Potassium limitation of forest productivity – Part 2: CASTANEA-MAESPA-K shows a reduction in photosynthesis rather than a stoichiometric limitation of tissue formation

Potassium (K) availability constrains forest productivity. Brazilian eucalypt plantations are a good example of the K limitation of wood production. Here, we built upon a previously described model (CASTANEA-MAESPA-K) and used it to understand whether the simulated decline in C source under K deficiency was sufficient to explain the K limitation of wood productivity in Brazilian eucalypt plantations. We developed allocation schemes for both C and K and included these in CASTANEA-MAESPA-K. Neither direct limitations of the C-sink activity nor direct modifications of the C allocation by K availability were included in the model. Simulation results show that the model was successful in replicating the observed patterns of wood productivity limitation by K deficiency. Simulations also show that the response of net primary productivity (NPP) is not linear with increasing K fertilisation. Simulated stem carbon use and water use efficiencies decreased with decreasing levels of K availability. Simulating a direct stoichiometric limitation of NPP or wood growth was not necessary to reproduce the observed decline of productivity under K limitation, suggesting that K stoichiometric plasticity could be different to that of N and P. Confirming previous results from the literature, the model simulated an intense recirculation of K in the trees, suggesting that retranslocation processes were essential for tree functioning. Optimal K fertilisation levels calculated by the model were similar to nutritional recommendations currently applied in Brazilian eucalypt plantations, paving the way for validation of the model at a larger scale and of this approach for developing decision-making tools to improve fertilisation practices.</p

Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands

The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K limitation could influence the response of forests to future global changes. To understand the effects of K limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from stand-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterise the model. The model was parameterised for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with estimations in K-limited eucalypt stands. Simulations showed a decrease of modelled canopy transpiration of around 50 % and a decrease in modelled water-use efficiency WUEGPP of 10 %. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K limitation of GPP. The inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the cycle of K within the ecosystem were critical for the response of the system to K deficiency. Litter leaching processes were of lower importance, since residence time of K in litter was low. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP were outlined. This is a first step in identifying the source or sink limitation of forest growth by K.</p

Soil respiration at mean annual temperature predicts annual total across vegetation types and biomes

Soil respiration (SR) constitutes the largest flux of CO₂ from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (〖SR〗_MAT), irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q₁₀). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SRMAT corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure 〖SR〗_MAT for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO₂ emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle

Estimate of Leaf Area Index in an Old-Growth Mixed Broadleaved-Korean Pine Forest in Northeastern China

Leaf area index (LAI) is an important variable in the study of forest ecosystem processes, but very few studies are designed to monitor LAI and the seasonal variability in a mixed forest using non-destructive sampling. In this study, first, true LAI from May 1st and November 15th was estimated by making several calibrations to LAI as measured from the WinSCANOPY 2006 Plant Canopy Analyzer. These calibrations include a foliage element (shoot, that is considered to be a collection of needles) clumping index measured directly from the optical instrument, TRAC (Tracing Radiation and Architecture of Canopies); a needle-to-shoot area ratio obtained from shoot samples; and a woody-to-total area ratio. Second, by periodically combining true LAI (May 1st) with the seasonality of LAI for deciduous and coniferous species throughout the leaf-expansion season (from May to August), we estimated LAI of each investigation period in the leaf-expansion season. Third, by combining true LAI (November 15th) with litter trap data (both deciduous and coniferous species), we estimated LAI of each investigation period during the leaf-fall season (from September to mid-November). Finally, LAI for the entire canopy then was derived from the initial leaf expansion to the leaf fall. The results showed that LAI reached its peak with a value of 6.53 m2 m−2 (a corresponding value of 3.83 m2 m−2 from optical instrument) in early August, and the mean LAI was 4.97 m2 m−2 from May to November using the proposed method. The optical instrument method underestimated LAI by an average of 41.64% (SD = 6.54) throughout the whole study period compared to that estimated by the proposed method. The result of the present work implied that our method would be suitable for measuring LAI, for detecting the seasonality of LAI in a mixed forest, and for measuring LAI seasonality for each species

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Model parameterization to simulate and compare the PAR absorption potential of two competing plant species

Mountain pastures dominated by the pasture grass Setaria sphacelata in the Andes of southern Ecuador are heavily infested by southern bracken (Pteridium arachnoideum), a major problem for pasture management. Field observations suggest that bracken might outcompete the grass due to its competitive strength with regard to the absorption of photosynthetically active radiation (PAR). To understand the PAR absorption potential of both species, the aims of the current paper are to (1) parameterize a radiation scheme of a two-big-leaf model by deriving structural (LAI, leaf angle parameter) and optical (leaf albedo, transmittance) plant traits for average individuals from field surveys, (2) to initialize the properly parameterized radiation scheme with realistic global irradiation conditions of the Rio San Francisco Valley in the Andes of southern Ecuador, and (3) to compare the PAR absorption capabilities of both species under typical local weather conditions. Field data show that bracken reveals a slightly higher average leaf area index (LAI) and more horizontally oriented leaves in comparison to Setaria. Spectrometer measurements reveal that bracken and Setaria are characterized by a similar average leaf absorptance. Simulations with the average diurnal course of incoming solar radiation (1998–2005) and the mean leaf–sun geometry reveal that PAR absorption is fairly equal for both species. However, the comparison of typical clear and overcast days show that two parameters, (1) the relation of incoming diffuse and direct irradiance, and (2) the leaf–sun geometry play a major role for PAR absorption in the two-big-leaf approach: Under cloudy sky conditions (mainly diffuse irradiance), PAR absorption is slightly higher for Setaria while under clear sky conditions (mainly direct irradiance), the average bracken individual is characterized by a higher PAR absorption potential. (∼74 MJ m−2 year−1). The latter situation which occurs if the maximum daily irradiance exceeds 615 W m−2 is mainly due to the nearly orthogonal incidence of the direct solar beam onto the horizontally oriented frond area which implies a high amount of direct PAR absorption during the noon maximum of direct irradiance. Such situations of solar irradiance favoring a higher PAR absorptance of bracken occur in ∼36% of the observation period (1998–2005). By considering the annual course of PAR irradiance in the San Francisco Valley, the clear advantage of bracken on clear days (36% of all days) is completely compensated by the slight but more frequent advantage of Setaria under overcast conditions (64% of all days). This means that neither bracken nor Setaria show a distinct advantage in PAR absorption capability under the current climatic conditions of the study area

Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere–biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997–1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources

A mechanistic ecohydrological model to investigate complex interactions in cold and warm water‐controlled environments: 1. Theoretical framework and plot‐scale analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95321/1/jame60.pd

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible