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291.
David M. Bell Matthew J. Gregory Van Kane Jonathan Kane Robert E. Kennedy Heather M. Roberts Zhiqiang Yang 《Carbon balance and management》2018,13(1):15
Background
Satellite-based aboveground forest biomass maps commonly form the basis of forest biomass and carbon stock mapping and monitoring, but biomass maps likely vary in performance by region and as a function of spatial scale of aggregation. Assessing such variability is not possible with spatially-sparse vegetation plot networks. In the current study, our objective was to determine whether high-resolution lidar-based and moderate-resolution Landsat-base aboveground live forest biomass maps converged on similar predictions at stand- to landscape-levels (10 s to 100 s ha) and whether such differences depended on biophysical setting. Specifically, we examined deviations between lidar- and Landsat-based biomass mapping methods across scales and ecoregions using a measure of error (normalized root mean square deviation), a measure of the unsystematic deviations, or noise (Pearson correlation coefficient), and two measures related to systematic deviations, or biases (intercept and slope of a regression between the two sets of predictions).Results
Compared to forest inventory data (0.81-ha aggregate-level), lidar and Landsat-based mean biomass predictions exhibited similar performance, though lidar predictions exhibited less normalized root mean square deviation than Landsat when compared with the reference plot data. Across aggregate-levels, the intercepts and slopes of regression equations describing the relationships between lidar- and Landsat-based biomass predictions stabilized (i.e., little additional change with increasing area of aggregates) at aggregate-levels between 10 and 100 ha, suggesting a consistent relationship between the two maps at landscape-scales. Differences between lidar- and Landsat-based biomass maps varied as a function of forest canopy heterogeneity and composition, with systematic deviations (regression intercepts) increasing with mean canopy cover and hardwood proportion within forests and correlations decreasing with hardwood proportion.Conclusions
Deviations between lidar- and Landsat-based maps indicated that satellite-based approaches may represent general gradients in forest biomass. Ecoregion impacted deviations between lidar and Landsat biomass maps, highlighting the importance of biophysical setting in determining biomass map performance across aggregate scales. Therefore, regardless of the source of remote sensing (e.g., Landsat vs. lidar), factors affecting the measurement and prediction of forest biomass, such as species composition, need to be taken into account whether one is estimating biomass at the plot, stand, or landscape scale.292.
Rapid weathering and erosion rates in mountainous tropical watersheds lead to highly variable soil and saprolite thicknesses which in turn impact nutrient fluxes and biological populations. In the Luquillo Mountains of Puerto Rico, a 5-m thick saprolite contains high microorganism densities at the surface and at depth overlying bedrock. We test the hypotheses that the organisms at depth are limited by the availability of two nutrients, P and Fe. Many tropical soils are P-limited, rather than N-limited, and dissolution of apatite is the dominant source of P. We document patterns of apatite weathering and of bioavailable Fe derived from the weathering of primary minerals hornblende and biotite in cores augered to 7.5 m on a ridgetop as compared to spheroidally weathering bedrock sampled in a nearby roadcut.Iron isotopic compositions of 0.5 N HCl extracts of soil and saprolite range from about δ56Fe = 0 to ? 0.1‰ throughout the saprolite except at the surface and at 5 m depth where δ56Fe = ? 0.26 to ? 0.64‰. The enrichment of light isotopes in HCl-extractable Fe in the soil and at the saprolite–bedrock interface is consistent with active Fe cycling and consistent with the locations of high cell densities and Fe(II)-oxidizing bacteria, identified previously. To evaluate the potential P-limitation of Fe-cycling bacteria in the profile, solid-state concentrations of P were measured as a function of depth in the soil, saprolite, and weathering bedrock. Weathering apatite crystals were examined in thin sections and an apatite dissolution rate of 6.8 × 10? 14 mol m? 2 s? 1 was calculated. While surface communities depend on recycled nutrients and atmospheric inputs, deep communities survive primarily on nutrients released by the weathering bedrock and thus are tightly coupled to processes related to saprolite formation including mineral weathering. While low available P may limit microbial activity within the middle saprolite, fluxes of P from apatite weathering should be sufficient to support robust growth of microorganisms in the deep saprolite. 相似文献
293.