Distribution Of Net Primary Productivity Research Articles

Research on belowground productivity and ecophysiology of balsam fir and sugar maple in New Brunswick

We are investigating responses of ecosystem processes to climate and silvicultural practices to improve predictions of climate change impacts and to assess opportunities for adapting to impending changes. This involves studies of fine- and coarse-root dynamics, the distribution of net primary production between aboveground and belowground components of balsam fir (Abies balsamea [L.] Mill.) and sugar maple (Acer saccharum [Marsh.]) and photosynthetic capacity of balsam fir during winter and spring. Ongoing studies are described. Key words: fine roots, coarse roots, conifer, hardwood, net primary production, biomass dynamics, photosynthetic recovery, root lifespan, root turnover, soil temperature

Carbon‐based primary productivity modeling with vertically resolved photoacclimation

Net primary production (NPP) is commonly modeled as a function of chlorophyll concentration (Chl), even though it has been long recognized that variability in intracellular chlorophyll content from light acclimation and nutrient stress confounds the relationship between Chl and phytoplankton biomass. It was suggested previously that satellite estimates of backscattering can be related to phytoplankton carbon biomass (C) under conditions of a conserved particle size distribution or a relatively stable relationship between C and total particulate organic carbon. Together, C and Chl can be used to describe physiological state (through variations in Chl:C ratios) and NPP. Here, we fully develop the carbon‐based productivity model (CbPM) to include information on the subsurface light field and nitracline depths to parameterize photoacclimation and nutrient stress throughout the water column. This depth‐resolved approach produces profiles of biological properties (Chl, C, NPP) that are broadly consistent with observations. The CbPM is validated using regional in situ data sets of irradiance‐derived products, phytoplankton chlorophyll:carbon ratios, and measured NPP rates. CbPM‐based distributions of global NPP are significantly different in both space and time from previous Chl‐based estimates because of the distinction between biomass and physiological influences on global Chl fields. The new model yields annual, areally integrated water column production of ∼52 Pg C a−1 for the global oceans.

Dust pollen distribution on a continental scale and its relation to present-day vegetation along north-south transects in east China

A series of dust pollen samples was collected along N-S transects in east China (18 degrees N to 53 degrees N latitudes). Sample sites extend from the cold-temperate zone in the north to the tropical region in the south. Pollen taxa characterize each region and reflect the natural and devastated vegetation as well as corresponding climatic zones. The quantitative pollen data can be used to estimate the spatial distribution of planted and introduced species. Valuable information of human disturbance of the natural forest is evaluated by quantitative comparison between dust pollen and in-situ pollen of protected forest. In addition, percentages of grass pollen vary regularly from north to south that is consistent with spatial distribution of net primary productivity in east China. Among all grasses, Artemisia and the Gramineae carry the clearest signal: their ratio increases northwards and therefore represent a suitable and convenient tool for palaeoclimate reconstructions.

Climate-driven trends in contemporary ocean productivity

Contributing roughly half of the biosphere's net primary production (NPP), photosynthesis by oceanic phytoplankton is a vital link in the cycling of carbon between living and inorganic stocks. Each day, more than a hundred million tons of carbon in the form of CO2 are fixed into organic material by these ubiquitous, microscopic plants of the upper ocean, and each day a similar amount of organic carbon is transferred into marine ecosystems by sinking and grazing. The distribution of phytoplankton biomass and NPP is defined by the availability of light and nutrients (nitrogen, phosphate, iron). These growth-limiting factors are in turn regulated by physical processes of ocean circulation, mixed-layer dynamics, upwelling, atmospheric dust deposition, and the solar cycle. Satellite measurements of ocean colour provide a means of quantifying ocean productivity on a global scale and linking its variability to environmental factors. Here we describe global ocean NPP changes detected from space over the past decade. The period is dominated by an initial increase in NPP of 1,930 teragrams of carbon a year (Tg C yr(-1)), followed by a prolonged decrease averaging 190 Tg C yr(-1). These trends are driven by changes occurring in the expansive stratified low-latitude oceans and are tightly coupled to coincident climate variability. This link between the physical environment and ocean biology functions through changes in upper-ocean temperature and stratification, which influence the availability of nutrients for phytoplankton growth. The observed reductions in ocean productivity during the recent post-1999 warming period provide insight on how future climate change can alter marine food webs.

Vegetation NPP distribution based on MODIS data and CASA model—A case study of northern Hebei Province

Net Primary Productivity (NPP) is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach (CASA) model. The spatial distribution of Absorbed Photosynthetically Active Radiation (APAR) of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subregions were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 106gC/(m2·a), and NPP in 2001 ranged from 2 to 608gC/(m2·a), with an average of 337.516gC/(m2·a). NPP of the study area in 2001 accumulated mainly from May to September (DOY 129–272), high NPP values appeared from June to August (DOY 177–204), and the maximum NPP appeared from late July to mid-August (DOY 209–224).

Spatio-temporal distribution of net primary productivity along the Northeast China Transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model (CASA model) was used to estimate the net primary productivity (NPP) of the Northeast China Transect (NECT) every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 (P < 0.01). The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 (P < 0.01). The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer (June to August) accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m−2·a−1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Climate variability, vegetation productivity and people at risk

Human domination of ecosystems has been pervasive over the last century, with nearly half of Earth's surface transformed by human actions. It is widely accepted that humans appropriate up to 50% of global net primary production (NPP), the energy base of all the trophic levels on the land surface. Yet, despite the important role of vegetation productivity for defining Earth habitability, the covariation of NPP and human population distribution has not been analyzed in depth. We used recently available satellite-based NPP estimates, along with gridded population at 0.5° resolution, first, to identify the global distribution of human population with reference to average NPP and to the various climatic constraints (temperature, water and cloud cover) that limit NPP, second, to analyze recent trends in global NPP in relation to population trends, and third, to identify populations that are vulnerable to changes in NPP due to interannual variability in climate. Our results indicate that over half of the global human population is presently living in areas with above the average NPP of 490 g C m −2 year −1. By 1998, nearly 56% of global population lived in regions where water availability strongly influences NPP. Per capita NPP declined over much of Africa between 1982 and 1998, in spite of the estimated increases in NPP over the same period. On average, NPP over 40% of the total vegetated land surface has shown significant correlations with ENSO-induced climate variability affecting over 2.8 billion people.

Anthropogenic impacts upon plant species richness and net primary productivity in California

AbstractWe assess the importance of anthropogenic land‐use, altered productivity, and species invasions for observed productivity–richness relationships in California. To this end, we model net primary productivity (NPP) c. 1750 AD and at present (1982–1999) and map native and exotic vascular plant richness for 230 subecoregions. NPP has increased up to 105% in semi‐arid areas and decreased up to 48% in coastal urbanized areas. Exotic invasions have increased local species diversity up to 15%. Human activities have reinforced historical gradients in species richness but reduced the spatial heterogeneity of NPP. Structural equation modelling suggests that, prior to European settlement, NPP and richness were primarily controlled by precipitation and other abiotic variables, with NPP mediating richness. Abiotic variables remain the strongest predictors of present NPP and richness, but intermodel comparisons indicate a significant anthropogenic impact upon statewide distributions of NPP and richness. Exotic and native species each positively correlate to NPP after controlling for other variables, which may help explain recent reports of positively associated native and exotic richness.

Photosynthesis, transpiration, and primary productivity: Scaling up from leaves to canopies and regions using process models and remotely sensed data

Biophysical and physiological processes in plants and ecosystems occur over a wide range of spatial and temporal scales. Our knowledge (or models) of these processes is largely at small scales. It is, however, difficult to directly apply mechanistic process‐oriented models over large scales due to heterogeneities in the distributions of processes, and nonlinearities in the functional responses of processes to environmental variables. On the other hand, simple parametric/empirical models in which system complexity is lumped into a small number of parameters have been widely employed to describe processes at larger scales. The variation of these parameters in these simple parametric/empirical models depends on the underlying biophysical processes. In this work, we showed that detailed process models and simple parametric models for primary production and transpiration could be effectively combined to scale leaf photosynthesis and transpiration up to large spatial scales. The integrated process model, General Energy Mass Transfer Model (GEMTM), was used to identify major factors contributing to the variability of the parameters in the parametric models for regional transpiration and primary production and quantify their responses to these factors. Simulations with the GEMTM showed that net carbon assimilation was proportional to intercepted photosynthetically active radiation (IPAR), but the radiation use efficiency (RUE) changed with leaf N concentration, temperature, and atmospheric CO2 concentration; transpiration was linearly correlated with the product of net primary production (NPP) and atmospheric water vapor pressure deficit (VPD), and the slope varied with leaf N concentration. RUE increased with leaf N content asymptotically, and responded to temperature in an asymmetric bell shape pattern with a 22°C and 26°C optimal temperature under current ambient and doubled CO2 concentration, respectively. A simple parametric NPP model and a regional transpiration model (Tr model) were developed from the relationships and parameter values obtained using the GEMTM. The NPP model reasonably simulated the seasonal and interannual variations of accumulated NPP estimated from field data. Simulated regional distribution of NPP over the Central Grassland Region of the United States was consistent with estimates obtained using other models. NPP increased from 120 gC/m2/year in the northwest to 956 gC/m2/year in the southeast. Simulated regional transpiration had a similar spatial distribution pattern as NPP, ranging from about 16 cmH2O/year to 136 cmH2O/year. The transpiration model introduced in this study provides a mechanism to explicitly couple transpiration and NPP in large‐scale analyses, although more complete analysis and validation are required.

Spatial distribution of net primary productivity and evapotranspiration in Changbaishan Natural Reserve, China, using Landsat ETM+ data

Remote sensing has been a useful tool to monitor net primary productivity (NPP) and evapotranspiration (ET). In this paper, based on field measurements and Landsat enhanced thematic mapper plus (ETM+) data, NPP and ET are estimated in 2001 in the Changbaishan Natural Reserve, China. Maps of land cover, leaf area index, and biomass of this forested region are first derived from ETM+ data. With these maps and additional soil texture and daily meteorological data, NPP and ET maps are produced for 2001 using the boreal ecosystem productivity simulator (BEPS). The results show that the estimated and observed NPP values for forest agree fairly well, with a mean relative error of 8.6%. The NPP of mixed forests is the highest, with a mean of 500 g C m–2·a–1, and that of alpine tundra and shrub is the lowest, with a mean of 136 g C m–2·a–1. Unlike the spatial pattern of NPP, the annual ET changes distinctly with altitude from greater than 600 mm at the foot of the mountain to about 200 mm at the top of the mountain. ET is highest for broadleaf forests and lowest for urban and built-up areas.

A new methodology for estimating forest NPP based on forest inventory data—A case study of Chinese pine forest

Accurately estimating forest net primary productivity (NPP) plays an important role in study of global carbon budget. A NPP model reflecting the synthetic effects of both biotic (forest stand age, A and stem volume, V) and climatic factors (mean annual actual evapotranspiration, E) was developed for Chinese pine (Pinus tabulaeformis) forest by making full use of Forest Inventory Data (FID) and dynamically assessing forest productivity. The NPP of Chinese pine forest was estimated by using this model and the fourth FID (1989–1993), and the spatial pattern of NPP of Chinese pine forest was given by Geography Information System (GIS) software. The results indicated that mean NPP value, of Chinese pine forest was 7.82 t m−2·a−1 and varied at the range of 3.32–11.87 t hm−2·a−1. NPP distribution of Chinese pine forests was significantly different in different regions, higher in the south and lower in the north of China. In terms of the main distribution regions of Chinese pine, the NPPs of Chinese pine forest in Shanxi and Shaanxi provinces were in middle level, with an average NPP of 7.4 t hm−2·a−1, that in the southern and the eastern parts (e.g. Shichuang Hunan, Henan, and Liaoning provinces) was higher (over 7.7 t hm−2·a−1), and that in the northern part and western part (e.g. Neimenggu and Ningxia provinces) was lower (below 5 t hm−2·a−1). This study provides an efficient way for using FID to understand the dynamics of foest NPP and evaluate its effects on global climate change.

The temporal and spatial patterns of terrestrial net primary productivity in China

In this paper, we use CEVSA, a process-based model, which has been validated on regional and global scales, to explore the temporal and spatial patterns of Net Primary Productivity (NPP) and its responses to interannual climate fluctuations in China’s terrestrial ecosystems over the period 1981–1998. The estimated results suggest that, in this study period, the averaged annual total NPP is about 3.09 Gt C/yr1 and average NPP is about 342 g C/m2. The results also showed that the precipitation was the key factor determining the spatial distribution and temporal trends of NPP. Temporally, the total NPP exhibited a slowly increasing trend. In some ENSO years (e.g. 1982, 1986, 1997) NPP decreased clearly compared to the previous year, but the relationship between ENSO and NPP is complex due to the integrated effects of monsoons and regional differentiation. Spatially, the relatively high NPP occurred at the middle high latitudes, the low latitudes and the lower appeared at the middle latitudes. On national scale, precipitation is the key control factor on NPP variations and there exists a weak correlation between NPP and temperature, but regional responses are greatly different.

Integrating remotely sensed data with an ecosystem model to estimate net primary productivity in East Asia

This paper describes a method of integrating remotely sensed data with an ecosystem model to estimate net primary productivity (NPP) in East Asia. We improved the Boreal Ecosystem Productivity Simulator (BEPS) model for global NPP estimation by incorporating a new land cover map and employed a robust Normalized Difference Vegetation Index–Leaf Area Index (NDVI–LAI) algorithm. Using this method, we produced a map showing the distribution of annual NPP in East Asia in 1998 and calculated that the mean NPP for that area in that year was 634 g C/m 2/year. Comparing the estimated NPP obtained from model computation with the observed NPP obtained from an NPP database, we found that the estimated NPP closely approximates the observed NPP, with an average error of −20%. We checked the accuracy of a six-biome land cover map using a Geographic Information System (GIS) data set for Japan [Data Sets for GIS on the Natural Environment, Japan (DS_GIS_NEJ), Japan Environment Agency, Ver. 2, 1999] and how the accuracy of the map affects NPP estimation. Results show that an accurate land cover map is essential if one is to accurately and reliably estimate NPP, and it is especially crucial if one is to estimate the NPP of an individual biome (e.g., for crop prediction).

Dynamic change of net primary productivity and fractional vegetation cover in the yellow river Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.

Estimation of net primary productivity in China using remote sensing data

It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. Remote sensing data can describe spatial distribution of plant resources better. So, in this paper an NPP model based on remote sensing data and climate data is developed. And 1km resolution AVHRR NDVI data are used to estimate the spatial distribution and seasonal change of NPP in China. The results show that NPP estimated using remote sensing data are more close to truth. Total annual NPP in China is 2.645X109 tC. The spatial distribution of NPP in China is mainly affected by precipitation and has the trend of decreasing from southeast to northwest.

Analysis of the spatial distribution of net primary productivity across Corsica (France) using the echelon approach

One of the main directions of research for ecologists studying the Earth as a global system is the search for quantitative methods for mapping and monitoring broad-scale patterns of net primary productivity (NPP). While all monitoring activities have a spatial context to a varying degree, the monitoring of NPP patterns requires an objective, criterion-based method for characterizing the spatial distribution of areas that are high or low in NPP relative to their surroundings. In this Letter, we apply a topology-based methodology called the 'echelon approach' to characterize the spatial structure of the remotely sensed NPP spatial structure across the island of Corsica (France) using a coarse-grained grid consisting of annually integrated Normalized Difference Vegetation Index (NDVI) values. Results show that the echelon approach provides a new perspective to objectively characterize the structural complexity of a tessellated surface variable for environmental monitoring purposes.

Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data

The purpose of this paper is to upscale tower measurements of net primary productivity (NPP) to the Boreal Ecosystem‐Atmosphere Study (BOREAS) study region by means of remote sensing and modeling. The Boreal Ecosystem Productivity Simulator (BEPS) with a new daily canopy photosynthesis model was first tested in one coniferous and one deciduous site. The simultaneous CO2 flux measurements above and below the tree canopy made it possible to isolate daily net primary productivity of the tree canopy for model validation. Soil water holding capacity and gridded daily meteorological data for the region were used as inputs to BEPS, in addition to 1 km resolution land cover and leaf area index (LAI) maps derived from the advanced very high resolution radiometer (AVHRR) data. NPP statistics for the various cover types in the BOREAS region and in the southern study area (SSA) and the northern study area (NSA) are presented. Strong dependence of NPP on LAI was found for the three major cover types: coniferous forest, deciduous forest and cropland. Since BEPS can compute total photosynthetically active radiation absorbed by the canopy in each pixel, light use efficiencies for NPP and gross primary productivity could also be analyzed. From the model results, the following area‐averaged statistics were obtained for 1994: (1) mean NPP for the BOREAS region of 217 g C m−2 yr−1; (2) mean NPP of forests (excluding burnt areas in the region) equal to 234 g C m−2 yr−1; (3) mean NPP for the SSA and the NSA of 297 and 238 g C m−2 yr−1, respectively; and (4) mean light use efficiency for NPP equal to 0.40, 0.20, and 0.33 g C (MJ APAR)−1 for deciduous forest, coniferous forest, and crops, respectively.

Comparing global models of terrestrial net primary productivity (NPP): comparison of NPP to climate and the Normalized Difference Vegetation Index (NDVI)

SummaryTo analyse the broad‐scale behaviour of 15 global models of the terrestrial biosphere, we evaluated the sensitivity of simulated net primary productivity (NPP) to spatial and seasonal variations in precipitation, temperature and solar radiation, and to the Normalized Difference Vegetation Index (NDVI). For annual NPP estimates, the models’ sensitivities to climate were the most similar in regions where NPP was not limited by precipitation. The largest differences in sensitivities occurred in regions where NPP was limited by both temperature and precipitation. Water use efficiencies within the models were relatively constant across latitudes so that higher correlations occurred between the latitudinal distribution of NPP and precipitation than with the other climate variables. The sensitivities of NPP estimates to solar radiation varied considerably with latitude. The largest differences in temperature sensitivity among NPP estimates occurred in the northern latitudes (50°N–70°N), i.e. the zone with the shortest active growing seasons. The sensitivity of NPP estimates to climate also varied seasonally. At the beginning and end of the active growing season in the boreal zone, monthly NPP estimates of all models were the most sensitive to temperature. In the tropics, sensitivities to climate varied widely among and within models. Seasonal changes in water balance and the structure of the vegetation canopy, as reflected by seasonal changes in NDVI, modified the sensitivity of NPP to climate in both boreal and tropical zones. Because these are both highly productive regions sensitive to climate change, continued investigations and better validation of models are necessary before we can fully understand and predict changes in ecosystem structure and function under various climatic conditions.

Primary production of the biosphere: integrating terrestrial and oceanic components

Integrating conceptually similar models of the growth of marine and terrestrial primary producers yielded an estimated global net primary production (NPP) of 104.9 petagrams of carbon per year, with roughly equal contributions from land and oceans. Approaches based on satellite indices of absorbed solar radiation indicate marked heterogeneity in NPP for both land and oceans, reflecting the influence of physical and ecological processes. The spatial and temporal distributions of ocean NPP are consistent with primary limitation by light, nutrients, and temperature. On land, water limitation imposes additional constraints. On land and ocean, progressive changes in NPP can result in altered carbon storage, although contrasts in mechanisms of carbon storage and rates of organic matter turnover result in a range of relations between carbon storage and changes in NPP.

Contrasting Climatic Controls on the Estimated Productivity of Global Terrestrial Biomes

Net primary productivity (NPP) represents the greatest annual carbon flux from the atmosphere to the biosphere, is an important component of seasonal fluctuations in atmospheric CO2 concentrations, and is the most critical biotic component of the global carbon cycle. NPP measures products of major economic and social importance, such as crop yield and forest production. Given that global NPP can not be measured directly, model simulations must provide understanding of its global spatial and temporal dynamics. In this study, we used the biogeochemical model BIOME-BGC to simulate global terrestrial NPP and assessed relative importance of climatic controls (temperature, water availability, and radiation) in limiting NPP in the array of climatic combinations found globally. The degree of limitation on NPP by climatic controls was defined by using an empirical membership function. Results showed that temperature or water availability limited NPP over larger land areas (31% and 52%, respectively) than did radiation limitation (5%). Climatic controls appeared to be important in limiting productivity in most vegetation biomes, except for evergreen broadleaf forests. Nevertheless, there were areas of the globe (12%) where none of the climatic factors appeared to limit NPP. Our research has suggested that other environmental controls, such as nutrient availability or biological constraints, should then be considered. The wide distribution of NPP between zero and the upper boundary values in the correlation plots indicated that multivariate environmental balances, not single limiting factors, controlled biospheric productivity.