Grassland Aboveground Net Primary Productivity Research Articles

Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery.

This study aimed to evaluate changes in the aboveground net primary productivity (ANPP) of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration) were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

Climatic controls of aboveground net primary production in semi-arid grasslands along a latitudinal gradient portend low sensitivity to warming.

Although climate models forecast warmer temperatures with a high degree of certainty, precipitation is the primary driver of aboveground net primary production (ANPP) in most grasslands. Conversely, variations in temperature seldom are related to patterns of ANPP. Thus forecasting responses to warming is a challenge, and raises the question: how sensitive will grassland ANPP be to warming? We evaluated climate and multi-year ANPP data (67 years) from eight western US grasslands arrayed along mean annual temperature (MAT; ~7-14 °C) and mean annual precipitation (MAP; ~250-500 mm) gradients. We used regression and analysis of covariance to assess relationships between ANPP and temperature, as well as precipitation (annual and growing season) to evaluate temperature sensitivity of ANPP. We also related ANPP to the standardized precipitation evaporation index (SPEI), which combines precipitation and evapotranspiration to better represent moisture available for plant growth. Regression models indicated that variation in growing season temperature was negatively related to total and graminoid ANPP, but precipitation was a stronger predictor than temperature. Growing season temperature was also a significant parameter in more complex models, but again precipitation was consistently a stronger predictor of ANPP. Surprisingly, neither annual nor growing season SPEI were as strongly related to ANPP as precipitation. We conclude that forecasted warming likely will affect ANPP in these grasslands, but that predicting temperature effects from natural climatic gradients is difficult. This is because, unlike precipitation, warming effects can be positive or negative and moderated by shifts in the C3/C4 ratios of plant communities.

Functional response of U.S. grasslands to the early 21st-century drought.

Grasslands across the United States play a key role in regional livelihood and national food security. Yet, it is still unclear how this important resource will respond to the prolonged warm droughts and more intense rainfall events predicted with climate change. The early 21st-century drought in the southwestern United States resulted in hydroclimatic conditions that are similar to those expected with future climate change. We investigated the impact of the early 21st-century drought on aboveground net primary production (ANPP) of six desert and plains grasslands dominated by C4 (warm season) grasses in terms of significant deviations between observed and expected ANPP. In desert grasslands, drought-induced grass mortality led to shifts in the functional response to annual total precipitation (P(T)), and in some cases, new species assemblages occurred that included invasive species. In contrast, the ANPP in plains grasslands exhibited a strong linear function of the current-year P(T) and the previous-year ANPP, despite prolonged warm drought. We used these results to disentangle the impacts of interannual total precipitation, intra-annual precipitation patterns, and grassland abundance on ANPP, and thus generalize the functional response of C4 grasslands to predicted climate change. This will allow managers to plan for predictable shifts in resources associated with climate change related to fire risk, loss of forage, and ecosystem services.

Spatiotemporal dynamics of grassland aboveground net primary productivity and its association with climatic pattern and changes in Northern China

Various vegetation indices and environmental parameters derived from remote sensing were used to investigate the spatiotemporal dynamics of grassland aboveground net primary productivity (ANPP) in Northern China from 2000 to 2011. An integrated model for grassland ANPP estimation was proposed based on 209 field observations and the corresponding MODIS reflectance products. Five samples for each of five grassland types were extracted randomly to validate the remote sensing model. The model was then used to derive the spatial and temporal patterns of ANPP for the five grassland types. Additionally, the correlations of ANPP to land surface temperature (LST) and land surface water index (LSWI) were analyzed to explore the response of ANPP to changes in hydrothermal conditions. Results show that different vegetation indices have different sensitivities to diverse grassland types. A notable gradient of ANPP in grasslands from west to east is obvious, and a slight increase in annual ANPP for each type of grassland during 2000–2011 is observed. The spatial pattern of ANPP in grasslands is found to correlate with the gradients of LST and LSWI. The temporal correlation of ANPP in grasslands is significantly negative to LST, but positive to LSWI. For alpine steppe and desert steppe, the ANPP is most sensitive to the change of LST; for desert steppe, the ANPP has the highest sensitivity to the change of LSWI. With this improved understanding of the spatiotemporal dynamics of ANPP as well as the effects of climate change, an efficient and sustainable use of China's grasslands could be possible.

Estimating Aboveground Net Primary Production in Grasslands: A Comparison of Nondestructive Methods

Abstract Aboveground net primary production (ANPP) is an important ecosystem property that is affected by environmental variability. ANPP in grasslands is typically measured by clipping peak live plant material. However, this method is time intensive (and therefore expensive), making it difficult to capture spatial and temporal variability. Additionally, it is impractical to use a destructive method to estimate ANPP in long-term, permanent plots. Thus, many double-sampling techniques have been developed to reduce costs and increase sample size. The objective of our study was to assess the accuracy and precision of nondestructive techniques to estimate ANPP as supplements to the traditional method of peak biomass harvest at two grassland sites. We harvested biomass and compared estimates from the same plots to 1) canopy interception using a point frame, 2) green cover estimates derived from a digital camera, and 3) reflectance measurements using a handheld radiometer. We calculated the optimum allocation o...

Influence of early dry season fires on primary production in western Serengeti grasslands, Tanzania

Short-term, i.e. 4-9 weeks aboveground net primary production (ANPP) temporal patterns during the first post-fire year in western Seren-geti National Park, and potential differences in the factors limiting ANPP between burnt and non burnt grasslands were examined and es-tablished. Fire stimulated growth at early post-fire stages, even during the dry season, July-October and led to larger increments in green phytomass compared to the non burnt grassland at the onset of short rains, Octo-ber-December. Further, ANPP in burnt plots correlated well with the ratio leaf/total standing phytomass suggesting that the accumulation of standing dead material can be a limiting factor to ANPP in burnt grass-lands. However, ANPP in burnt plots was unrelated to rainfall contrary to earlier arguments, but reached peak earlier and declined early in the rain season, perhaps due to the interactive effects of fire and grazing in the area. In non burnt plots, the temporal change in ANPP was more related to rainfall availability, at least until mid-growing season. Also, the phytomass structure differed between burnt and non burnt grasslands, and together with litter did not recover to non burnt levels within the first post-fire year. The study has demonstrated that the desire of the fire man-agement program in Serengeti National Park, which is to supply green forage to both migra-tory and resident populations during dry season is being fulfilled.

Climate change alters interannual variation of grassland aboveground productivity: evidence from a 22-year measurement series in the Inner Mongolian grassland

Climate change is known to influence interannual variation in grassland aboveground net primary productivity (ANPP), or seasonal biomass, but direct, long-term ground observations are rare. We present a 22-year (1982-2003) measurement series from the Inner Mongolia grassland, China, to examine the effect of climate change on interannual variations in ANPP and monthly aboveground biomass (MAB). ANPP exhibited no increase over 1982-2003 but there was an association with previous-year precipitation. MAB in May increased by 21.8% from 47.8 g m(-2) (averaged for 1982-1984) to 58.2 g m(-2) (2001-2003), whereas there was no significant variation in June, July and August, and a decrease of 29.7% in September. The MAB increase in May was correlated with increases in precipitation and temperature in the preceding months. These findings suggest that the effects of climate change on grassland production vary throughout the growing season, with warmer and wetter springs resulting in increased biomass early in the growing season, and drier falls causing a decrease in biomass late in the growing season.

DEFOLIATION SYNCHRONIZES ABOVEGROUND GROWTH OF CO-OCCURRING C4GRASS SPECIES

The aboveground net primary productivity (ANPP) of grass communities in grasslands and savannas is primarily determined by precipitation quantity. Recent research, motivated by predictions of changes in the distribution of rainfall events by global climate change models, indicates that ANPP may be affected by rainfall distribution as much as by annual totals. Grazing and community composition are also known to affect grassland ANPP. The manner in which interactions between rainfall distribution, grazing, and community composition affect the relationship between precipitation and ANPP represents a critical knowledge gap. The effects of community composition and grazing on aboveground growth responses to intraseasonal variation in water availability were investigated at seven grassland sites with a nonselective clipping experiment. The aboveground growth of the dominant C4 species at each site was measured at regular intervals for 2-3 growing seasons in the presence or absence of regular defoliation. In the absence of defoliation, there was a general lack of synchrony of intraseasonal growth among co-occurring species. Variation in growth rates was high and was only partially explained by variation in rainfall. Regular defoliation increased growth synchrony at all sites, but changes in growth responses to rainfall varied between sites. These results suggest that community composition will be important in determining ANPP-precipitation relationships under conditions of altered rainfall distribution. However this effect appears to be a result of species responding differently to soil water or other resources rather than to rainfall per se. Grazing may override the effects of community composition by reducing differences in growth patterns between species and has the potential to weaken precipitation controls on ANPP.

Responses of a California annual grassland to litter manipulation

AbstractQuestion:What are the physical and chemical effects of plant litter on annual grassland community composition, above‐ground net primary production (ANPP), and density?Location:California annual grassland.Methods:We manipulated litter and light levels independently and in concert. Litter removal and litter addition treatments tested both the physical and chemical impacts of litter's presence. We additionally simulated the effect of litter physical shading by using shade cloth, and added powdered litter to test for the chemical impacts of decomposing litter.Results:Increased whole litter and shading decreased grass germination and establishment, but not that of forbs or legumes. Species shifts occurred within all groups across treatments, including a transition from small‐seeded to large‐seeded grass and legume species with increased shading. ANPP was highest in control plots (473 ± 59 g/m2), and species richness was highest in litter removal plots. While the physical effects of litter via shading were significant, the chemical effects of adding powdered litter were negligible.Conclusions:This work suggests that over one growing season, the physical impacts of litter are more important than chemical impacts in shaping community structure and ANPP in annual grasslands. Changes in light availability with altered litter inputs drive shifts in species and functional group composition. Litter feedbacks to ANPP and species composition of local patches may help maintain diversity and stabilize ANPP in this grassland.

Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China

Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites (including temperate meadow steppe, temperate steppe, temperate desert steppe and alpine meadow) were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity (ANPP) and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation (MAP) was the main factor determining spatial distribution of grassland ANPP ( r 2 = 0.61, P < 0.01); while temporally, no significant relationship was found between the variance of ANPP and inter-annual precipitation for the four types of grassland. However, after dividing annual precipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow steppe, the key variable determining inter-annual change of ANPP was last August—May precipitation ( r 2 = 0.47, P < 0.01); for the temperate steppe, the key variable was July precipitation ( r 2 = 0.36, P = 0.02); for the temperate desert steppe, the key variable was April—June precipitation ( r 2 = 0.51, P < 0.01); for the alpine meadow, the key variable was last September—May precipitation ( r 2 = 0.29, P < 0.05). In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.

VEGETATION STRUCTURE CONSTRAINS PRIMARY PRODUCTION RESPONSE TO WATER AVAILABILITY IN THE PATAGONIAN STEPPE

Grassland aboveground net primary production (ANPP) increases linearly with precipitation in space and time, but temporal models relating time series of ANPP and annual precipitation for single sites show lower slopes and regression coefficients than are shown by spatial models. The analysis of several ANPP time series showed lags in the ecosystem response to increased water availability, which may explain the difference between spatial and temporal models. The lags may result from constraints that ecosystems experience after drought. Our objective was to explore the structural constraints of the ANPP response to rainfall variability in a semiarid ecosystem, the Patagonian steppe, in southern Argentina. We designed a 3-yr rainfall manipulation experiment where we decreased water input with rainout shelters during two consecutive years, which included three levels of rainfall interception (30%, 55%, and 80%) and a control. In the third year, we irrigated one-half of the plots of each rainfall-interception treatment. We evaluated the immediate effects of drought on current-year ANPP and the effects of previous-year drought on vegetation recovery after water supplementation. ANPP (g x m(-2) x yr(-1)) was linearly related to annual precipitation input (APPT; mm/yr) along the experimental precipitation gradient (ANPP = 0.13 x APPT + 58.3; r2 = 0.34, P < 0.01), and this relationship was mostly accounted for by changes in the ANPP of grasses. Plant density (D; no. individuals/mm2) was related to the precipitation received during the drought period (D = 0.11 x APPT + 18; r2 = 0.39, P < 0.05). The recovery of plants after irrigation was lower for those plots that had experienced experimental drought the previous years relative to controls, and the lags were proportional to the intensity of drought. Therefore, our results suggest that the density of plants may constrain the recovery of vegetation after drought, and these constraints may determine lags that limit the capacity of the ecosystem to take advantage of wet years after dry years.

Intra-annual rainfall variability and grassland productivity: can the past predict the future?

Precipitation quantity has been shown to influence grassland aboveground net primary productivity (ANPP) positively whereas experimental increases in of temporal variability in water availability commonly exhibit a negative relationship with ANPP. We evaluated long term ANPP datasets from the Konza Prairie Long Term Ecological Research (LTER) program (1984–1999) to determine if similar relationships could be identified based on patterns of natural variability (magnitude and timing) in precipitation. ANPP data were analyzed from annually burned sites in native mesic grassland and productivity was partitioned into graminoid (principally C4 grasses) and forb (C3 herbaceous) components. Although growing season precipitation amount was the best single predictor of total and grass ANPP (r 2=0.62), several measures of precipitation variability were also significantly and positively correlated with productivity, independent of precipitation amount. These included soil moisture variability, expressed as CV, for June (r 2=0.45) and the mean change in soil moisture between weekly sampling periods in June and August (%wv) (r 2=0.27 and 0.32). In contrast, no significant relationships were found between forb productivity and any of the precipitation variables (p>0.05). A multiple regression model combining precipitation amount and both measures of soil moisture variability substantially increased the fit with productivity (r 2=0.82). These results were not entirely consistent with those of short-term manipulative experiments in the same grassland, however, because soil moisture variability was often positively, not negatively related to ANPP. Differences in results between long and short term experiments may be due to low variability in the historic precipitation record compared to that imposed experimentally as experimental levels of variability exceeded the natural variability of this dataset by a factor of two. Thus, forecasts of ecosystem responses to climate change (i.e. increased climatic variability), based on data constrained by natural and recent historical rainfall patterns may be inadequate for assessing climate change scenarios if precipitation variability in the future is expected to exceed current levels.

Regional analysis of climate, primary production, and livestock density in inner Mongolia.

Overstocking is believed to be one of the principal causes for grassland degradation in northern China. For this reason, quantification of overstocking and spatiotemporal analysis are needed for this area. In this study, the relationship between annual rainfall and grassland aboveground net primary production (ANPP) was analyzed using data from 1982 to 1991 in the Inner Mongolia Autonomous Region (IMAR), China. Subsequently, rainfall-based livestock carrying capacity was estimated and combined with livestock density calculated from county-level livestock data from 1982 to 1991 to determine spatial and temporal patterns of a stocking rate index and its relationship with climatic factors. The results indicate the following. First, there was a significant linear relationship between annual rainfall and ANPP in IMAR and the slope of ANPP versus rainfall was greater than those found in South America and Africa, indicating higher rain-use efficiency. Second, temporally averaged livestock density showed overstocking in most of the rural counties except for those in the cold north, where human populations are low and transportation systems are poor. Third, the stocking rate index increased with temperature, from less than 1.0 in the north, to greater than 2.0 in most of the southern IMAR. Within the central IMAR, the index increased from west to east, along the gradient of increasing rainfall. Fourth, long-term dynamics of livestock density depicted continuous overstocking, more than 20%, from 1982 to 1991 along the western part of the NorthEast China Transect (NECT) within IMAR. Spatial planning of livestock densities according to carrying capacities and improved pastoral management are needed in this area.

Estimating net primary productivity of grasslands from field biomass measurements in temperate northern China

Data on field biomass measurements in temperate grasslands of northern China (141 samples from 74 sites) were obtained from 23 Chinese journals, reports and books. Net primary productivity (NPP) of grasslands was estimated using three algorithms (peak live biomass, peak standing crop and maximum minus minimum live biomass), respectively, based on availability of biomass data in sites. 135 samples which have aboveground biomass (AGB) measurements, have peak AGB ranges from 20 to 2021 g m–2 (mean = 325.3) and the aboveground NPP (ANPP) ranges from 15 to 1647.1 g m–2 per year (mean = 295.7). 72 samples which have belowground biomass (BGB) measurements, have peak BGB ranges from 226.5 to 12827.5 g m–2 (mean = 3116) and the belowground NPP (BNPP) ranges from 15.8 to 12827.5 g m–2 per year (mean = 2425.6). In total 66 samples have the total NPP (TNPP), ranging from 55.3 to 13347.8 g m–2 per year (mean = 2980.3). Mean peak biomass and NPP varied from different geographical sampling locations, but they had a general rough regularity in ten grasslands. Meadow, mountain and alpine grasslands had high biomass and NPP (sometimes including saline grassland). Forested steppe, saline grassland and desert had median values. Meadowed and typical steppes had low biomass and NPP (sometimes including desert). The lowest biomass and NPP occurred in deserted steppe and stepped desert. Grassland ANPP has significant positive relationships with annual and summer precipitation as well as summer temperature (all p<0.01). However, grassland BNPP and TNPP have more significant negative relationships with summer temperature (p<0.01) than with annual temperature (p<0.05). The analysis of climate – productivity correlations implied that aboveground productivity is more controlled by rainfall, whereas belowground and total productivity is more influenced by temperature in the temperate grasslands of northern China. The present study might underestimate grassland NPP in northern China due to limitation of biomass measurements. Data on relative long-term aboveground and belowground biomass dynamics, as well as data of standing dead matter, litterfall, decomposition and turnover, are required if grassland NPP is to be more accurately estimated and the role of temperate grasslands in the regional to global carbon cycles is to be fully appreciated.

Frequency and Extent of Water Limitation to Primary Production in a Mesic Temperate Grassland

The frequency and extent of water limitation to aboveground net primary production (ANPP) in a mesic grassland in NE Kansas (Konza Prairie, USA) was assessed with an 8-year irrigation experiment. Since 1991, transects spanning upland and lowland sites in annually burned, ungrazed tallgrass prairie were provided with supplemental water to satisfy evapotranspirational demands. This protocol minimized water limitations during the growing season, as well as interannual variability in water stress. Irrigation of this mesic grassland increased ANPP in 6 of 8 years by an average of 26% when compared to control transects. Although interannual variation in ANPP was greater in uplands than lowlands at nominal levels of precipitation, reducing interannual variability in water availability via irrigation eliminated topographic differences; the irrigation protocol also reduced interannual variability in ANPP by as much as 40%. The addition of supplemental water enabled us to extend the relationship between annual precipitation and ANPP in grasslands to precipitation levels (average, 1153 mm; maximum, 1346 mm) similar to those experienced by more mesic grasslands that today exist only as remnants several hundred kilometers east of Kansas. This relationship was linear (r 2= 0.81), with maximum ANPP (738 g/m2) similar to values reported for sites in Illinois and Wisconsin. After 8 years of irrigation, production of the C3 forb component was twice that in control sites. These results indicate that water limitations in grasslands at the western edge of the presettlement extent of tallgrass prairie affect ANPP in most years and that this high frequency of water limitation may lead to greater dominance of the C4 grasses than is seen in more eastern grassland sites.