasets of precipitation, air temperature or drought severity, combined with several proxies of ecosystem productivity: a remote sensing product of aboveground biomass, an net primary productivity (NPP) remote sensing product, an NPP model-based product and four gross primary productivity products. We used an asymmetry index (AI) where positive AI indicates a greater increase of ecosystem productivity in wet years compared to the decline in dry years, and negative AI indicates a greater decline of ecosystem productivity in dry years compared to the increase in wet years. We found consistent spatial patterns of AI across the CONUS for the different products, with negative asymmetries over the Great Plains and positive asymmetries over the southwestern CONUS. Shrubs and, to a lesser extent, evergreen forests show a persistent positive asymmetry, whilst (natural) grasslands appear to have transitioned from positive to negative anomalies during the last decade. The general tendency of dominant negative asymmetry response for ecosystem productivity across the CONUS appears to be influenced by the negative asymmetry of precipitation anomalies. AI was found to be a function of mean rainfall: more positive AIs were found in dry areas where plants are adapted to drought and take advantage of rainfall pulses, and more negative AIs were found in wet areas, with a threshold delineating the two regimes corresponding to a mean annual rainfall of 200-400mm/year.

Temporal Coherence Between Lake and Landscape Primary Productivity

Understanding the patterns and drivers of primary productivity is a major goal of ecology, but little is known about whether the primary productivities of different types of ecosystems—here, lakes and the landscapes in which they are embedded—fluctuate in related ways through time. Due to shared climatic variation and well-known connections between lake and terrestrial ecosystems, such as nutrient and resource subsidies, we hypothesized that interannual fluctuations in aquatic and terrestrial primary productivity indices could be coherent. We also expected that lake and watershed characteristics could modify the strength and nature of primary productivity relationships. We applied wavelet coherence analyses to time series of lake chlorophyll-a and satellite-derived NDVI to examine coherence between lakes and land, and used random forest regression and generalized additive models to evaluate why coherence varies among lakes. There can be substantial coherence between lake and terrestrial primary productivity, but the strength and phase (direction and time lag) of this relationship vary widely, and there were marked differences between short (2–4-year periods of oscillation) and long (> 4-year periods of oscillation) timescales. Across all timescales, variables associated with the connectedness of lakes to their watersheds were consistently the important explanatory variables of the strength and phase of coherence. The patterns observed in this study suggest the importance of cross-ecosystem flows, as opposed to shared climatic variation, in determining temporal coherence between lakes and the landscape.

Increasing impacts of extreme droughts on vegetation productivity under climate change

Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions. Terrestrial primary productivity will increase with CO2 fertilization, but water limitation will decrease this positive effect. Analyses of Earth system model projections show that extreme droughts will have a much stronger impact on future productivity than mild and moderate droughts.

Soil Warming Accelerates Biogeochemical Silica Cycling in a Temperate Forest.

Biological cycling of silica plays an important role in terrestrial primary production. Soil warming stemming from climate change can alter the cycling of elements, such as carbon and nitrogen, in forested ecosystems. However, the effects of soil warming on the biogeochemical cycle of silica in forested ecosystems remain unexplored. Here we examine long-term forest silica cycling under ambient and warmed conditions over a 15-year period of experimental soil warming at Harvard Forest (Petersham, MA). Specifically, we measured silica concentrations in organic and mineral soils, and in the foliage and litter of two dominant species (Acer rubrum and Quercus rubra), in a large (30 × 30 m) heated plot and an adjacent control plot (30 × 30 m). In 2016, we also examined effects of heating on dissolved silica in the soil solution, and conducted a litter decomposition experiment using four tree species (Acer rubrum, Quercus rubra, Betula lenta, Tsuga canadensis) to examine effects of warming on the release of biogenic silica (BSi) from plants to soils. We find that tree foliage maintained constant silica concentrations in the control and warmed plots, which, coupled with productivity enhancements under warming, led to an increase in total plant silica uptake. We also find that warming drove an acceleration in the release of silica from decaying litter in three of the four species we examined, and a substantial increase in the silica dissolved in soil solution. However, we observe no changes in soil BSi stocks with warming. Together, our data indicate that warming increases the magnitude of silica uptake by vegetation and accelerates the internal cycling of silica in in temperate forests, with possible, and yet unresolved, effects on the delivery of silica from terrestrial to marine systems.

Terrestrial contributions to Afrotropical aquatic food webs: The Congo River case.

Understanding the degree to which aquatic and terrestrial primary production fuel tropical aquatic food webs remains poorly understood, and quantifying the relative contributions of autochthonous and allochthonous inputs is methodologically challenging. Carbon and nitrogen stable isotope ratios (δ 13C, δ 15N) can provide valuable insights about contributions of terrestrial resources and trophic position, respectively, but this approach has caveats when applied in typical complex natural food webs.Here, we used a combination of C, N, and H (δ 2H) stable isotope measurements and Bayesian mixing models to estimate the contribution of terrestrial (allochthonous) and aquatic (autochthonous) inputs to fish and invertebrate communities in the Congo River (and some tributaries).Overall, our results show that we gained power to distinguish sources by using a multiple tracer approach and we were able to discriminate aquatic versus terrestrial sources (esp. including hydrogen isotopes). Fish δ 2H values were clearly correlated with their food preferences and revealed a high level of variation in the degree of allochthony in these tropical aquatic communities.At the community level, it is clear that terrestrial C3 plants are an important source fueling the Congo River food web. However, in order to better constrain source contribution in these complex environments will require more robust constraints on stable isotope values of algal and methane‐derived C sources.

Monitoring Spatial and Temporal Variabilities of Gross Primary Production Using MAIAC MODIS Data

Remotely sensed vegetation indices (RSVIs) can be used to efficiently estimate terrestrial primary productivity across space and time. Terrestrial productivity, however, has many facets (e.g., spatial and temporal variability, including seasonality, interannual variability, and trends), and different vegetation indices may not be equally good at predicting them. Their accuracy in monitoring productivity has been mostly tested in single-ecosystem studies, but their performance in different ecosystems distributed over large areas still needs to be fully explored. To fill this gap, we identified the facets of terrestrial gross primary production (GPP) that could be monitored using RSVIs. We compared the temporal and spatial patterns of four vegetation indices (NDVI, EVI, NIRV, and CCI), derived from the MODIS MAIAC data set and of GPP derived from data from 58 eddy-flux towers in eight ecosystems with different plant functional types (evergreen needle-leaved forest, evergreen broad-leaved forest, deciduous broad-leaved forest, mixed forest, open shrubland, grassland, cropland, and wetland) distributed throughout Europe, covering Mediterranean, temperate, and boreal regions. The RSVIs monitored temporal variability well in most of the ecosystem types, with grasslands and evergreen broad-leaved forests most strongly and weakly correlated with weekly and monthly RSVI data, respectively. The performance of the RSVIs monitoring temporal variability decreased sharply, however, when the seasonal component of the time series was removed, suggesting that the seasonal cycles of both the GPP and RSVI time series were the dominant drivers of their relationships. Removing winter values from the analyses did not affect the results. NDVI and CCI identified the spatial variability of average annual GPP, and all RSVIs identified GPP seasonality well. The RSVI estimates, however, could not estimate the interannual variability of GPP across sites or monitor the trends of GPP. Overall, our results indicate that RSVIs are suitable to track different facets of GPP variability at the local scale, therefore they are reliable sources of GPP monitoring at larger geographical scales.

Drought impacts on terrestrial primary production underestimated by satellite monitoring

Satellite retrievals of information about the Earth’s surface are widely used to monitor global terrestrial photosynthesis and primary production and to examine the ecological impacts of droughts. Methods for estimating photosynthesis from space commonly combine information on vegetation greenness, incoming radiation, temperature and atmospheric demand for water (vapour-pressure deficit), but do not account for the direct effects of low soil moisture. They instead rely on vapour-pressure deficit as a proxy for dryness, despite widespread evidence that soil moisture deficits have a direct impact on vegetation, independent of vapour-pressure deficit. Here, we use a globally distributed measurement network to assess the effect of soil moisture on photosynthesis, and identify a common bias in an ensemble of satellite-based estimates of photosynthesis that is governed by the magnitude of soil moisture effects on photosynthetic light-use efficiency. We develop methods to account for the influence of soil moisture and estimate that soil moisture effects reduce global annual photosynthesis by ~15%, increase interannual variability by more than 100% across 25% of the global vegetated land surface, and amplify the impacts of extreme events on primary production. These results demonstrate the importance of soil moisture effects for monitoring carbon-cycle variability and drought impacts on vegetation productivity from space. Soil moisture effects can substantially reduce photosynthesis and amplify the impacts of extreme events on primary production, potentially leading to biases in satellite-based estimates of photosynthesis, suggests an analysis of ground-based measurements.

A multiple hypothesis approach to explain species richness patterns in neotropical stream-dweller fish communities.

Several hypotheses are used to explain species richness patterns. Some of them (e.g. species-area, species-energy, environment-energy, water-energy, terrestrial primary productivity, environmental spatial heterogeneity, and climatic heterogeneity) are known to explain species richness patterns of terrestrial organisms, especially when they are combined. For aquatic organisms, however, it is unclear if these hypotheses can be useful to explain for these purposes. Therefore, we used a selection model approach to assess the predictive capacity of such hypotheses, and to determine which of them (combined or not) would be the most appropriate to explain the fish species distribution in small Brazilian streams. We perform the Akaike’s information criteria for models selections and the eigenvector analysis to control the special autocorrelation. The spatial structure was equal to 0.453, Moran’s I, and require 11 spatial filters. All models were significant and had adjustments ranging from 0.370 to 0.416 with strong spatial component (ranging from 0.226 to 0.369) and low adjustments for environmental data (ranging from 0.001 to 0.119) We obtained two groups of hypothesis are able to explain the richness pattern (1) water-energy, temporal productivity-heterogeneity (AIC = 4498.800) and (2) water-energy, temporal productivity-heterogeneity and area (AIC = 4500.400). We conclude that the fish richness patterns in small Brazilian streams are better explained by a combination of Water-Energy + Productivity + Temporal Heterogeneity hypotheses and not by just one.

Coupled effects of oil spill and hurricane on saltmarsh terrestrial arthropods

Terrestrial arthropods play an important role in saltmarsh ecosystems, mainly affecting the saltmarsh’s primary production as the main consumers of terrestrial primary production and decomposition. Some of these arthropods, including selected insects and spiders, can be used as ecological indicators of overall marsh environmental health, as they are differentially sensitive to ecological stressors, such as land loss, erosion, oil spills, and tropical storms. In the present study, we used terrestrial arthropods collected from seven (three lightly-oiled, four heavily-oiled) sites in Barataria Bay and from three unoiled reference sites in Delacroix, Louisiana, to determine the impacts of the distribution and re-distribution of Deepwater Horizon (DWH) oil on these saltmarsh ecosystems. A total of 9,476 and 12,256 insects were collected in 2013 and 2014, respectively. The results show that the terrestrial arthropods were negatively affected by the re-distribution of DWH oil by Hurricane Isaac in 2012, although the level of impacts varied among the arthropod groups. Moreover, the mean diversity index was higher (>1.5) in 2014 than in 2013 (<1.5) for all sites, suggesting a recovery trajectory of the saltmarsh arthropod population. The higher taxonomic richness observed in the reference sites compared to the oiled sites for both years also indicated long-term impacts of DWH oil to the saltmarsh arthropod community. Whereas a slow recovery of certain terrestrial arthropods was observed, long-term monitoring of arthropod communities would help better understand the recovery and succession of the marsh ecosystems.

Importance of Considered Organic Versus Inorganic Source of Carbon to Lakes for Calculating Net Effect on Landscape C Budgets

AbstractLakes and reservoirs transform, emit, and bury carbon that is exported from land and are thus significant components of terrestrial carbon budgets. Their significance is often assessed by integrating these water bodies into terrestrial primary production. However, the transfer of inorganic carbon (IC) is likely a sticking point for these integrations because IC is not part of net ecosystem production. Here we integrated carbon evasion and organic carbon (OC) burial in a lake in the context of inorganic and OC cycling in a karst catchment from a system perspective. The lake emitted carbon dioxide (CO2) and buried OC at rates of 1.0 ± 0.2 and 0.9 ± 0.2 g C m−2 a−1, respectively, approximately equaling 13% and 11% of catchment net ecosystem production, respectively. These proportions represent significant influences on terrestrial carbon budgets, given an organic origin. However, catchment carbon export is dominated by IC that is derived from carbonates dissolved by soil CO2. Lake CO2 evasion accounts for less than 0.1% of soil CO2 efflux, suggesting little potential in significantly altering terrestrial carbon budgets. This comparison indicates the significance of aquatic CO2 evasion, requiring an adjustment of terrestrial carbon budgets to recognize their dependence on carbon origins. The significance may be overstated if inorganic origin is ignored. Our study suggests that a careful reassessment of the significance of CO2 evasion and OC burial in freshwater ecosystems to local and global carbon budgets, with full consideration of their sources, is necessary and pressing.

Quantifying soil moisture impacts on light use efficiency across biomes

Summary Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology.Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness.This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub‐humid, semi‐arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly‐based drought indices. Counter to common assumptions, fLUE reductions are largest in drought‐deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought‐related assessments.

Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m

AbstractTerrestrial primary production is a fundamental ecological process and a crucial component in understanding the flow of energy through trophic levels. The global MODIS gross primary production (GPP) and net primary production (NPP) products (MOD17) are widely used for monitoring GPP and NPP at coarse resolutions across broad spatial extents. The coarse input datasets and global biome‐level parameters, however, are well‐known limitations to the applicability of the MOD17 product at finer scales. We addressed these limitations and created two improved products for the conterminous United States (CONUS) that capture the spatiotemporal variability in terrestrial production. The MOD17 algorithm was utilized with medium resolution land cover classifications and improved meteorological data specific to CONUS in order to produce: (a) Landsat derived 16‐day GPP and annual NPP at 30 m resolution from 1986 to 2016 (GPPL30 and NPPL30, respectively); and (b) MODIS derived 8‐day GPP and annual NPP at 250 m resolution from 2001 to 2016 (GPPM250 and NPPM250 respectively). Biome‐specific input parameters were optimized based on eddy covariance flux tower‐derived GPP data from the FLUXNET2015 database. We evaluated GPPL30 and GPPM250 products against the standard MODIS GPP product utilizing a select subset of representative flux tower sites, and found improvement across all land cover classes except croplands. We also found consistent interannual variability and trends across NPPL30, NPPM250, and the standard MODIS NPP product. We highlight the application potential of the production products, demonstrating their improved capacity for monitoring terrestrial production at higher levels of spatial detail across broad spatiotemporal scales.

Terrestrial primary productivity indicators for inclusion in the National Climate Indicators System

The National Climate Indicators System (NCIS) aims to provide a suite of systematically updated, easily interpretable, and policy relevant national metrics of key physical, ecological, and societal conditions. The NCIS will distill and communicate complex scientific information to a broad audience as part of sustained National Climate Assessments. The current NCIS has made significant strides in defining its scope, providing an initial suite of indicators, and outlining its future development goals. In line with the scope and aims of the NCIS, we present a set of terrestrial primary productivity indicators that are scientifically defensible, scalable, directly related to climate, nationally important, built on existing agency efforts, and linked to the conceptual framework of the NCIS. The Gross Primary Productivity (GPP) and Net Primary Productivity (NPP) indicators provide seasonal and annual metrics of the growth of all plant material across the contiguous U.S., Alaska, Hawaii, and Puerto Rico. The GPP and NPP products used to produce the indicators have become key carbon measurements of environmental health and ecosystem services, including food, fiber, and fuels supporting national economies, human sustainability, and quality of life. We demonstrate how the proposed GPP and NPP indicators are relevant across indicator system sector topics of Forests, Grassland/Rangelands/Pastures, Agriculture, Wildfire, and Seasonal Timing and Phenology, can be used in concert with existing proposed indicators, and will aid to filling current gaps in the NCIS.