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1,141 results for “primary_productivity”
Net Primary Production (NPP) estimates from 4 Land Surface Modelling (LSM) in Fennoscandia 1997-2013
<p>The file "Dec1997_Dec2013_4LSM_subCLINF_npp_.RData" contains NPP (Net Primary Production) estimates from 4 Land Surface Modelling (LSM): JULES, ORCHIDEE-MICT, ORCHIDEE-HLveg and CLM5 over the nordic area encompassing Norway, Sweden, Finland and western Russia (58.25-71.25 North and 4.75-34.75 East).</p> <p>The data is used in the paper: <a href="https://www.biogeosciences-discuss.net/bg-2019-252/">Leibovici DG</a>, Quegan S, Comyn-Platt E, Hayman G, Val Martin M, Guimberteau M, Druel A, Zhu D, and Ciais P (2020) Spatio-Temporal Variations and Uncertainty in Land Surface Modelling for High Latitudes: Univariate Response Analysis.<strong> Biogeosciences (accepted 5Feb2020) </strong></p>
Drought risk of global terrestrial gross primary productivity in recent 40 years detected by a remote sensing-driven process model
<p class="Abstract"><span>Gross primary productivity (GPP) is the largest flux in the global terrestrial carbon cycle and affected by multiple factors. In recent decades, drought has significantly impacted global terrestrial GPP and been projected to occur with increasing frequency and intensity. However, the drought risk of global terrestrial GPP has not been well investigated. In this study, global terrestrial GPP over the period from 1981 to 2016 was simulated with the process-based Boreal Ecosystem Productivity Simulator (BEPS) model. Then, the drought risk of terrestrial GPP was quantified as the product of frequency of drought and reduction of GPP caused by drought, which were determined using the standardized precipitation evapotranspiration index (SPEI). During the study period, the drought risk of terrestrial GPP exhibited detectable spatial heterogeneity, high in southeastern United States, most of South America, southern Europe, central and eastern Africa, eastern and southeastern Asia, and eastern Australia. In these regions, the maximum reduction of GPP might be above 30% in drought years relative to that in normal years. The drought risk of GPP was low at high latitudes of the Northern Hemisphere, in which terrestrial GPP increased slightly in drought years. The spatial pattern of the drought risk of GPP simulated by the BEPS model was close to that of FLUXCOM GPP, which was scaled from tower observations with a machine learning algorithm forced by remote sensing and meteorological data. This study advances our understanding on the impact of drought on terrestrial GPP over the globe.</span></p>
Data from: Identification of glucose kinase dependent and independent pathways for carbon control of primary metabolism, development and antibiotic production in Streptomyces coelicolor by quantitative proteomics
Members of the soil-dwelling prokaryotic genus Streptomyces are indispensable for the recycling of complex polysaccharides, and produce a wide range of natural products. Nutrient availability is a major determinant for the switch to development and antibiotic production in streptomycetes. Carbon catabolite repression (CCR), a main signaling pathway underlying this phenomenon, was so far considered fully dependent on the glycolytic enzyme glucose kinase (Glk). Here we provide evidence of a novel Glk-independent pathway in Streptomyces coelicolor, using advanced proteomics that allowed the comparison of the expression of some 2,000 proteins, including virtually all enzymes for central metabolism. While CCR and inducer exclusion of enzymes for primary and secondary metabolism and precursor supply for natural products is mostly mediated via Glk, enzymes for the urea cycle, as well as for biosynthesis of the γ-butyrolactone Scb1 and the responsive cryptic polyketide Cpk are subject to Glk-independent CCR. Deletion of glkA led to strong downregulation of biosynthetic proteins for prodigionin and calcium-dependent antibiotic (CDA) in mannitol-grown cultures. Repression of bldB, bldN, and its target bldM explains the poor development of S. coelicolor on solid-grown cultures containing glucose. A new model for carbon catabolite repression in streptomycetes is presented.
Data from: Variability in primary productivity determines metapopulation dynamics
Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality, and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity —a major outcome of ecosystem functions— on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feedback into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for > 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatial population processes has broad implications for metapopulation persistence in fluctuating and changing environments.
Carbon flux and gross primary production of a scrub of Mexico
<p><span>Vegetation fixes C in its biomass through photosynthesis or might release it into the atmosphere through respiration. Measurements of these fluxes would help us to understand ecosystem functioning. This data is related to carbon flux (NEE) colected with the eddy covariance technique (EC_Data). The NEE is the balance between gross primary production (GPP) and ecosystem respiration (Reco) both calculated using the recent R package Reddyproc (Code Reddyproc). The database also include estimates of GPP of MOD17A2H product of MODIS Satellite for four pixels of a site with scrub vegetation in Mexico (GPP_MODIS). The programming code include the pre-procecing of NEE and the Theil-Sen and Linear model to describe the relationship between GPP of EC and GPP of MODIS (Code Theil-Sen).</span></p>
Results of coccolith assemblage and reconstructed primary productivity over the Holocene of marine sediment cores MD77-191 and MD98-2152
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Data from: Aquatic primary production in a high-CO2 world
Here, we provide a review of the direct effect of increasing CO2 on aquatic primary producers through its function as a source of carbon, focusing our analysis on the interpretation of this increase as an increase in the availability of a resource. This provides an interesting context to evaluate ecological and evolutionary theories relating to nutrient availability and leads us to: the assessment of theories about limitation of productivity and the integration of CO2 into the co-limitation paradigm; the prediction of community composition and of change in communities from known changes in the environment; and evaluation of the potential for evolutionary adaptation in conditions that increase growth.
Dataset of article: Evaluation of the Effects of Submarine Groundwater on Nutrient Concentration and Primary Production in a Deep Bay of the Japan Sea
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Figure 1 in Peculiarities of seasonal dynamics of net primary production and its microzooplankton grazing in the coastal waters of the Black Sea (Sevastopol region)
Figure 1. Map of the sampling stations: 1—the exit from the Quarantine Bay (St.1); 2—Sevastopol Bay (St. 2).
A global gross primary productivity dataset of sunlit and shaded leaves via combining two-leaf light use efficiency model with random forest from 2002 to 2020
<p><span>The TL-CRF model generated a global </span><span>0.05</span><span><span>´</span></span><span>0.05<span>°</span></span><span> product for eight-day gross primary productivity (GPP) of sunlit and shaded canopies from 2002 to 2020 by embedding the random forest (RF) submodule into the two-leaf light use efficiency (TL-LUE) model while considering the seasonal differences in the clumping index. The RF technique was used to integrate various environmental stress factors including meteorological, hydrological, soil properties, and elevation, thereby improving the overall scale of the complex environmental conditions to the maximum LUE. Eight-day GPP was then aggregated into monthly, seasonal, and annual GPP. This novel GPP product could support further research on spatial and temporal patterns of the carbon cycle and its association with climate change. </span></p>
Data from: Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model
Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie–Ames–Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPPCASA) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPPCASA for early, intermediate, and late successional stages were 3.22 Mg C ha−1 yr−1, 8.90 Mg C ha−1 yr−1, and 7.59 Mg C ha−1 yr−1, respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPPCASA. The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.
Linking population dynamics models with empirically derived models through phytoplankton primary production
<p>There are alternative methods for estimation of phytoplankton primary production (PP) that are fundamentally different in the calculation approach. The process-oriented PP model is a mechanistic, empirically derived method based on the photosynthesis–light relationships. The population dynamics-based PP calculation, which is a synthetic method, provides a production estimate based on population dynamics of phytoplankton. These alternative methods were here compared with regard to production estimates and linked to enhance the performance of the existing models of population dynamics applied to a wide variety of lakes worldwide in terms of morphometry, nutrient status, and light environments. Estimates of primary production were shown to be sensitive to changes in phytoplankton sinking and zooplankton grazing rates in both methods. Production estimates in the process-oriented PP model were also sensitive to light-associated parameters such as day length. Although the production estimated from the population dynamics-based PP calculation tended to be lower than that from the process-oriented PP model irrespective of lake morphometry, production estimates calculated from both methods with standard parameterization were comparable when production was estimated on an annual timescale. However, it was also shown that the alternative methods could produce different production estimates when estimated on shorter timescales such as cyanobacterial blooms in summer. Cyanobacteria with low mortality due to grazing and sinking losses have been considered as trophic bottlenecks, but there is increasing evidence that their mortality is, to a considerable extent, due to parasitic pathogens. In the case of cyanobacterial blooms, an addition of parasite-related loss term (19–33% of standing stock) resulted in a resolution of the difference in production estimates between the methods. These analyses theoretically support the critical role of parasitism and resolve the bottleneck problem in aquatic ecosystem metabolism.</p>
Global Monthly Gross Primary Production
<p>This is global monthly gross primary production from 2001-2016 derived from P model using pyrealm python package. Unit for GPP is gC/m2 day (monthly daily mean value). Detailed description of data can be found in Shen et al. 2023. For detailed description of P model please refer to Wang et al. 2017, Cai and Prentice 2020 and Stocker et al. 2020.</p>
CMLR: A mechanistic global 0.05° Gross Primary Production dataset using TROPOMI Solar-induced fluorescence observations
<p>CMLR GPP is a mechanistic global Gross Primary Production dataset using TROPOMI Solar-induced chlorophyll fluorescence observations (TROPOSIF). This dataset provided GPP estimates from May 2018 to December 2021 with a 0.05° spatial resolution at 1-day time step. We modified the mechanistic light response (MLR) model proposed by Gu et al. (2019) to apply it to the canopy-scale, and then generated this dataset. The parameterization of q<sub>L</sub> (the fraction of open photosystem II reaction centers) in the MLR framework is accomplished using a random forest model. For the continuous global mapping purpose, we further composited the original CMLR GPP using an 8-day moving window and applied a 2D Gaussian function in 3 × 3 moving windows to fill in the gaps. Pixels with filled data were marked using flag = 1 in the quality control layer.</p>
Regional estimates of gross primary production applying the process-based model 3D-CMCC-FEM vs. multiple datasets
<p>This repository contains the model 3D-CMCC-FEM v5.6 executable (Testolin et al.2023), model inputs and model outputs in the folder RUN_BASILICATA; scripts to prepare model inputs and perform model outputs post-processing in SCRIPTS; remote-sensing based data and forcing in DATA; tables and post-processed files in OUTPUT; figures in FIGURE, related to the manuscript entitled “Regional estimates of gross primary production applying the process-based model 3D-CMCC-FEM vs. multiple datasets”</p>
Reconstructed net primary productivity of marine sediment cores MD98-2152, BAR94-24, MD85-666, and MD98-2178
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To Investigate Primary Irritation Potential of Four Skin Serum Products on Human Subjects Assessed by 24 Hour Patch Test
ClinicalTrials.gov study NCT03233009. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Aquatic primary production in a high-CO2 world
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Carbon flux and gross primary production of a scrub of Mexico
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Data from: Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model
Open the record for dataset details and reuse information.
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OpenNeuro
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