Seeing the canopy for the branches: Improved within canopy scaling of leaf nitrogen

Abstract Transitioning across biological scales is a central challenge in land surface models. Processes that operate at the scale of individual leaves must be scaled to canopies, and this is done using dedicated submodels. Here, we focus on a submodel that prescribes how light and nitrogen are distributed through plant canopies. We found a mathematical inconsistency in a submodel implemented in the Community and Energy Land Models (CLM and ELM), which incorporates twigs, branches, stems, and dead leaves in nitrogen scaling from leaf to canopy. The inconsistency leads to unrealistic (physically impossible) values of the nitrogen scaling coefficient. The mathematical inconsistency is a general mistake, that is, would occur in any model adopting this particular submodel. We resolve the inconsistency by allowing distinct profiles of stems and branches versus living leaves. We implemented the updated scheme in the ELM and find that the correction reduces global mean gross primary production (GPP) by 3.9 Pg C (3%). Further, when stems and branches are removed from the canopy in the updated model (akin to models that ignore shading from stems), global GPP increases by 4.1 Pg C (3.2%), because of reduced shading. Hence, models that entirely ignore stem shading also introduce errors in the global spatial distribution of GPP estimates, with a strong signal in the tropics, increasing GPP there by over 200 g C m−2 yr−1. Appropriately incorporating stems and other nonphotosynthesizing material into the light and nitrogen scaling routines of global land models, will improve their biological realism and accuracy

Potential climate change impacts on temperate forest ecosystem processes

Large changes in atmospheric CO2, temperature, and precipitation are predicted by 2100, yet the long-term consequences for carbon (C), water, and nitrogen (N) cycling in forests are poorly understood. We applied the PnET-CN ecosystem model to compare the long-term effects of changing climate and atmospheric CO2 on productivity, evapotranspiration, runoff, and net nitrogen mineralization in current Great Lakes forest types. We used two statistically downscaled climate projections, PCM B1 (warmer and wetter) and GFDL A1FI (hotter and drier), to represent two potential future climate and atmospheric CO2 scenarios. To separate the effects of climate and CO2, we ran PnET-CN including and excluding the CO2 routine. Our results suggest that, with rising CO2 and without changes in forest type, average regional productivity could increase from 67% to 142%, changes in evapotranspiration could range from –3% to +6%, runoff could increase from 2% to 22%, and net N mineralization could increase 10% to 12%. Ecosystem responses varied geographically and by forest type. Increased productivity was almost entirely driven by CO2 fertilization effects, rather than by temperature or precipitation (model runs holding CO2 constant showed stable or declining productivity). The relative importance of edaphic and climatic spatial drivers of productivity varied over time, suggesting that productivity in Great Lakes forests may switch from being temperature- to water-limited by the end of the century

Relationship between aerodynamic roughness length and bulk sedge leaf area index in a mixed-species boreal mire complex

Leaf area index (LAI) is an important parameter in natural ecosystems, representing the seasonal development of vegetation and photosynthetic potential. However, direct measurement techniques require labor-intensive field campaigns that are usually limited in time, while remote sensing approaches often do not yield reliable estimates. Here we propose that the bulk LAI of sedges (LAI(s)) can be estimated alternatively from a micrometeorological parameter, the aerodynamic roughness length for momentum (z(0)). z(0) can be readily calculated from high-response turbulence and other meteorological data, typically measured continuously and routinely available at ecosystem research sites. The regressions of LAI versus z(0) were obtained using the data from two Finnish natural sites representative of boreal fen and bog ecosystems. LAI(s) was found to be well correlated with z(0) and sedge canopy height. Superior method performance was demonstrated in the fen ecosystem where the sedges make a bigger contribution to overall surface roughness than in bogs.Peer reviewe

Implications of improved representations of plant respiration in a changing climate

Land-atmosphere exchanges influence atmospheric CO2. Emphasis has been on describing photosynthetic CO2 uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (R d) and temperature dependencies. This allows characterisation of baseline R d, instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates R d to whole-plant respiration R p, driven with meteorological forcings spanning uncertainty across climate change models. For pre-industrial estimates, new baseline R d increases R p and especially in the tropics. Compared to new baseline, revised instantaneous response decreases R p for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new R d estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how R d aggregates to whole-plant respiration. Our analysis suggests R p could be around 30% higher than existing estimates.C.H. acknowledges the NERC CEH National Capability fund. We acknowledge the many climate research centres that contributed GCM outputs in to the Coupled Model Intercomparison Project (CMIP5) database. The support of the Australian Research Council to O.K.A. and P.M. (DP130101252, CE140100008, FT0991448, FT110100457) is acknowledged, as are awards DE-FG02-07ER64456 from the US Department of Energy, Office of Science, Office of Biological and Environmental Research and DEB-1234162 from the U.S. National Science Foundation (NSF) Long-Term Ecological Research Program (to P.B.R.); and National Science Foundation International Polar Year Grant (to K.L.G.). L.M.M. acknowledges the support of the Natural Environment Research Council (NERC) South American Biomass Burning Analysis (SAMBBA) project grant code NE/ J010057/1

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means

Higher thermal acclimation potential of respiration but not photosynthesis in two alpine Picea taxa in contrast to two lowland congeners

The members of the genus Picea form a dominant component in many alpine and boreal forests which are the major sink for atmospheric CO2. However, little is known about the growth response and acclimation of CO2 exchange characteristics to high temperature stress in Picea taxa from different altitudes. Gas exchange parameters and growth characteristics were recorded from four year old seedlings of two alpine (Picea likiangensis vars. rubescens and linzhiensis) and two lowland (P. koraiensis and P. meyeri) taxa. Seedlings were grown at moderate (25°C/15°C) and high (35°C/25°C) day/night temperatures, for four months. The approximated biomass increment (ΔD2H) for all taxa decreased under high temperature stress, associated with decreased photosynthesis and increased respiration. However, the two alpine taxa exhibited lower photosynthetic acclimation and higher respiratory acclimation than either lowland taxon. Moreover, higher leaf dry mass per unit area (LMA) and leaf nitrogen content per unit area (Narea), and a smaller change in the nitrogen use efficiency of photosynthesis (PNUE) for lowland taxa indicated that these maintained higher homeostasis of photosynthesis than alpine taxa. The higher respiration rates produced more energy for repair and maintenance biomass, especially for higher photosynthetic activity for lowland taxa, which causes lower respiratory acclimation. Thus, the changes of ΔD2H for alpine spruces were larger than that for lowland spruces. These results indicate that long term heat stress negatively impact on the growth of Picea seedlings, and alpine taxa are more affected than low altitude ones by high temperature stress. Hence the altitude ranges of Picea taxa should be taken into account when predicting changes to carbon fluxes in warmer conditions

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

• Leaf dark respiration (Rdark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits. • Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark. • Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8–28°C). By contrast, Rdark at a standard T (25°C, Rdark25) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark25 at a given photosynthetic capacity (Vcmax25) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark25 values at any given Vcmax25 or [N] were higher in herbs than in woody plants. • The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs)