Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ
| Autor: | Martín Durante, Jorge Gonzalo Nicolás Irisarri, Feng Gao, Rowan Gaffney, Justin D. Derner, Lauren M. Porensky, David J. Augustine |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
plant composition 010504 meteorology & atmospheric sciences NDVI RADIATION USE EFFICIENCY temporal ANPP Biomasa Ganadería Atmospheric sciences 010603 evolutionary biology 01 natural sciences SPATIAL Normalized Difference Vegetation Index LANDSAT Semiarid Zones Abundance (ecology) Sensores Sensores Remotos Ecosystem Biomass lcsh:Science 0105 earth and related environmental sciences Zona Semiárida Biomass (ecology) radiation use efficiency biomass Sensors Primary production Regression analysis spatial MODIS Producción Animal y Lechería Biomasa sobre el Suelo PLANT COMPOSITION purl.org/becyt/ford/4.2 [https] Photosynthetically active radiation CIENCIAS AGRÍCOLAS Aboveground Net Primary Production General Earth and Planetary Sciences Environmental science TEMPORAL Rangelands Spatial variability lcsh:Q Above-Ground Biomass purl.org/becyt/ford/4 [https] Tierras de Pastos |
| Zdroj: | Remote Sensing 10 (9) : 1474. (2018) INTA Digital (INTA) Instituto Nacional de Tecnología Agropecuaria instacron:INTA Remote Sensing Vol.10, no.9 (2018) FAUBA Digital (UBA-FAUBA) Universidad de Buenos Aires. Facultad de Agronomía instacron:UBA-FAUBA Vol.10, no.9 CONICET Digital (CONICET) Consejo Nacional de Investigaciones Científicas y Técnicas instacron:CONICET Remote Sensing, Vol 10, Iss 9, p 1474 (2018) Remote Sensing; Volume 10; Issue 9; Pages: 1474 |
| Popis: | Monitoring of aboveground net primary production (ANPP) is critical for effective management of rangeland ecosystems but is problematic due to the vast extent of rangelands globally, and the high costs of ground-based measurements. Remote sensing of absorbed photosynthetically active radiation (APAR) can be used to predict ANPP, potentially offering an alternative means of quantifying ANPP at both high temporal and spatial resolution across broad spatial extents. The relationship between ANPP and APAR has often been quantified based on either spatial variation across a broad region or temporal variation at a location over time, but rarely both. Here we assess: (i) if the relationship between ANPP and APAR is consistent when evaluated across time and space; (ii) potential factors driving differences between temporal versus spatial models, and (iii) the magnitude of potential errors relating to space for time transformations in quantifying productivity. Using two complimentary ANPP datasets and remotely sensed data derived from MODIS and a Landsat/MODIS fusion data product, we find that slopes of spatial models are generally greater than slopes of temporal models. The abundance of plant species with different structural attributes, specifically the abundance of C4 shortgrasses with prostrate canopies versus taller, more productive C3 species with more vertically complex canopies, tended to vary more dramatically in space than over time. This difference in spatial versus temporal variation in these key plant functional groups appears to be the primary driver of differences in slopes among regression models. While the individual models revealed strong relationships between ANPP to APAR, the use of temporal models to predict variation in space (or vice versa) can increase error in remotely sensed predictions of ANPP. Fil: Gaffney, Rowan. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Porensky, Lauren. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Gao, Feng. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Irisarri, Jorge Gonzalo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Durante, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Concepción del Uruguay; Argentina Fil: Derner, Justin. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Augustine, David. United States Department of Agriculture. Agricultural Research Service; Argentina |
| Databáze: | OpenAIRE |
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