Comparing the Penman-Monteith equation and a modified Jarvis-Stewart model with an artificial neural network to estimate stand-scale transpiration and canopy conductance

The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy conductance has then often been used to predict transpiration using the Penman-Monteith (PM) model. We previously suggested an alternative approach in which the JS model is modified to directly estimate transpiration rather than canopy conductance. In the present study we used this alternative approach to model tree water fluxes from an Australian native forest over an annual cycle. For comparative purposes we also modelled canopy conductance and estimated transpiration via the PM model. Finally we applied an artificial neural network as a statistical benchmark to compare the performance of both models. Both the PM and modified JS models were parameterised using solar radiation, vapour pressure deficit and soil moisture as inputs with results that compare well with previous studies. Both models performed comparably well during the summer period. However, during winter the PM model was found to fail during periods of high rates of transpiration. In contrast, the modified JS model was able to replicate observed sapflow measurements throughout the year although it too tended to underestimate rates of transpiration in winter under conditions of high rates of transpiration. Both approaches to modelling transpiration gave good agreement with hourly, daily and total sums of sapflow measurements with the modified JS and PM models explaining 87% and 86% of the variance, respectively. We conclude that these three approaches have merit at different time-scales. © 2009 Elsevier B.V. All rights reserved

Interactive effects of elevated CO <inf>2</inf> and drought on nocturnal water fluxes in Eucalyptus saligna

Nocturnal water flux has been observed in trees under a variety of environmental conditions and can be a significant contributor to diel canopy water flux. Elevated atmospheric CO 2 (elevated [CO 2]) can have an important effect on day-time plant water fluxes, but it is not known whether it also affects nocturnal water fluxes. We examined the effects of elevated [CO 2] on nocturnal water flux of field-grown Eucalyptus saligna trees using sap flux through the tree stem expressed on a sapwood area (J s) and leaf area (E t) basis. After 19 months growth under well-watered conditions, drought was imposed by withholding water for 5 months in the summer, ending with a rain event that restored soil moisture. Reductions in J s and E t were observed during the severe drought period in the dry treatment under elevated [CO 2], but not during moderate- and post-drought periods. Elevated [CO 2] affected night-time sap flux density which included the stem recharge period, called 'total night flux' (19:00 to 05:00, J s,r), but not during the post-recharge period, which primarily consisted of canopy transpiration (23:00 to 05:00, J s,c). Elevated [CO 2] wet (EW) trees exhibited higher J s,r than ambient [CO 2] wet trees (AW) indicating greater water flux in elevated [CO 2] under well-watered conditions. However, under drought conditions, elevated [CO 2] dry (ED) trees exhibited significantly lower J s,r than ambient [CO 2] dry trees (AD), indicating less water flux during stem recharge under elevated [CO 2]. J s,c did not differ between ambient and elevated [CO 2]. Vapour pressure deficit (D) was clearly the major influence on night-time sap flux. D was positively correlated with J s,r and had its greatest impact on J s,r at high D in ambient [CO 2]. Our results suggest that elevated [CO 2] may reduce night-time water flux in E. saligna when soil water content is low and D is high. While elevated [CO 2] affected J s,r, it did not affect day-time water flux in wet soil, suggesting that the responses of J s,r to environmental factors cannot be directly inferred from day-time patterns. Changes in J s,r are likely to influence pre-dawn leaf water potential, and plant responses to water stress. Nocturnal fluxes are clearly important for predicting effects of climate change on forest physiology and hydrology. © 2011 The Author. Published by Oxford University Press. A ll rights reserved

Elevated CO₂ does not increase eucalypt forest productivity on a low-phosphorus soil

Rising atmospheric CO2 stimulates photosynthesis and productivity of forests, offsetting CO2 emissions. Elevated CO2 experiments in temperate planted forests yielded ~23% increases in productivity over the initial years. Whether similar CO2 stimulation occurs in mature evergreen broadleaved forests on low-phosphorus (P) soils is unknown, largely due to lack of experimental evidence. This knowledge gap creates major uncertainties in future climate projections as a large part of the tropics is P-limited. Here,we increased atmospheric CO2 concentration in a mature broadleaved evergreen eucalypt forest for three years, in the first large-scale experiment on a P-limited site. We show that tree growth and other aboveground productivity components did not significantly increase in response to elevated CO2 in three years, despite a sustained 19% increase in leaf photosynthesis. Moreover, tree growth in ambient CO2 was strongly P-limited and increased by ~35% with added phosphorus. The findings suggest that P availability may potentially constrain CO2-enhanced productivity in P-limited forests; hence, future atmospheric CO2 trajectories may be higher than predicted by some models. As a result, coupled climate-carbon models should incorporate both nitrogen and phosphorus limitations to vegetation productivity in estimating future carbon sinks

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

An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance

The hypothesis that vegetation adapts optimally to its environment gives rise to a novel framework for modeling the interactions between vegetation dynamics and the catchment water balance that does not rely on prior knowledge about the vegetation at a particular site. We present a new model based on this framework that includes a multilayered physically based catchment water balance model and an ecophysiological gas exchange and photosynthesis model. The model uses optimization algorithms to find those static and dynamic vegetation properties that would maximize the net carbon profit under given environmental conditions. The model was tested at a savanna site near Howard Springs (Northern Territory, Australia) by comparing the modeled fluxes and vegetation properties with long-term observations at the site. The results suggest that optimality may be a useful way of approaching the prediction and estimation of vegetation cover, rooting depth, and fluxes such as transpiration and CO2 assimilation in ungauged basins without model calibration

Multi vegetation model evaluation of the Green Sahara climate regime

During the Quaternary, the Sahara desert was periodically colonized by vegetation, likely because of orbitally induced rainfall increases. However, the estimated hydrological change is not reproduced in climate model simulations, undermining confidence in projections of future rainfall. We evaluated the relationship between the qualitative information on past vegetation coverage and climate for the mid-Holocene using three different dynamic vegetation models. Compared with two available vegetation reconstructions, the models require 500–800 mm of rainfall over 20°–25°N, which is significantly larger than inferred from pollen but largely in agreement with more recent leaf wax biomarker reconstructions. The magnitude of the response also suggests that required rainfall regime of the early to middle Holocene is far from being correctly represented in general circulation models. However, intermodel differences related to moisture stress parameterizations, biases in simulated present-day vegetation, and uncertainties about paleosoil distributions introduce uncertainties, and these are also relevant to Earth system model simulations of African humid periods

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

Biophysical impacts of climate change on Australia's forests. Contribution of Work Package 2 to the Forest Vulnerability Assessment

The assessment of the vulnerability of Australian forests to climate change is an initiative of the Natural Resource Management Ministerial Council (NRMMC). The National Climate Change Adaptation Research Facility (NCCARF) was approached to carry out a comprehensive Forest Vulnerability Assessment (FVA). NCCARF engaged four research groups to investigate distinct aspects in relation to the vulnerability of forests, each of which has produced a report. In addition a fifth group was engaged to create a summary and synthesis report of the project. This report – Biophysical impacts of climate change on Australia's forests - is the second in the series. It presents a review of the primary literature on evidence of impacts of climate change on Australian forests. Existing evidence for climate change impacts in relation to direct stresses (CO2, temperature and rainfall), indirect stresses (fire, pests, pathogens and weeds) and plant processes (growth, transpiration and phenology) is discussed. The report concludes with a discussion of the overall impact of climate change on vegetation and the ecosystem services provided by forests. It should be noted that there have been several excellent reviews of climate change impacts on Australian forests as well as reports on climate change impacts on natural heritage and biodiversity. Conclusions drawn from these earlier reviews are not repeated. Instead, the report focuses on drawing evidence from the primary literature, including grey literature. Relevant literature was identified by bibliographic searches and in consultation with experts across Australia. This review highlighted a number of uncertainties involved in assessing forest vulnerability to climate change. These include uncertainty over changes in the climate, the ecosystem-scale responses to climate change, and interactions of climate change impacts with other global change processes. There is, however, clear evidence of the impact of some individual factors