| 1. |
- Duncanson, Laura, et al.
(författare)
-
Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission
- 2022
-
Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 270
-
Tidskriftsartikel (refereegranskat)abstract
- NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
|
|
| 2. |
- Medina-Vega, José A., et al.
(författare)
-
Tropical tree ectomycorrhiza are distributed independently of soil nutrients
- 2024
-
Ingår i: Nature Ecology and Evolution. - 2397-334X. ; 8, s. 400-410
-
Tidskriftsartikel (refereegranskat)abstract
- Mycorrhizae, a form of plant–fungal symbioses, mediate vegetation impacts on ecosystem functioning. Climatic effects on decomposition and soil quality are suggested to drive mycorrhizal distributions, with arbuscular mycorrhizal plants prevailing in low-latitude/high-soil-quality areas and ectomycorrhizal (EcM) plants in high-latitude/low-soil-quality areas. However, these generalizations, based on coarse-resolution data, obscure finer-scale variations and result in high uncertainties in the predicted distributions of mycorrhizal types and their drivers. Using data from 31 lowland tropical forests, both at a coarse scale (mean-plot-level data) and fine scale (20 × 20 metres from a subset of 16 sites), we demonstrate that the distribution and abundance of EcM-associated trees are independent of soil quality. Resource exchange differences among mycorrhizal partners, stemming from diverse evolutionary origins of mycorrhizal fungi, may decouple soil fertility from the advantage provided by mycorrhizal associations. Additionally, distinct historical biogeographies and diversification patterns have led to differences in forest composition and nutrient-acquisition strategies across three major tropical regions. Notably, Africa and Asia’s lowland tropical forests have abundant EcM trees, whereas they are relatively scarce in lowland neotropical forests. A greater understanding of the functional biology of mycorrhizal symbiosis is required, especially in the lowland tropics, to overcome biases from assuming similarity to temperate and boreal regions.
|
|
