Grassland Primary Production Research Articles

Unveiling the Role of Spatial Functional Trait Variations on Grassland Primary Productivity at France Scale

Unveiling the Role of Spatial Functional Trait Variations on Grassland Primary Productivity at France Scale

Nitrogen addition regulates the effects of variation in precipitation patterns on plant biomass formation and allocation in a Leymus chinensis grassland of northeast China.

Global warming is predicted to change precipitation amount and reduce precipitation frequency, which may alter grassland primary productivity and biomass allocation, especially when interact with other global change factors, such as nitrogen deposition. The interactive effects of changes in precipitation amount and nitrogen addition on productivity and biomass allocation are extensively studied; however, how these effects may be regulated by the predicted reduction in precipitation frequency remain largely unknown. Using a mesocosm experiment, we investigated responses of primary productivity and biomass allocation to the manipulated changes in precipitation amount (PA: 150mm, 300mm, 450mm), precipitation frequency (PF: medium and low), and nitrogen addition (NA: 0 and 10 g N m-2 yr-1) in a Leymus chinensis grassland. We detected significant effects of the PA, PF and NA treatments on both aboveground biomass (AGB) and belowground biomass (BGB); but the interactive effects were only significant between the PA and NA on AGB. Both AGB and BGB increased with an increment in precipitation amount and nitrogen addition; the reduction in PF decreased AGB, but increased BGB. The reduced PF treatment induced an enhancement in the variation of soil moisture, which subsequently affected photosynthesis and biomass formation. Overall, there were mismatches in the above- and belowground biomass responses to changes in precipitation regime. Our results suggest the predicted changes in precipitation regime, including precipitation amount and frequency, is likely to alter primary productivity and biomass allocation, especially when interact with nitrogen deposition. Therefore, predicting the influence of global changes on grassland structure and functions requires the consideration of interactions among multiple global change factors.

Evolutionary history shapes grassland productivity through opposing effects on complementarity and selection.

Phylogenetic diversity (PD), the evolutionary history of the organisms comprising a community, is increasingly recognized as an important driver of ecosystem function. However, biodiversity-ecosystem function experiments have rarely included PD as an a priori treatment. Thus, PD's effects in existing experiments are often confounded by covarying differences in species richness and functional trait diversity (FD). Here we report an experimental demonstration of strong PD effects on grassland primary productivity that are independent of FD, which was separately manipulated, and species richness, which was planted uniformly high to mimic diverse natural grasslands. Partitioning diversity effects demonstrated that higher PD increased complementarity (niche partitioning and/or facilitation) but lowered selection effects (probability of sampling highly productive species). Specifically, for every 5% increase in PD, complementarity increased by 26% on average (±8% SE), while selection effects decreased more modestly (8 ± 16%). PD also shaped productivity through clade-level effects on functional traits, that is, trait values associated with particular plant families. This clade effect was most pronounced in the Asteraceae (sunflower family), which, in tallgrass prairies, generally comprises tall, high-biomass species with low phylogenetic distinctiveness. FD also reduced selection effects but did not alter complementarity. Our results show that PD, independent of richness and FD, mediates ecosystem function through contrasting effects on complementarity and selection. This adds to growing evidence that consideration of phylogenetic dimensions of biodiversity can advance ecological understanding and inform conservation and restoration.

Species richness and asynchrony maintain the stability of primary productivity against seasonal climatic variability.

The stability of grassland communities informs us about the ability of grasslands to provide reliable services despite environmental fluctuations. There is large evidence that higher plant diversity and asynchrony among species stabilizes grassland primary productivity against interannual climate variability. Whether biodiversity and asynchrony among species and functional groups stabilize grassland productivity against seasonal climate variability remains unknown. Here, using 29-year monitoring of a temperate grassland, we found lower community temporal stability with higher seasonal climate variability (temperature and precipitation). This was due to a combination of processes including related species richness, species asynchrony, functional group asynchrony and dominant species stability. Among those processes, functional group asynchrony had the strongest contribution to community compensatory dynamics and community stability. Based on a long-term study spanning 29 years, our results indicate that biodiversity and compensatory dynamics a key for the stable provision of grassland function against increasing seasonal climate variability.

Real-time forests monitoring system based on IOT for forest and grassland primary production and biodiversity conservation

Real-time forests monitoring system based on IOT for forest and grassland primary production and biodiversity conservation

Estimation of the Grassland Aboveground Biomass of the Inner Mongolia Plateau Using the Simulated Spectra of Sentinel-2 Images

An accurate assessment of the grassland aboveground biomass (AGB) is important for analyzing terrestrial ecosystem structures and functions, estimating grassland primary productivity, and monitoring climate change and carbon/nitrogen circulation on a global scale. Multispectral satellites with wide-width advantages, such as Sentinel-2, have become the inevitable choice for the large-scale monitoring of grassland biomass on regional and global scales. However, the spectral resolution of multispectral satellites is generally low, which limits the inversion accuracy of grassland AGB and restricts further application in large-scale grassland monitoring. For this reason, a satellite-scale simulated spectra method was proposed to enhance the spectral information of the Sentinel-2 data, and a simulated spectrum (SS) was constructed using this algorithm. Then, the raw spectrum (RS) of Sentinel-2 and the SS were used as data sources to calculate the vegetation indices (RS-VIs and SS-VIs, which represent vegetation indices calculated using RS and SS data, respectively), and the multi-granularity spectral segmentation algorithm (MGSS) was employed to extract spectral segmentation features (RS-SF and SS-SF, which represent segmentation features extracted by RS and SS data, respectively). Following this, these spectral features (RS-SF, SS-SF, RS-VIs, and SS-VIs) were used to estimate AGB by partial least-squares regression (PLSR) and multiple stepwise regression (MSR) models. Finally, the spatial distribution law and the reasons for the latitude zone of the Inner Mongolia Plateau were analyzed, based on precipitation, the average temperature, topography, etc. The conclusions are as follows. Firstly, the SS has more spectral information and its sensitivity to biomass is higher than the RS of Sentinel-2 in some bands, and the correlation between the SS-VIs and biomass is higher than that of the RS-VIs. Secondly, among the spectral features, the most accurate AGB estimation was obtained by SS-SF, which gave R2 = 0.95. The root mean square error (RMSE) was 10.86 g/m2 and the estimate accuracy (EA) was 82.84% in the MSR model. Additionally, RMSE = 10.89 g/m2 and EA = 82.78% in the PLSR model. Compared with the traditional estimation methods using RS and VI, R2 was increased by at least 0.2, RMSE was reduced by at least 14.08 g/m2, and EA was increased by 22.26%. Therefore, the simulated spectra method can help improve the estimation accuracy of AGB, and a new idea about regional and global large-scale biomass acquisition is provided.

Effect of nitrification inhibitor on plant biomass and N2O emission rates in alpine meadows on the Tibetan Plateau

ABSTRACTTreatment with nitrification inhibitors, such as dicyandiamide (DCD) and 3,4-dimethylpyrazole phosphate (DMPP) have been strongly indicated to increase grassland biomass and mitigate soil N2O emission rates. However, the responses of both alpine meadow aboveground biomass and N2O emission rates to nitrification inhibitors remains unclear. We separately applied three doses of DCD and DMPP to alpine grassland soils with three duplicates. The biomass and N2O emission rates were subsequently measured by a clear-cut method and in-situ static chamber gas chromatography during the growing season. Our findings indicated that aboveground biomass increased significantly, and N2O emission rate decreased significantly at 6.8 kg ha−1 DCD and DMPP. Furthermore, the biomass increase effect was more significant than the N2O emission rate mitigation effect (p < 0.05). The highest ratios of DCD treatments on meadow production increase and N2O emission rate decrease were 27.2% and 36.3%, respectively. Our findings provide insight into the enhanced grassland primary production and decreased N2O flux by nitrification inhibitor treatment in alpine meadows, which may be beneficial to help mitigate global warming.

Nutrient addition increases grassland sensitivity to droughts.

Grasslands worldwide are expected to experience an increase in extreme events such as drought, along with simultaneous increases in mineral nutrient inputs as a result of human industrial activities. These changes are likely to interact because elevated nutrient inputs may alter plant diversity and increase the sensitivity to droughts. Dividing a system's sensitivity to drought into resistance to change during the drought and rate of recovery after the drought generates insights into different dimensions of the system's resilience in the face of drought. Here, we examine the effects of experimental nutrient fertilization and the resulting diversity loss on the resistance to and recovery from severe regional droughts. We do this at 13 North American sites spanning gradients of aridity, five annual grasslands in California, and eight perennial grasslands in the Great Plains. We measured rate of resistance as the change in annual aboveground biomass (ANPP) per unit change in growing season precipitation as conditions declined from normal to drought. We measured recovery as the change in ANPP during the postdrought period and the return to normal precipitation. Resistance and recovery did not vary across the 400-mm range of mean growing season precipitation spanned by our sites in the Great Plains. However, chronic nutrient fertilization in the Great Plains reduced drought resistance and increased drought recovery. In the California annual grasslands, arid sites had a greater recovery postdrought than mesic sites, and nutrient addition had no consistent effects on resistance or recovery. Across all study sites, we found that predrought species richness in natural grasslands was not consistently associated with rates of resistance to or recovery from the drought, in contrast to earlier findings from experimentally assembled grassland communities. Taken together, these results suggest that human-induced eutrophication may destabilize grassland primary production, but the effects of this may vary across regions and flora, especially between perennial and annual-dominated grasslands.

Nitrous oxide emissions decrease with plant diversity but increase with grassland primary productivity

Nitrous oxide (N2O), a main greenhouse gas that contributes to ozone layer depletion, is released from soils. Even when it has been argued that agriculture is the main cause of its increase in the atmosphere, natural ecosystems are also an important source of N2O. However, the impacts of human activities on N2O emissions through biodiversity loss or primary productivity changes in natural ecosystems have rarely been assessed. Here, we analyzed the effects of vegetation attributes such as plant diversity and production, as drivers of N2O emission rates, in addition to environmental factors. We measured N2O emissions monthly during 1year in 12 sites covering a large portion of the Rio de la Plata grasslands, Argentina, and related these emissions with climate, soil and vegetation attributes. We performed spatial and temporal models of N2O emissions separately, to evaluate which drivers control N2O in space and over time independently. Our results showed that in the spatial model, N2O emissions decreased with increments in plant species richness, with concomitant reductions in soil [Formula: see text] whereas N2O emissions increased with primary productivity. By contrast, in the temporal model, monthly precipitation and monthly temperature were the main drivers of N2O emissions, with positive correlations, showing important differences with the spatial model. Overall, our results show that biological drivers may exert substantial control of N2O emissions at large spatial scales, together with climate and soil variables. Our results suggest that biodiversity conservation of natural grasslands may reduce regional greenhouse gas emissions, besides maintaining other important ecosystem services.

Plant functional groups mediate drought resistance and recovery in a multisite grassland experiment

Abstract Climate change predictions suggest that summer droughts will become more intense and recurrent in Europe. While drought‐induced reductions in grassland primary productivity are well documented, the drivers behind drought resistance (the capacity to withstand change) and recovery (the capacity for recovery of function) of above‐ and below‐ground biomass remain poorly understood. Across eight grasslands differing in plant community productivity (CP), we investigated the effects of summer drought on plant and soil microbial variables, plant nutrient content, and soil nitrogen (N) availability. We examined the linkages between CP, soil N, drought responses of plant and microbial communities, and relative drought responses of plant and microbial biomass. Plant and microbial variables were recorded at the end of a 3‐month rainfall exclusion period. Plant variables were also assessed during a 10‐month drought recovery period. Experimental drought decreased plant biomass and increased plant C:N ratios, but had no effect on total microbial biomass across sites. Instead, drought caused shifts in plant and microbial community structures as well as an increase in arbuscular mycorrhiza fungi biomass. Overall, plant biomass drought resistance was unrelated to CP or microbial community structure but was positively related to drought resistance of forbs. In the month after rewetting, soil N availability increased in droughted plots across sites. Two months post‐rewetting, droughted plots had higher plant N concentration, but lower plant N use efficiency. The short‐term drought recovery of plant biomass was unrelated to CP or soil N availability, but positively related to the response of grass biomass, reflecting incomplete recovery at high CP. Ten months after rewetting, drought effects on plant biomass and plant N content were no longer apparent. Synthesis. Our results suggest that drought resistance and recovery are more sensitive to plant community composition than to community productivity. Short‐term recovery of plant biomass may also benefit from increased soil N availability after drought and from a high abundance of soil fungi in low productivity sites. Our findings underline the importance of plant functional groups for the stability of permanent grasslands in a changing climate with more frequent drought.

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Abstract. Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

Shifting plant species composition in response to climate change stabilizes grassland primary production

The structure and function of alpine grassland ecosystems, including their extensive soil carbon stocks, are largely shaped by temperature. The Tibetan Plateau in particular has experienced significant warming over the past 50 y, and this warming trend is projected to intensify in the future. Such climate change will likely alter plant species composition and net primary production (NPP). Here we combined 32 y of observations and monitoring with a manipulative experiment of temperature and precipitation to explore the effects of changing climate on plant community structure and ecosystem function. First, long-term climate warming from 1983 to 2014, which occurred without systematic changes in precipitation, led to higher grass abundance and lower sedge abundance, but did not affect aboveground NPP. Second, an experimental warming experiment conducted over 4 y had no effects on any aspect of NPP, whereas drought manipulation (reducing precipitation by 50%), shifted NPP allocation belowground without affecting total NPP. Third, both experimental warming and drought treatments, supported by a meta-analysis at nine sites across the plateau, increased grass abundance at the expense of biomass of sedges and forbs. This shift in functional group composition led to deeper root systems, which may have enabled plant communities to acquire more water and thus stabilize ecosystem primary production even with a changing climate. Overall, our study demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but it also caused a shift from aboveground to belowground productivity.

Variability in community productivity—mediating effects of vegetation attributes

Abstract Plant productivity varies through time in response to environmental fluctuations. Reducing variability in productivity requires an improved understanding of how plant community attributes interact with environmental fluctuations to influence plant growth dynamics. We evaluated links between two community attributes, species diversity and abundance‐weighted values of specific leaf area (SLA), and temporal variability in grassland productivity at patch (local) and aggregate (multipatch) spatial scales. Aggregate communities were created by combining patches of spatially distinct communities of perennial plant species from grassland biodiversity experiments in Texas, USA. Interannual variability in above‐ground net primary productivity (ANPP) of aggregate communities was analysed as a function of two multiplicative components, mean temporal variability in the ANPP of patches and temporal synchrony in ANPP dynamics among patches. We used regression analyses to determine whether temporal variability in aggregate ANPP and its components were correlated with either species diversity or community‐weighted SLA over 5 years. Temporal variability in ANPP of aggregate communities was strongly correlated with temporal variability in patch ANPP. Increasing mean SLA reduced ANPP variability of aggregate communities by increasing mean productivity. Increased temporal changes in patch‐scale SLA further reduced temporal variability in aggregate ANPP by reducing effects of precipitation fluctuations on productivity. Conversely, increasing species diversity over the narrow range measured increased temporal variability in aggregate ANPP. High diversity was associated with reduced dominance of temporally stable C4 grasses. Our results implicate means and patch‐scale temporal dynamics in community SLA as potential indicators of variability in grassland primary productivity through time. A plain language summary is available for this article.

Short-Term Effects of Changing Precipitation Patterns on Shrub-Steppe Grasslands: Seasonal Watering Is More Important than Frequency of Watering Events

Climate change is expected to alter precipitation patterns. Droughts may become longer and more frequent, and the timing and intensity of precipitation may change. We tested how shifting precipitation patterns, both seasonally and by frequency of events, affects soil nitrogen availability, plant biomass and diversity in a shrub-steppe temperate grassland along a natural productivity gradient in Lac du Bois Grasslands Protected Area near Kamloops, British Columbia, Canada. We manipulated seasonal watering patterns by either exclusively watering in the spring or the fall. To simulate spring precipitation we restricted precipitation inputs in the fall, then added 50% more water than the long term average in the spring, and vice-versa for the fall precipitation treatment. Overall, the amount of precipitation remained roughly the same. We manipulated the frequency of rainfall events by either applying water weekly (frequent) or monthly (intensive). After 2 years, changes in the seasonality of watering had greater effects on plant biomass and diversity than changes in the frequency of watering. Fall watering reduced biomass and increased species diversity, while spring watering had little effect. The reduction in biomass in fall watered treatments was due to a decline in grasses, but not forbs. Plant available N, measured by Plant Root Simulator (PRS)-probes, increased from spring to summer to fall, and was higher in fall watered treatments compared to spring watered treatments when measured in the fall. The only effect observed due to frequency of watering events was greater extractable soil N in monthly applied treatments compared to weekly watering treatments. Understanding the effects of changing precipitation patterns on grasslands will allow improved grassland conservation and management in the face of global climatic change, and here we show that if precipitation is more abundant in the fall, compared to the spring, grassland primary productivity will likely be negatively affected.

Anthropogenic nitrogen deposition predicts local grassland primary production worldwide

Humans dominate many important Earth system processes including the nitrogen (N) cycle. Atmospheric N deposition affects fundamental processes such as carbon cycling, climate regulation, and biodiversity, and could result in changes to fundamental Earth system processes such as primary production. Both modelling and experimentation have suggested a role for anthropogenically altered N deposition in increasing productivity, nevertheless, current understanding of the relative strength of N deposition with respect to other controls on production such as edaphic conditions and climate is limited. Here we use an international multiscale data set to show that atmospheric N deposition is positively correlated to aboveground net primary production (ANPP) observed at the 1‐m2 level across a wide range of herbaceous ecosystems. N deposition was a better predictor than climatic drivers and local soil conditions, explaining 16% of observed variation in ANPP globally with an increase of 1 kg N·ha−1·yr−1 increasing ANPP by 3%. Soil pH explained 8% of observed variation in ANPP while climatic drivers showed no significant relationship. Our results illustrate that the incorporation of global N deposition patterns in Earth system models are likely to substantially improve estimates of primary production in herbaceous systems. In herbaceous systems across the world, humans appear to be partially driving local ANPP through impacts on the N cycle.

EVALUATION OF PRIMARY PRODUCTIVITY AT THE WILDLIFE PROTECTED AREA, "NEVADO DE TOLUCA" MEXICO, DURING THE DRY SEASON

&lt;p&gt;This is the first report on grassland primary productivity for the wildlife protected area Nevado de Toluca (APFF Nevado de Toluca). We evaluated three communities in this area during dry season: Loma Alta, La Peñuela y Agua Blanca. Following Hodgson (1994), for this study we used exclusion cages. Vegetation was cut every 28 days during a five months sampling period. A randomized block design was used, where the blocks represented the grassland communities and the different months constituted treatments. The month of September showed the higher production (610.3 kg/ha DM). No significant differences were observed among communities (P &amp;gt;0.05). In conclusion, these communities have similar low primary productivity through the evaluation dry season months, which in addition was found lower in comparison to other areas, therefore livestock grazing in this region should be limited this season.&lt;/p&gt;

Determinants of grassland primary production in seasonally-dry silvopastoral systems in Central America

Grassland primary productivity is the function that underpins the majority of the fodder production in cattle-rearing silvopastoral farms. Hence, understanding the factors that determine grassland productivity is critical for the design and management of silvpastoral systems. We studied the effect of two factors with documented impact on grassland productivity in seasonally dry silvopastures of Nicaragua, rainfall and trees. We assessed the effects of three species that differed in crown size and phenology, one evergreen, Cassia grandis, and two deciduous species, Guazuma ulmifolia and Tabebuia rosea. Overall, grassland ANPP had a quadratic response to rainfall, with a decline at high rainfall that coincided with peak standing biomass and grassland cover. Trees had a predominately negative effect on grassland productivity, and the effect was concentrated in the rainy season at peak productivity. The effect of the trees corresponded with the tree crown area, but not with crown density. Trees reduced the standing biomass of graminoids and increased forb biomass; thus, the effect of trees on grassland ANPP appears in part to respond to changes in grassland composition. We also found higher levels of soil moisture content below the tree canopy, particularly at the peak of the rainy season when soils tend to become waterlogged. The evergreen species, C. grandis, affected grassland ANPP more strongly than the deciduous species.

Precipitation legacies in desert grassland primary production occur through previous‐year tiller density

In arid ecosystems, current-year precipitation often explains only a small proportion of annual aboveground net primary production (ANPP). We hypothesized that lags in the response of ecosystems to changes in water availability explain this low explanatory power, and that lags result from legacies from transitions from dry to wet years or the reverse. We explored five hypotheses regarding the magnitude of legacies, two possible mechanisms, and the differential effect of previous dry or wet years on the legacy magnitude. We used a three-year manipulative experiment with five levels of rainfall in the first two years (-80% and -50% reduced annual precipitation (PPT), ambient, +50% and +80% increased PPT), and reversed treatments in year 3. Legacies of previous two years, which were dry or wet, accounted for a large fraction (20%) of interannual variability in production on year 3. Legacies in ANPP were similar in absolute value for both types of precipitation transitions, and their magnitude was a function of the difference between previous and current-year precipitation. Tiller density accounted for 40% of legacy variability, while nitrogen and carryover water availability showed no effect. Understanding responses to changes in interannual precipitation will assist in assessing ecosystem responses to climate change-induced increases in precipitation variability.

Simulation of grassland productivity by the combination of ground and satellite data

This paper presents the assessment of a NDVI-based parametric model (C-Fix) and a bio-geochemical model (BIOME-BGC) for the simulation of semi-natural grassland primary productivity in Italy. The two models are first calibrated using the gross primary productivity (GPP) data of an eddy covariance flux tower placed over a Mediterranean-temperate hilly area in Central Italy. Next, they are applied to estimate the net primary productivity (NPP) of three independent areas representative of different eco-climatic zones. The first area shows a typical Alpine climate, while the other two are characterized by more or less pronounced Mediterranean features. The accuracy of the NPP estimates is assessed through comparison with destructive dry matter measurements taken in the three areas. The results obtained support the capability of the two models to predict spatial NPP differences across the various grassland sites. The greatest estimation errors are found in the mountain area, mostly due to inaccuracies in the meteorological input data. These errors affect particularly the outputs of the bio-geochemical model and are mitigated by the use of C-Fix, which exploits the remotely sensed information related to the seasonal evolution of green biomass.

Legume defoliation affects rhizosphere decomposers, but not the uptake of organic matter N by a neighbouring grass

Legume–grass interactions have a great influence on grassland primary production and it was recently shown how defoliation of a legume can increase the transfer of fixed N to a neighbouring grass. It has also been shown that defoliation of a plant can increase soil microbial activity and lead to better soil N availability in the rhizosphere of the defoliated plant. We combined these two perspectives and tested whether defoliation of a legume (Lotus corniculatus) can enhance N nutrition of the neighbouring grass (Holcus lanatus) by increasing growth of soil decomposer biota and the availability of soil organic matter N for grass uptake. We grew mixtures of L. corniculatus and H. lanatus in grassland soil that included 15N-labelled L. corniculatus litter. In half of the systems, we subjected L. corniculatus to a defoliation treatment mimicking insect larvae feeding. At destructive harvests 1, 3, 9 and 30 days after the last defoliation event, we determined how L. corniculatus defoliation affected decomposer microbes, protozoa and nematodes and whether these changes among decomposers created a feedback on the growth and 15N uptake of the neighbouring H. lanatus. Defoliation reduced the growth and litter-N uptake, but increased shoot N concentration of L. corniculatus. Of the soil variables measured, defoliation doubled the number of bacterial-feeding protozoa, but did not affect the abundance of decomposer microbes and bacterial- and fungal-feeding nematodes. Defoliation did not have statistically significant effects on H. lanatus shoot growth, shoot N concentration or litter-N uptake. Our results demonstrate how defoliation-induced changes in legume ecophysiology can affect the growth of decomposers in soil. However, these effects did not appear to lead to a significant change in the availability of soil organic N to the neighbouring grass. It seems that when positive effects of legume defoliation on grass N nutrition are found in grassland ecosystems, these are more likely to be explained by direct transfer of fixed N rather than changes in the availability of soil organic matter N.