Leaf dry matter content predicts herbivore productivity, but its functional diversity is positively related to resilience in grasslands.
Ontology highlight
ABSTRACT:
SUBMITTER: Pakeman RJ
PROVIDER: S-EPMC4086977 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background and aimsSpecific leaf area (SLA), a key element of the 'worldwide leaf economics spectrum', is the preferred 'soft' plant trait for assessing soil fertility. SLA is a function of leaf dry matter content (LDMC) and leaf thickness (LT). The first, LDMC, defines leaf construction costs and can be used instead of SLA. However, LT identifies shade at its lowest extreme and succulence at its highest, and is not related to soil fertility. Why then is SLA more frequently used as a predictor of soil fertility than LDMC?MethodsSLA, LDMC and LT were measured and leaf density (LD) estimated for almost 2000 species, and the capacity of LD to predict LDMC was examined, as was the relative contribution of LDMC and LT to the expression of SLA. Subsequently, the relationships between SLA, LDMC and LT with respect to soil fertility and shade were described.Key resultsAlthough LD is strongly related to LDMC, and LDMC and LT each contribute equally to the expression of SLA, the exact relationships differ between ecological groupings. LDMC predicts leaf nitrogen content and soil fertility but, because LT primarily varies with light intensity, SLA increases in response to both increased shade and increased fertility.ConclusionsGradients of soil fertility are frequently also gradients of biomass accumulation with reduced irradiance lower in the canopy. Therefore, SLA, which includes both fertility and shade components, may often discriminate better between communities or treatments than LDMC. However, LDMC should always be the preferred trait for assessing gradients of soil fertility uncoupled from shade. Nevertheless, because leaves multitask, individual leaf traits do not necessarily exhibit exact functional equivalence between species. In consequence, rather than using a single stand-alone predictor, multivariate analyses using several leaf traits is recommended.
| S-EPMC3197453 | biostudies-literature
Project description:This work aims to predict time courses of leaf area index (LAI) based on dry matter partitioning into the leaves and on specific leaf area of newly formed leaf biomass (SLA(n)) for year-round cut chrysanthemum crops. In five glasshouse experiments, each consisting of several plant densities and planted throughout the year, periodic destructive measurements were conducted to develop empirical models for partitioning and for SLA(n). Dry matter partitioning into leaves, calculated as incremental leaf dry mass divided by incremental shoot dry mass between two destructive harvests, could be described accurately (R(2 )= 0.93) by a Gompertz function of relative time, R(t). R(t) is 0 at planting date, 1 at the start of short-days, and 2 at final harvest. SLA(n), calculated as the slope of a linear regression between periodic measurements of leaf dry mass (LDM) and LAI, showed a significant linear increase with the inverse of the daily incident photosynthetically active radiation (incident PAR, MJ m(-2 )d(-1)), averaged over the whole growing period, the average glasshouse temperature and plant density (R(2 )= 0.74). The models were validated by two independent experiments and with data from three commercial growers, each with four planting dates. Measured shoot dry mass increase, initial LAI and LDM, plant density, daily temperature and incident PAR were input into the model. Dynamics of LDM and LAI were predicted accurately by the model, although in the last part of the cultivation LAI was often overestimated. The slope of the linear regression of simulated against measured LDM varied between 0.95 and 1.09. For LAI this slope varied between 1.01 and 1.12. The models presented in this study are important for the development of a photosynthesis-driven crop growth model for cut chrysanthemum crops.
| S-EPMC4244956 | biostudies-literature
Project description:Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2-71.2% during 1982-2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms.
| S-EPMC4886642 | biostudies-literature
Project description:Delayed sowing of maize hybrids could exacerbate the capability of maximizing the yield potential through poor crop stand, root proliferation, nutrient uptake, and dry matter accumulation coupled with the inadequate partitioning of the assimilates. This study appraised the performance of five recent maize hybrids viz., PMH-1, PJHM-1, AH-4158, AH-4271, and AH-8181 under timely and late sown conditions of the irrigated semi-arid ecologies. Timely sowing had the grain and stover yields advantage of 16–19% and 12–25%, respectively over the late sown maize hybrids. The advanced hybrids AH-4271 and AH-4158 had higher grain yields than the others. During the post-anthesis period, a greater dry matter accumulation and contribution to the grain yield to the tune of 16% and 10.2%, respectively, was observed under timely sown conditions. Furthermore, the nutrient acquisition and use efficiencies also improved under the timely sown. The nutrient and dry matter remobilization varied among the hybrids with AH-4271 and PMH-1 registering greater values. The grain yield stability index (0.85) was highest with AH-4158 apart from the least yield reduction (15.2%) and stress susceptibility index (0.81), while the maximum geometric mean productivity was recorded with the AH-4271 (5.46 Mg ha−1). The hybrids AH-4271 and PJHM-1 exhibited improved root morphological traits, such as root length, biomass, root length density, root volume at the V5 stage (20 days after sowing, DAS) and 50% flowering (53 DAS). It is thus evident that the timely sowing and appropriate hybrids based on stress tolerance indices resulted in greater yields and better utilization of resources.
| S-EPMC9886954 | biostudies-literature
Project description:Young plants of Rhizophora mucronata Lam. were tested for oxidative stress, photosynthetic capacity and dry matter accumulation under two abiotic stress conditions; prolonged submergence and soil water stress. The experiment of prolonged submergence was performed in field conditions with two treatment levels; 50% inundation (control) and 100% inundation levels. The experiment of soil water stress was conducted in a plant-house with four treatment levels, 100% water holding capacity (WHC) (control), 50% WHC, 25% WHC and high salinity (> 35 psu). The experimentation period was 18 months. According to the results, antioxidant activity was increased in the 100% inundation level in field conditions and in the 25% WHC, 50% WHC and high salinity levels in plant-house conditions. However, decreased radical scavenging capacity reflected by low 2,2-diphenyl-1-picrylhydrazyl (DPPH) and high IC50 values were only observed in the 25% and 50% WHCs. Plant cell membranes were highly damaged in the 25%, 50% WHCs and high salinity level and a significant decrease in photosynthetic capacity (~ 90% reduction) and in dry matter content of Rhizophora plants were also observed in the same treatment levels. It was recorded that a higher proportion of dry matter is allocated to the root system under the 100% inundation level and it may be an adaptation to keep up the standing stability. Although, the antioxidant and scavenging capacities of young Rhizophora plants have increased under abiotic stress conditions, oxidative stress and its associated impacts on leaf photosynthetic capacity and dry weight contents were unavoidable under persistence of the stress.
| S-EPMC7415043 | biostudies-literature
Project description:Intercropping can obtain yield advantages, but the mechanism of yield advantages of maize-legume intercropping is still unclear. Then, we explored the effects of cropping systems and N input on yield advantages in a two-year experiment. Cropping systems included monoculture maize (Zea mays L.) (MM), monoculture soybean (Glycine max L. Merr.) (MS), monoculture peanut (Arachis hypogaea L.) (MP), maize-soybean substitutive relay intercropping (IMS), and maize-peanut substitutive strip intercropping (IMP). N input included without N (N0) and N addition (N1). Results showed that maize's leaf area index was 31.0% and 34.6% higher in IMS and IMP than in MM. The specific leaf weight and chlorophyll a (chl a) of maize were notably higher by 8.0% and 18.8% in IMS, 3.1%, and 18.6% in IMP compared with MM. Finally, N addition resulted in a higher thousand kernels weight of maize in IMS and IMP than that in MM. More dry matter accumulated and partitioned to the grain, maize's averaged partial land equivalent ratio and the net effect were 0.76 and 2.75 t ha-1 in IMS, 0.78 and 2.83 t ha-1 in IMP. The leaf area index and specific leaf weight of intercropped soybean were 16.8% and 26% higher than MS. Although soybean suffers from shade during coexistence, recovered growth strengthens leaf functional traits and increases dry matter accumulation. The averaged partial land equivalent ratio and the net effect of intercropped soybean were 0.76 and 0.47 t ha-1. The leaf area index and specific leaf weight of peanuts in IMP were 69.1% and 14.4% lower than in the MP. The chlorophyll a and chlorophyll b of peanut in MP were 17.0% and 24.4% higher than in IMP. A less dry matter was partitioned to the grain for intercropped peanut. The averaged pLER and NE of intercropped peanuts were 0.26 and -0.55 t ha-1. In conclusion, the strengthened leaf functional traits promote dry matter accumulation, maize-soybean relay intercropping obtained a win-win yield advantage, and maize-peanut strip intercropping achieved a trade-off yield advantage.
| S-EPMC10507892 | biostudies-literature
Project description:The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the system transitions between water and radiation limitation of evapotranspiration. The breakpoint appears to be fairly stable in the future, suggesting resilience of the Amazon to climate change. Changes in precipitation and land use are therefore more likely to govern biomass and vegetation structure in Amazonia.Earth system model simulations of future climate in the Amazon show little agreement. Here, the authors show that biases in internally generated climate explain most of this uncertainty and that the balance between water-saturated and water-limited evapotranspiration controls the Amazon resilience to climate change.
| S-EPMC5577139 | biostudies-literature
Project description:Extensive land-use change in the tropics has produced a mosaic of successional forests within an agricultural and cattle-pasture matrix. Post-disturbance biodiversity assessments have found that regeneration speed depends upon propagule availability and the intensity and duration of disturbance. However, reestablishment of species interactions is still poorly understood and this limits our understanding of the anthropogenic impacts upon ecosystem resilience. This is the first investigation that evaluates plant-herbivore interaction networks during secondary succession. In particular we investigated succession in a Mexican tropical dry forest using data of caterpillar associations with plants during 2007-2010. Plant-herbivore networks showed high resilience. We found no differences in most network descriptors between secondary and mature forest and only recently abandoned fields were found to be different. No significant nestedness or modularity network structure was found. Plant-herbivore network properties appear to quickly reestablish after perturbation, despite differences in species richness and composition. This study provides some valuable guidelines for the implement of restoration efforts that can enhance ecological processes such as the interaction between plants and their herbivores.
| S-EPMC3531414 | biostudies-literature
Project description:Cassava is a starchy root crop cultivated in the tropics for fresh consumption and commercial processing. Primary selection objectives in cassava breeding include dry matter content and micronutrient density, particularly provitamin A carotenoids. These traits are negatively correlated in the African germplasm. This study aimed at identifying genetic markers associated with these traits and uncovering whether linkage and/or pleiotropy were responsible for observed negative correlation. A genome-wide association mapping using 672 clones genotyped at 72,279 single nucleotide polymorphism (SNP) loci was performed. Root yellowness was used indirectly to assess variation in carotenoid content. Two major loci for root yellowness were identified on chromosome 1 at positions 24.1 and 30.5 Mbp. A single locus for dry matter content that colocated with the 24.1 Mbp peak for carotenoids was identified. Haplotypes at these loci explained 70 and 37% of the phenotypic variability for root yellowness and dry matter content, respectively. Evidence of megabase-scale linkage disequilibrium (LD) around the major loci of the two traits and detection of the major dry matter locus in independent analysis for the white- and yellow-root subpopulations suggests that physical linkage rather that pleiotropy is more likely to be the cause of the negative correlation between the target traits. Moreover, candidate genes for carotenoid () and starch biosynthesis ( and ) occurred in the vicinity of the identified locus at 24.1 Mbp. These findings elucidate the genetic architecture of carotenoids and dry matter in cassava and provide an opportunity to accelerate breeding of these traits.
| S-EPMC7822061 | biostudies-literature
Project description:Improving the accuracy of predicting plant productivity is a key element in planning nutrient management strategies to ensure a balance between nutrient supply and demand under climate change. A calculation based on intercepted photosynthetically active radiation is an effective and relatively reliable way to determine the climate impact on a crop above-ground biomass (AGB). This research shows that using variations in a chlorophyll content index (CCI) in a mathematical function could effectively obtain good statistical diagnostic results between simulated and observed crop biomass. In this study, the leaf CCI, which is used as a biochemical photosynthetic component and calibration parameter, increased simulation accuracy across the growing stages during 2016-2017. This calculation improves the accuracy of prediction and modelling of crops under specific agroecosystems, and it may also improve projections of AGB for a variety of other crops.
| S-EPMC6330949 | biostudies-literature