Correction: Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

This chapter deals with the ecology of Tropical East Asia from the perspective of water, energy, and matter flows through ecosystems, particularly forests. Data from the network of eddy flux covariance towers is revealing general patterns in gross primary production, ecosystem respiration, and net ecosystem production, and exchange. There is also new information on the patterns of net primary production and biomass within the region. In contrast, our understanding of the role of soil nutrients in tropical forest ecology still relies mostly on work done in the Neotropics, with just enough data from Asia to suggest that the major patterns may be pantropical. Nitrogen and phosphorus have received most attention regionally, followed by calcium, potassium, and magnesium, and there has been very little study of the role of micronutrients and potentially toxic concentrations of aluminium, manganese, and hydrogen ions. Animal nutrition has also been neglected.

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Changes in root zone storage capacity and their effects on river discharge and gross primary production

10.5194/egusphere-egu2020-12017 ◽

2020 ◽

Author(s):

Rodolfo Nóbrega ◽

David Sandoval ◽

Colin Prentice

Keyword(s):

Land Cover ◽

Primary Production ◽

Mass Balance ◽

Land Cover Change ◽

Storage Capacity ◽

Root Zone ◽

Gross Primary Production ◽

Terrestrial Ecosystem ◽

Ecosystem Models ◽

Stress Functions

Root zone storage capacity (Rz) is a parameter widely used in terrestrial ecosystem models that estimate the amount of soil moisture available for transpiration. However, Rz is subject to large uncertainty, due to the lack of data on the distribution of soil properties and the depth of plant roots that actively take up water. Our study makes use of a mass-balance approach to investigate Rz in different ecosystems, and changes in water fluxes caused by land-cover change. The method needs no land-cover or soil information, and uses precipitation (P) and evapotranspiration (ET) time series to estimate the seasonal water deficit. To account for some of the uncertainty in ET, we use different methods for ET estimation, including methods based on satellite estimates, and modelling approaches that back-calculate ET from other ecosystem fluxes. We show that reduced ET due to land-cover change reduces Rz, which in turn increases baseflow in regions with a strong rainfall seasonality. This finding allows us to analyse the trade-off between gross primary production and hydrological fluxes at river basin scales. We also consider some ideas on how to use mass-balance Rz in water-stress functions as incorporated in existing terrestrial ecosystem models.

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Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types

Ecological Indicators ◽

10.1016/j.ecolind.2016.08.022 ◽

2017 ◽

Vol 72 ◽

pp. 153-164 ◽

Cited By ~ 28

Author(s):

Hao Shi ◽

Longhui Li ◽

Derek Eamus ◽

Alfredo Huete ◽

James Cleverly ◽

...

Keyword(s):

Land Cover ◽

Primary Production ◽

Gross Primary Production ◽

Terrestrial Ecosystem ◽

Land Cover Types ◽

Modis Evi

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Land cover change-induced decline in terrestrial gross primary production over the conterminous United States from 2001 to 2016

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2021.108609 ◽

2021 ◽

Vol 308-309 ◽

pp. 108609

Author(s):

Yulong Zhang ◽

Conghe Song ◽

Taehee Hwang ◽

Kimberly Novick ◽

John W. Coulston ◽

...

Keyword(s):

United States ◽

Land Cover ◽

Primary Production ◽

Land Cover Change ◽

Gross Primary Production

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Improvement of satellite-based estimation of gross primary production through optimization of meteorological parameters and high resolution land cover information at regional scale over East Asia

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2019.02.040 ◽

2019 ◽

Vol 271 ◽

pp. 180-192

Author(s):

Haemi Park ◽

Jungho Im ◽

Miae Kim

Keyword(s):

High Resolution ◽

Land Cover ◽

Primary Production ◽

East Asia ◽

Meteorological Parameters ◽

Gross Primary Production ◽

Regional Scale

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Studying the Influence of Nitrogen Deposition, Precipitation, Temperature, and Sunshine in Remotely Sensed Gross Primary Production Response in Switzerland

Remote Sensing ◽

10.3390/rs11091135 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1135 ◽

Cited By ~ 1

Author(s):

Marta Gómez Giménez ◽

Rogier de Jong ◽

Armin Keller ◽

Beat Rihm ◽

Michael E. Schaepman

Keyword(s):

Species Richness ◽

Land Cover ◽

Primary Production ◽

Management Practices ◽

Gross Primary Production ◽

N Deposition ◽

Natural Vegetation ◽

Alpine Grasslands ◽

High Species Richness ◽

Vegetation Mosaic

Climate, soil type, and management practices have been reported as primary limiting factors of gross primary production (GPP). However, the extent to which these factors predict GPP response varies according to scales and land cover classes. Nitrogen (N) deposition has been highlighted as an important driver of primary production in N-limited ecosystems that also have an impact on biodiversity in alpine grasslands. However, the effect of N deposition on GPP response in alpine grasslands hasn’t been studied much at a large scale. These remote areas are characterized by complex topography and extensive management practices with high species richness. Remotely sensed GPP products, weather datasets, and available N deposition maps bring along the opportunity of analyzing how those factors predict GPP in alpine grasslands and compare these results with those obtained in other land cover classes with intensive and mixed management practices. This study aims at (i) analyzing the impact of N deposition and climatic variables (precipitation, sunshine, and temperature) on carbon (C) fixation response in alpine grasslands and (ii) comparing the results obtained in alpine grasslands with those from other land cover classes with different management practices. We stratified the analysis using three land cover classes: Grasslands, croplands, and croplands/natural vegetation mosaic and built multiple linear regression models. In addition, we analyzed the soil characteristics, such as aptitude for croplands, stone content, and water and nutrient storage capacity for each class to interpret the results. In alpine grasslands, explanatory variables explained up to 80% of the GPP response. However, the explanatory performance of the covariates decreased to maximums of 47% in croplands and 19% in croplands/natural vegetation mosaic. Further information will improve our understanding of how N deposition affects GPP response in ecosystems with high and mixed intensity of use management practices, and high species richness. Nevertheless, this study helps to characterize large patterns of GPP response in regions affected by local climatic conditions and different land management patterns. Finally, we highlight the importance of including N deposition in C budget models, while accounting for N dynamics.

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ESTIMATION OF GROSS PRIMARY PRODUCTION USING SATELLITE DATA AND GIS IN URBAN AREA, DENPASAR

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2010.v7.a1544 ◽

2011 ◽

Vol 7 (1) ◽

Cited By ~ 1

Author(s):

A.R. As-syakur ◽

T. Osawa ◽

IW.S. Adnyana

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Primary Production ◽

Spatial Resolution ◽

Satellite Data ◽

High Spatial Resolution ◽

Gross Primary Production ◽

Remote Sensing Data ◽

Sensing Data

Remote sensing data with high spatial resolution is very useful to provideinformation about Gross Primary Production (GPP) especially over spatial coverage in theurban area. Most models of ecosystem carbon exchange based on remote sensing data usedlight use efficiency (LUE) model. The aim of this research was to analyze the distributionof annual GPP urban area of Denpasar. Two main satellite data used in this study wereALOS/AVNIR-2 and Aster satellite data. Result showed that annual value of GPP usingALOS/AVNIR-2 varied from 0.130 gC m-2 yr-1 to 2586.181 gC m-2 yr-1. Meanwhile, usingAster the value varied from 0.144 gC m-2 yr-1 to 2595.264 gC m-2 yr-1. The annual value ofGPP ALOS was lower than the value of Aster, because ALOS have high spatial resolutionand smaller interval of spectral resolution compared to Aster. Different land use couldeffect the value of GPP, because the different land use has different vegetation type,distribution, and different photosynthetic pathway type. The high spatial resolution of theremote sensing data is crucial to discriminate different land cover types in urban region.With heterogeneous land cover surface, maximum value of GPP using ALOS/AVNIR-2was smaller than that of Aster, however, the annual mean of GPP value usingALOS/AVNIR-2 was higher than that of Aster.

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