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  1. Abstract

    Earlier snowmelt, warmer temperatures and herbivory are among the factors that influence high-latitude tundra productivity near the town of Utqiaġvik in northern Alaska. However, our understanding of the potential interactions between these factors is limited. MODIS observations provide cover fractions of vegetation, snow, standing water, and soil, and fractional absorption of photosynthetically active radiation by canopy chlorophyll (fAPARchl) per pixel. Here, we evaluated a recent time-period (2001–2014) that the tundra experienced large interannual variability in vegetation productivity metrics (i.e. fAPARchland APARchl), which was explainable by both abiotic and biotic factors. We found earlier snowmelt to increase soil and vegetation cover, and productivity in June, while warmer temperatures significantly increased monthly productivity. However, abiotic factors failed to explain stark decreases in productivity during August of 2008, which coincided with a severe lemming outbreak. MODIS observations found this tundra ecosystem to completely recover two years later, resulting in elevated productivity. This study highlights the potential roles of both climate and herbivory in modulating the interannual variability of remotely retrieved plant productivity metrics in Arctic coastal tundra ecosystems.

  2. Geostationary satellite reveals the asymmetrical impact of heatwaves on plant diurnal photosynthesis at the continental scale.
    Free, publicly-accessible full text available August 4, 2024
  3. Free, publicly-accessible full text available September 1, 2024
  4. Free, publicly-accessible full text available August 1, 2024
  5. Abstract

    Understanding the controlling mechanisms of soil properties on ecosystem productivity is essential for sustaining productivity and increasing resilience under a changing climate. Here we investigate the control of topsoil depth (e.g., A horizons) on long‐term ecosystem productivity. We used nationwide observations (n = 2401) of topsoil depth and multiple scaled datasets of gross primary productivity (GPP) for five ecosystems (cropland, forest, grassland, pasture, shrubland) over 36 years (1986–2021) across the conterminous USA. The relationship between topsoil depth and GPP is primarily associated with water availability, which is particularly significant in arid regions under grassland, shrubland, and cropland (r = .37, .32, .15, respectively,p < .0001). For every 10 cm increase in topsoil depth, the GPP increased by 114 to 128 g C m−2 year−1in arid regions (r = .33 and .45,p < .0001). Paired comparison of relatively shallow and deep topsoils while holding other variables (climate, vegetation, parent material, soil type) constant showed that the positive control of topsoil depth on GPP occurred primarily in cropland (0.73, confidence interval of 0.57–0.84) and shrubland (0.75, confidence interval of 0.40–0.94). The GPP difference between deep and shallow topsoils was small and not statistically significant. Despite the positive control of topsoil depth on productivity in arid regions, its contribution (coefficients: .09–.33) was similar to that of heat (coefficients:more ».06–.39) but less than that of water (coefficients: .07–.87). The resilience of ecosystem productivity to climate extremes varied in different ecosystems and climatic regions. Deeper topsoils increased stability and decreased the variability of GPP under climate extremes in most ecosystems, especially in shrubland and grassland. The conservation of topsoil in arid regions and improvements of soil depth representation and moisture‐retention mechanisms are critical for carbon‐sequestration ecosystem services under a changing climate. These findings and relationships should also be included in Earth system models.

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  6. Abstract Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m −2  yr −1 forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m −2  yr −1 , respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency,more »thereby improving projections of land-based climate mitigation potentials.« less
    Free, publicly-accessible full text available December 1, 2023
  7. Free, publicly-accessible full text available November 1, 2023