Terrestrial Net Primary Productivity Research Articles

Savannas Need Protection

The Savanna biome covers 20% of Earth's land surface; contributes 30% of terrestrial net primary production (NPP) ([ 1 ][1], [ 2 ][2]) (equivalent to the contribution of tropical forests); and accounts for 85% of the global area of land burnt annually ([ 3 ][3]). By any account, this productive

Estimation and analysis of terrestrial net primary productivity over India by remote-sensing-driven terrestrial biosphere model

In the present study, the Carnegie-Ames-Stanford Approach (CASA), a terrestrial biosphere model, has been used to investigate spatiotemporal pattern of net primary productivity (NPP) during 2003 over the Indian subcontinent. The model drivers at 2-min spatial resolution were derived from National Oceanic and Atmospheric Administration advanced very high resolution radiometer normalized difference vegetation index, weather inputs, and soil and land cover maps. The annual NPP was estimated to be 1.57 Pg C (at the rate of 544 g C m(-2)), of which 56% contributed by croplands (with 53% of geographic area of the country (GAC)), 18.5% by broadleaf deciduous forest (15% of GAC), 10% by broadleaf evergreen forest (5% of GAC), and 8% by mixed shrub and grassland (19% of GAC). There is very good agreement between the modeled NPP and ground-based cropland NPP estimates over the western India (R2=0.54; p=0.05). The comparison of CASA-based annual NPP estimates with the similar products from other operational algorithms such as C-fix and Moderate Resolution Imaging Spectroradiometer (MODIS) indicate that high agreement exists between the CASA and MODIS products over all land covers of the country, while agreement between CASA and C-Fix products is relatively low over the region dominated by agriculture and grassland, and the agreement is very low over the forest land. Sensitivity analysis suggest that the difference could be due to inclusion of variable light use efficiency (LUE) across different land cover types and environment stress scalars as downregulator of NPP in the present CASA model study. Sensitivity analysis further shows that the CASA model can overestimate the NPP by 50% of the national budget in absence of downregulators and underestimate the NPP by 27% of the national budget by the use of constant LUE (0.39 gC MJ(-1)) across different vegetation cover types.

The global loss of net primary production resulting from human-induced soil degradation in drylands

Land degradation, the temporary or permanent reduction of land's productive capacity resulting from poor land management, has gained considerable attention as an environmental and development issue of global importance, in particular in the Earth's drylands. This study presents a global estimate of net primary production (NPP) losses caused by human-induced dryland degradation. Due to the large uncertainties related to international databases on dryland degradation, we compiled a world map of the extent and degree of desertification based on existing regional and global maps. Two distinct approaches were followed in order to estimate NPP losses due to degradation on drylands: in the first approach, we combined these maps with model results on global potential NPP, determined with the LPJ-DGVM, with a set of factors on NPP losses per degradation degree, derived from the literature. In a second approach, we made use of spatially explicit information on potential and current NPP of agricultural areas obtained from a global HANPP assessment [Haberl, H., Erb, K.-H., Krausmann, F., Gaube, V., Bondeau, A., Plutzar, C., Gingrich, S., Lucht, W. and Fischer-Kowalski, M., 2007. Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems. Proceedings of the National Academy of Sciences of the United States of America, 104: 12942-12947.]. We used the difference between potential and current NPP on croplands situated in drylands in order to quantify the effect of dryland degradation on NPP. NPP losses were found to range between 799 and 1936 Tg C/yr in the first approach, and to amount to 965 Tg C/yr in the second approach. Overall, approximately 2% of the global terrestrial NPP are lost each year due to dryland degradation, or between 4% and 10% of the potential NPP in drylands. NPP losses amount to 20–40% of the potential NPP on degraded agricultural areas in the global average and above 55% in some world regions. The results reveal that the contributions of dryland degradation to the total HANPP in drylands is of similar dimension than the overall annual socioeconomic biomass harvest. Accordingly, strategies aimed at reducing dryland degradation could present promising options to sustain future population numbers without putting further pressures on dryland ecosystems.

Isotope composition and anion chemistry of soil profiles along the Kalahari Transect

Savannas cover about 20% of the Earth's land area across a wide range of climatic conditions. As an important and distinct biome, savannas produce approximately 29% of global terrestrial net primary productivity. In these ecosystems the distribution of belowground resources remains poorly investigated and the relationship to the climatic conditions remains unclear. In the present study, vertical profiles of soil nutrients (chloride, nitrate, phosphate and sulfate) and nitrogen stable isotopes were analyzed at four sites along the Kalahari mega-transect, where a distinct rainfall gradient exists on a homogeneous soil substrate. The results show clear differences in nutrients and δ 15N vertical distributions between wet and dry seasons. The results also show how the formation of “fertility islands” (i.e., the concentration of soil nutrients in the soils beneath tree canopies) is not necessarily coupled with belowground processes in that the distribution of soil nutrients at the surface does not match belowground patterns. The results also indicate that phosphorus may be a limiting nutrient in these savanna ecosystems with seasonal dynamics in its cycling.

Biospheric context of Siberian development

AbstractProductivity of ecosystems surrounding a city is important for supporting its activities in a sustainable way. The total terrestrial net primary production (NPP) shows biosphere potential to supply primary food energy source for all non-autotrophic species including humans. Humans appropriate approximately 20% of NPP, in average. Even in the relatively well-populated regions of Siberia, NPP per capita exceeds the average level by several times suggesting the window of opportunity for achieving sustainable development. (3 pages, 1086 words, 2 maps)

Retention of phosphorus in highly weathered soils under a lowland Amazonian forest ecosystem

The low available phosphorus (P) pools typical of highly weathered tropical forest soils are thought to result from a combination of export of phosphorus via erosion and leaching as well as chemical reactions resulting in physically and chemically protected P compounds. Despite the low apparent P availability, these soils support some of the highest terrestrial net primary productivity globally. We followed different P fractions after P additions to two soil types, sandy loam and sandy clay, over 1 year in a lowland Amazonian forest. Of all the soil P fractions measured, only the NaHCO3 and NaOH extractable fractions showed a significant increase following P additions, and this occurred only in sandy clays (+ 56.9 ± 15.1 kg ha−1 and + 2.8 ± 1.5 kg ha−1, respectively). Our results indicate that intermediate rather than recalcitrant pools are the dominant fate of added P over an annual timescale even in fine‐textured soils. Fine root and forest floor P pools increased more in the sandy loams following P additions suggesting a larger biotic P sink in these soils. Leaching of inorganic P from the surface soils was an unexpected and significant fate of added P in both soil types (9 ± 3% in the sandy loams, 2 ± 1% in the sandy clays). Significantly more of the added P was retained in the sandy clay soils than in the sandy loams (69 ± 20% versus 33 ± 7%) over the 1‐year period.

Putting people in the map: anthropogenic biomes of the world

Humans have fundamentally altered global patterns of biodiversity and ecosystem processes. Surprisingly, existing systems for representing these global patterns, including biome classifications, either ignore humans altogether or simplify human influence into, at most, four categories. Here, we present the first characterization of terrestrial biomes based on global patterns of sustained, direct human interaction with ecosystems. Eighteen “anthropogenic biomes” were identified through empirical analysis of global population, land use, and land cover. More than 75% of Earth's ice-free land showed evidence of alteration as a result of human residence and land use, with less than a quarter remaining as wildlands, supporting just 11% of terrestrial net primary production. Anthropogenic biomes offer a new way forward by acknowledging human influence on global ecosystems and moving us toward models and investigations of the terrestrial biosphere that integrate human and ecological systems.

Satellite‐based model detection of recent climate‐driven changes in northern high‐latitude vegetation productivity

We applied a satellite remote sensing based production efficiency model (PEM) using an integrated AVHRR and MODIS FPAR/LAI time series with a regionally corrected NCEP/NCAR reanalysis daily surface meteorology and NASA/GEWEX Surface Radiation Budget shortwave solar radiation inputs to assess annual terrestrial net primary productivity (NPP) for the pan‐Arctic basin and Alaska from 1983 to 2005. Our results show that low temperature constraints on Boreal‐Arctic NPP are decreasing by 0.43% per year (P < 0.001), whereas a positive trend in vegetation moisture constraints of 0.49% per year (P = 0.04) are offsetting the potential benefits of longer growing seasons and contributing to recent disturbances in NPP. The PEM simulations of NPP seasonality, annual anomalies and trends are similar to stand inventory network measurements of boreal aspen stem growth (r = 0.56; P = 0.007) and atmospheric CO2 measurement based estimates of the timing of growing season onset (r = 0.78; P < 0.001). Our results indicate that summer drought led to marked NPP decreases in much of the boreal forest region after the late‐1990s. However, seasonal low temperatures are still a dominant limitation on regional NPP. Despite recent drought events, mean annual NPP for the pan‐Arctic region showed a positive growth trend of 0.34% per year (20.27 TgC/a; P = 0.002) from 1983 to 2005. Drought induced NPP decreases may become more frequent and widespread as regional ecosystems adjust to a warmer, drier atmosphere, though the occurrence and severity of drought events will depend on future patterns of plant‐available moisture.

A new metric for evaluating the correspondence of spatial patterns in vegetation models

ABSTRACTAim To present a new metric, the ‘opposite and identity’ (OI) index, for evaluating the correspondence between two sets of simulated time‐series dynamics of an ecological variable.Innovation The OI index is introduced and its mathematical expression is defined using vectors to denote simulated variations of an ecological variable on the basis of the vector addition rule. The value of the OI index varies from 0 to 1 with a value 0 (or 1) indicating that compared simulations are opposite (or identical). An OI index with a value near 0.5 suggests that the difference in the amplitudes of variations between compared simulations is large. The OI index can be calculated in a grid cell, for a given biome and for time‐series simulations. The OI indices calculated in each grid cell can be used to map the spatial agreement between compared simulations, allowing researchers to pinpoint the extent of agreement or disagreement between two simulations. The OI indices calculated for time‐series simulations allow researchers to identify the time at which one simulation differs from another. A case study demonstrates the application and reliability of the OI index for comparing two simulated time‐series dynamics of terrestrial net primary productivity in Asia from 1982 to 2000. In the case study, the OI index performs better than the correlation coefficient at accurately quantifying the agreement between two simulated time‐series dynamics of terrestrial net primary productivity in Asia.Main conclusions The OI index provides researchers with a useful tool and multiple flexible ways to compare two simulation results or to evaluate simulation results against observed spatiotemporal data. The OI index can, in some cases, quantify the agreement between compared spatiotemporal data more accurately than the correlation coefficient because of its insensitivity to influential data and outliers and the autocorrelation of simulated spatiotemporal data.

Combining remote sensing data with process modelling to monitor boreal conifer forest carbon balances

Approaches combining satellite-based remote sensing data with ecosystem modelling offer potential for the accurate assessment of changes in forest carbon balances, for example, in support of emission credits under the Kyoto Protocol. We investigate the feasibility of two alternative methods of using satellite-derived data to constrain the behaviour of a dynamic ecosystem model, in order to improve the model's predictions of the net primary production (NPP) of conifer forests in northern Europe (4–30°E, 55–70°N). The ecosystem model incorporates a detailed description of forest stand structure and biogeochemical processes. The satellite product comprises multi-spectral reflectance data from the VEGETATION sensor. The first method combines satellite-based estimates of FPAR, the fraction of incoming photosynthetically active radiation absorbed by vegetation, with the model's predictions of the efficiency with which trees use the incoming radiation to fix carbon. Results obtained using this method averaged 0.22 kg C m −2 yr −1 for the NPP of conifer and mixed forests across the study area, and compared well with forest-inventory-based estimates for Sweden. The second method uses forest stand descriptions derived by application of an inverse radiation transfer scheme to VEGETATION data to prescribe stand structure in the ecosystem model simulations. Predictions obtained by this method averaged 0.31 kg C m −2 yr −1, somewhat high compared to forest inventory data for central and northern Sweden. Simulations by the ecosystem model when driven only by climate, CO 2 and soils data, but unconstrained by satellite information, yielded an average NPP of 0.41 kg C m −2 yr −1, which is likely to be an overestimate. Summed over the study area, the NPP estimates amounted to 0.16–0.23 Gt C yr −1, around 6–9% of the NPP of all boreal forest globally or 0.3–0.4% of terrestrial NPP globally. The investigated methods of combining process modelling and products derived from remote sensing data offer promise as a step towards the development of operational tools for monitoring forest carbon balances at large scales.

Links between Terrestrial Primary Production and Bacterial Production and Respiration in Lakes in a Climate Gradient in Subarctic Sweden

We compared terrestrial net primary production (NPP) and terrestrial export of dissolved organic carbon (DOC) with lake water heterotrophic bacterial activity in 12 headwater lake catchments along an altitude gradient in subarctic Sweden. Modelled NPP declined strongly with altitude and annual air temperature decreases along the altitude gradient (6°C between the warmest and the coldest catchment). Estimated terrestrial DOC export to the lakes was closely correlated to NPP. Heterotrophic bacterial production (BP) and respiration (BR) were mainly based on terrestrial organic carbon and strongly correlated with the terrestrial DOC export. Excess respiration over PP of the pelagic system was similar to net emission of CO2 in the lakes. BR and CO2 emission made up considerably higher shares of the terrestrial DOC input in warm lakes than in cold lakes, implying that respiration and the degree of net heterotrophy in the lakes were dependant not only on terrestrial export of DOC, but also on characteristics in the lakes which changed along the gradient and affected the bacterial metabolization of allochthonous DOC. The study showed close links between terrestrial primary production, terrestrial DOC export and bacterial activity in lakes and how these relationships were dependant on air temperature. Increases in air temperature in high latitude unproductive systems might have considerable consequences for lake water productivity and release of CO2 to the atmosphere, which are ultimately determined by terrestrial primary production.

Comprehensive analysis of the impact of climatic changes on Chinese terrestrial net primary productivity

Recent climatic changes have affected terrestrial net primary productivity (NPP). This paper presents an investigation of the impact of climatic changes on Chinese terrestrial vegetation NPP by analyzing 18 years’ (1982 to 1999) climatic data and satellite observations of vegetation activity. Results indicate that climatic changes in China have eased some critical climatic constraint on plant growth. (1) From 1982 to 1999, modeled NPP increased by 1.42%·a−1 in water-limited regions of Northwest China, 1.46%·a−1 in temperature-limited regions of Northeast China and Tibet Plateau, and 0.99%·a−1 in radiation-limited regions of South China and East China. (2) NPP increased by 24.2%, i.e. 0.76 petagram of carbon (Pg C) over 18 years in China. Changes in climate (with constant vegetation) directly contributed nearly 11.5% (0.36 Pg C). Changes in vegetation (with constant climate) contributed 12.4% (0.40 Pg C), possibly as a result of climate-vegetation feedbacks, changes in land use, and growth stimulation from other mechanisms. (3) Globally, NPP declined during all three major El Nino events (1982 to 1983, 1987 to 1988, and 1997 to 1998) between 1982 and 2000, but Chinese vegetation productivity responded differently to them because of the monsoon dynamics. In the first three events (1982 to 1983, 1987 to 1988, and 1992), Chinese vegetation NPP declined, while in the later two events (1993, 1997 to 1998) increasing obviously.

Impacts of large‐scale oscillations on pan‐Arctic terrestrial net primary production

Analyses of regional climate oscillations and satellite remote sensing derived net primary production (NPP) and growing season dynamics for the pan‐Arctic region indicate that the oscillations influence NPP by regulating seasonal patterns of low temperature and moisture constraints to photosynthesis. Early‐spring (Feb–Apr) patterns of the Arctic Oscillation (AO) are proportional to growing season onset (r = −0.653; P = 0.001), while growing season patterns of the Pacific Decadal Oscillation (PDO) are proportional to plant‐available moisture constraints to NPP (Im) (r = −0.471; P = 0.023). Relatively strong, negative PDO phases from 1988–1991 and 1998–2002 coincided with prolonged regional droughts indicated by a standardized moisture stress index. These severe droughts resulted in widespread reductions in NPP, especially for relatively drought prone boreal forest and grassland/cropland ecosystems. The influence of AO and PDO patterns on northern vegetation productivity appears to be decreasing and increasing, respectively, as low temperature constraints to plant growth relax and NPP becomes increasingly limited by available water supply under a warming climate.

Assessing the impacts of agricultural intensification on biodiversity: a British perspective

Agricultural intensification is best considered as the level of human appropriation of terrestrial net primary production. The global value is set to increase from 30%, increasing pressures on biodiversity. The pressures can be classified in terms of spatial scale, i.e. land cover, landscape management and crop management. Different lowland agricultural landscapes in Great Britain show differences among these pressures when habitat diversity and nutrient surplus are used as indicators. Eutrophication of plants was correlated to N surplus, and species richness of plants correlated with broad habitat diversity. Bird species diversity only correlated with habitat diversity when the diversity of different agricultural habitats was taken into account. The pressures of agricultural change may be reduced by minimizing loss of large habitats, minimizing permanent loss of agricultural land, maintaining habitat diversity in agricultural landscapes in order to provide ecosystem services, and minimizing pollution from nutrients and pesticides from the crops themselves. While these pressures could potentially be quantified using an internationally consistent set of indicators, their impacts would need to be assessed using a much larger number of locally applicable biodiversity indicators.

From Miami to Madison: Investigating the relationship between climate and terrestrial net primary production

The 1973 “Miami Model” was the first global‐scale empirical model of terrestrial net primary productivity (NPP), and its simplicity and relative accuracy has led to its continued use. However, improved techniques to measure NPP in the field and the expanded spatial and temporal range of observations have prompted this study, which reexamines the relationship of climatic variables to NPP. We developed several statistical models with paired climatic variables in order to investigate their relationships to terrestrial NPP. A reference data set of 3023 NPP field observations was compiled for calibration and parameter optimization. In addition to annual mean temperature and precipitation, as in the Miami Model, we chose more ecologically relevant climatic variables including growing degree‐days, a soil moisture stress index, and photosynthetically active radiation (PAR). Calculated annual global NPP ranged from 36 to 74 Pg‐C yr−1, comparable with previous studies. Comparisons of geographic patterns of NPP were made using biome and latitudinal averages.

Isoprene emission from terrestrial ecosystems in response to global change: minding the gap between models and observations

Coupled surface-atmosphere models are being used with increased frequency to make predictions of tropospheric chemistry on a 'future' earth characterized by a warmer climate and elevated atmospheric CO2 concentration. One of the key inputs to these models is the emission of isoprene from forest ecosystems. Most models in current use rely on a scheme by which global change is coupled to changes in terrestrial net primary productivity (NPP) which, in turn, is coupled to changes in the magnitude of isoprene emissions. In this study, we conducted measurements of isoprene emissions at three prominent global change experiments in the United States. Our results showed that growth in an atmosphere of elevated CO2 inhibited the emission of isoprene at levels that completely compensate for possible increases in emission due to increases in aboveground NPP. Exposure to a prolonged drought caused leaves to increase their isoprene emissions despite reductions in photosynthesis, and presumably NPP. Thus, the current generation of models intended to predict the response of isoprene emission to future global change probably contain large errors. A framework is offered as a foundation for constructing new isoprene emission models based on the responses of leaf biochemistry to future climate change and elevated atmospheric CO2 concentrations.

Global primary production

Global primary production

Sensitivity of pan‐Arctic terrestrial net primary productivity simulations to daily surface meteorology from NCEP‐NCAR and ERA‐40 reanalyses

We applied a terrestrial net primary production (NPP) model driven by satellite remote sensing observations of vegetation properties and daily surface meteorology from the 45‐year ECMWF Re‐Analysis (ERA‐40) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP‐NCAR) reanalysis (NNR) to assess NPP spatial and temporal variability for the pan‐Arctic basin and Alaska from 1982 to 2000. Sensitivity analysis of the production efficiency model (PEM) to uncertainties in surface meteorological inputs indicate that ERA‐40 solar radiation and NNR solar radiation and surface temperatures are the primary sources of PEM‐based NPP uncertainty for the region. Considerable positive bias in solar radiation inputs relative to surface observation networks resulted in overprediction of annual NPP by approximately 35.2 and 61.6% using ERA‐40 and NNR inputs, respectively. Despite these uncertainties, both reanalysis products captured the major annual anomalies and trends in surface meteorology for the domain. The two reanalysis products also produced similar NPP spatial patterns for 74.7% of the domain, and similar annual anomalies and temporal trends, though there were significant regional differences particularly for Eurasia. A simple correction method based on a sensitivity experiment between reanalysis and surface station meteorological measurements produced generally consistent NPP results that were considerably smaller than PEM simulations derived from uncorrected reanalysis drivers. The results of this study identify major sources of uncertainty in reanalysis‐based surface meteorology, and associated impacts on regional NPP simulations of the northern high latitudes.

Use of ISLSCP II data to intercompare and validate the terrestrial net primary production in a land surface model coupled to a general circulation model

Using the global terrestrial NPP and climate data from International Satellite Land Surface Climatology Project Initiative II (ISLSCP II) and additional NPP data, we validated the NPP simulations and explored the relationship between NPP and climate variation in a global two‐way coupled model AVIM‐GOALS. The strength of this study is that the global simulations produced will enhance interactive climate and vegetation study; however, the weakness is that the NPP distribution is not fully reproduced in some regions, because of the coarse model resolution and climate biases. Global NPP is spatially consistent with IGBP NPP and MODIS data, though there is a discrepancy in NPP (significantly lower values) for boreal forests and tundra, due to the underestimated temperature. The NPP distribution in China indicates agreement with IGBP data, but the IGBP data in northeast China (around 48°N) seem to be slightly high in contrast with other modeled and estimated NPP. The spatial structure of NPP in USA and Australia roughly corresponds to the IGBP NPP data and GPPDI Gridded data, and a possible lower value of GPPDI data in central Australia exists, in contrast with other NPP data. The globally averaged NPP of 447.47 g C m−2 year−1 is close to the 450.42 g C m−2 year−1 from IGBP data. The global relative error of simulated NPP against IGBP data is about 20% and is comparable to other global biogeochemical models. The meridional variation of globally zonal mean NPP corresponds more to the meridional change of precipitation than temperature. The global NPP for all vegetation types is highly statistically significant in correlation with precipitation.

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal–spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gC m −2 yr −1, respectively; the total GPP and mean GPP were 4.418 GtC and 465 gC m −2 yr −1; and the total RA and mean RA were 2.227 GtC and 234 gC m −2 yr −1, respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.