Modelling the net primary productivity of temperate forest ecosystems in China with a GAP model

1999 ◽  
Vol 122 (3) ◽  
pp. 225-238 ◽  
Author(s):  
Hong Jiang ◽  
Changhui Peng ◽  
Michael J Apps ◽  
Yanli Zhang ◽  
Paul M Woodard ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Temperate Forest ◽  
Forest Ecosystems ◽  
Net Primary Productivity ◽  
Gap Model

scholarly journals Assessing Forest Ecosystems across the Vertical Edge of the Mid-Latitude Ecotone Using the BioGeoChemistry Management Model (BGC-MAN)

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 523 ◽  
Author(s):  
Cholho Song ◽  
Stephan A. Pietsch ◽  
Moonil Kim ◽  
Sungeun Cha ◽  
Eunbeen Park ◽  
...  
Keyword(s):  
Transition Zone ◽  
Primary Productivity ◽  
Forest Ecosystems ◽  
Net Primary Productivity ◽  
Northeast Asia ◽  
Siberian Larch ◽  
Management Model ◽  
High Mountain ◽  
Specific Information ◽  
Larch Forests

The mid-latitude ecotone (MLE)—a transition zone between boreal and temperate forests, which includes the regions of Northeast Asia around 30°–60° N latitudes—delivers different ecosystem functions depending on different management activities. In this study, we assessed forest volume and net primary productivity changes in the MLE of Northeast Asia under different ecological characteristics, as well as various current management activities, using the BioGeoChemistry Management Model (BGC-MAN). We selected five pilot sites for pine (Scots pine and Korean red pine; Pinus sylvestris and P. densiflora), oak (Quercus spp.), and larch forests (Dahurian larch and Siberian larch; Larix gmelinii and L. sibirica), respectively, which covered the transition zone across the MLE from Lake Baikal, Russia to Kyushu, Japan, including Mongolia, Northeast China, and the Korean Peninsula. With site-specific information, soil characteristics, and management descriptions by forest species, we established their management characteristics as natural preserved forests, degraded forests, sandy and cold forest stands, and forests exposed to fires. We simulated forest volume (m3) and net primary productivity (Mg C ha−1) during 1960–2005 and compared the results with published literature. They were in the range of those specified in previous studies, with some site-levels under or over estimation, but unbiased estimates in their mean values for pine, oak, and larch forests. Annual rates of change in volume and net primary productivity differed by latitude, site conditions, and climatic characteristics. For larch forests, we identified a high mountain ecotype which warrants a separate model parameterization. We detected changes in forest ecosystems, explaining ecological transition in the Northeast Asian MLE. Under the transition, we need to resolve expected problems through appropriate forest management and social efforts.

scholarly journals Productivity, biodiversity, and pathogens influence the global hunter-gatherer population density

2017 ◽  
Vol 115 (6) ◽  
pp. 1232-1237 ◽  
Author(s):  
Miikka Tallavaara ◽  
Jussi T. Eronen ◽  
Miska Luoto
Keyword(s):  
Population Density ◽  
Primary Productivity ◽  
Human Population ◽  
Temperate Forest ◽  
Net Primary Productivity ◽  
Environmental Drivers ◽  
Ecological Research ◽  
High Productivity ◽  
The Core ◽  
Global Population

The environmental drivers of species distributions and abundances are at the core of ecological research. However, the effects of these drivers on human abundance are not well-known. Here, we report how net primary productivity, biodiversity, and pathogen stress affect human population density using global ethnographic hunter-gatherer data. Our results show that productivity has significant effects on population density globally. The most important direct drivers, however, depend on environmental conditions: biodiversity influences population density exclusively in low-productivity regions, whereas pathogen stress does so in high-productivity regions. Our results also indicate that subtropical and temperate forest biomes provide the highest carrying capacity for hunter-gatherer populations. These findings document that environmental factors play a key role in shaping global population density patterns of preagricultural humans.

scholarly journals Non-stomatal processes reduce gross primary productivity in temperate forest ecosystems during severe edaphic drought

2020 ◽  
Vol 375 (1810) ◽  
pp. 20190527 ◽  
Author(s):  
Louis Gourlez de la Motte ◽  
Quentin Beauclaire ◽  
Bernard Heinesch ◽  
Mathias Cuntz ◽  
Lenka Foltýnová ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Temperate Forest ◽  
Forest Ecosystems ◽  
Stomatal Closure ◽  
Gross Primary Productivity ◽  
Severe Drought ◽  
Continental Scale ◽  
European Forest ◽  
Ecosystem Flux ◽  
The Impact

Severe drought events are known to cause important reductions of gross primary productivity ( GPP ) in forest ecosystems. However, it is still unclear whether this reduction originates from stomatal closure (Stomatal Origin Limitation) and/or non-stomatal limitations (Non-SOL). In this study, we investigated the impact of edaphic drought in 2018 on GPP and its origin (SOL, NSOL) using a dataset of 10 European forest ecosystem flux towers. In all stations where GPP reductions were observed during the drought, these were largely explained by declines in the maximum apparent canopy scale carboxylation rate V CMAX,APP (NSOL) when the soil relative extractable water content dropped below around 0.4. Concurrently, we found that the stomatal slope parameter ( G 1 , related to SOL) of the Medlyn et al . unified optimization model linking vegetation conductance and GPP remained relatively constant. These results strengthen the increasing evidence that NSOL should be included in stomatal conductance/photosynthesis models to faithfully simulate both GPP and water fluxes in forest ecosystems during severe drought. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

scholarly journals Biomass and Net Primary Productivity in three different Aged Butea Forest Ecosystems in Western India, Rajasthan

Our Nature ◽  
1970 ◽  
Vol 9 (1) ◽  
pp. 73-82 ◽  
Author(s):  
J.I. Nirmal Kumar ◽  
P.R. Sajish ◽  
R.N. Kumar ◽  
K. Patel
Keyword(s):  
Primary Productivity ◽  
Forest Ecosystems ◽  
Net Primary Productivity ◽  
Forest Biomass ◽  
Western India ◽  
Butea Monosperma ◽  
Tree Layer ◽  
Tree Litter ◽  
Shrub Biomass ◽  
Trees And Shrubs

The study was conducted to estimate the biomass and net primary productivity of different age grouped (5, 10 and 15-year-old) Butea monosperma forest ecosystems in western India , Rajasthan (located between 23º49′ to 25º28′N latitudes and 73º0′ to 75º49′E longitudes) from June 2007 to May 2008. The vegetation biomass, forest floor biomass, tree litter fall and net primary productivity (NPP) of trees and shrubs were estimated and it was found that the tree biomass and net primary productivity increased with increasing age of the forest stand, whereas the herb biomass and net primary productivity decreased significantly (P<0.01) with increase in the forest age. The biomass of trees increased with age from 183.7±3.21 to 298.3±3.57 t ha-1 while shrub biomass ranged from 4.9±1.61 to 6.3±1.38 t ha-1 and the herb biomass fluctuated from 1.7±1.64 to 2.1±1.81. The tree layer NPP varied from 17.2 to 29.3 t ha-1 year-1 whereas the NPP of the shrub layer was 0.88 to 1.6 t ha-1 year-1. The productivity of the herb layer fluctuated from 2.3 to 3.1 t ha-1 year-1. All values of biomass and NPP of trees, shrubs and herbs were low in 5-year-old, moderate in 10-year-old and high in 15-year-old forest stands. The total forest biomass increased from 190.7 t ha-1 in the 5-year-old to 306.3 t ha-1 15-year-old forest and net primary productivity from 21.1 t ha-1 year-1 in the 5-year-old to 33.2 t ha-1 year-1 in the 15-year-old forest.  DOI: http://dx.doi.org/10.3126/on.v9i1.5736

Satellite-based estimation of net primary productivity for southern China’s grasslands from 1982 to 2012

2017 ◽  
Vol 71 (3) ◽  
pp. 187-201 ◽  
Author(s):  
W Yang ◽  
T Lu ◽  
S Liu ◽  
J Jian ◽  
F Shi ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity
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