Climate-driven tree mortality : insights from the piñon pine die-off in the United States

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Forest productivity under climate change : a checklist for evaluating model studies

Climate change is highly likely to impact on forest productivity over the next century. The direction and magnitude of change are uncertain because many factors are changing simultaneously, such as atmospheric composition, temperature, rainfall, and land use. Simulation models have been widely used to estimate how these interacting factors might combine to alter forest productivity. Such studies have used many different types of models with different underlying assumptions. To evaluate predictions made by such studies, it is essential to understand the type of model and the assumptions used. In this article, we provide a checklist for use when evaluating modeled estimates of climate change impacts on forest productivity. The checklist highlights the assumptions that we believe are critical in determining model outcomes. Models are classified into different general types, and assumptions relating to effects of atmospheric CO2 concentration, temperature, water availability, nutrient cycling, and disturbance are discussed. Our main aim is to provide a guide to enable correct interpretation of model projections. The article also challenges modelers to improve the quality of information provided about their model assumptions.24 page(s

Daily, seasonal and annual patterns of transpiration from a stand of remnant vegetation dominated by a coniferous Callitris species and a broad-leaved Eucalyptus species

Quantifying water use of native vegetation is an important contribution to understanding landscape ecohydrology. Few studies provide long-term (more than one growing season) estimates of water use and even fewer quantify interseasonal and interannual variation in transpiration. Globally, changes in land use are significantly altering landscape ecohydrology, resulting in problems such as dryland salinity and excessive groundwater recharge. Estimating stand water use is complex in multispecies forests, due to the differences in relationships among sapwood area, basal area and tree size for co-occurring species. In this article, we examine seasonal and interannual variation in transpiration rate of the tree canopy of two co-occurring species (a conifer Callitris glaucophylla J. Thompson & L.A.S. Johnson and a broad-leaved Eucalyptus crebra F. Muell.) in an open woodland in eastern Australia. Evapotranspiration of understorey species was measured using an open-top chamber, and tree water use was measured using heat-pulse sap flow sensors. Annual stand transpiration was 309 mm in 2003, a year of below average rainfall, and 629 mm in 2004, a year with higher-than-average rainfall. Despite an almost doubling (522 vs. 1062 mm) of annual rainfall between 2003 and 2004, annual tree water use remained a constant fraction (59%) of rainfall, indicative of compensatory mechanisms linking annual rainfall, leaf area index and tree water use. Deep drainage was estimated to be 4% of rainfall (20.8 mm) in 2003 and 2% (21.2 mm) in 2004, indicating that this native woodland was able to minimize deep drainage despite large interannual variability in rainfall.10 page(s

Forest mortality due to drought : latest insights, evidence and unresolved questions on physiological pathways and consequences of tree death

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Mechanistic causes of tree drought mortality : recent results, unresolved questions and future research needs

Report on the 96th Annual Meeting, Ecological Society of America in Austin, Texas, August 2011.4 page(s

Representing nighttime and minimum conductance in CLM4.5 : global hydrology and carbon sensitivity analysis using observational constraints

The terrestrial biosphere regulates climate through carbon, water, and energy exchanges with the atmosphere. Land-surface models estimate plant transpiration, which is actively regulated by stomatal pores, and provide projections essential for understanding Earth's carbon and water resources. Empirical evidence from 204 species suggests that significant amounts of water are lost through leaves at night, though land-surface models typically reduce stomatal conductance to nearly zero at night. Here, we test the sensitivity of carbon and water budgets in a global land-surface model, the Community Land Model (CLM) version 4.5, to three different methods of incorporating observed nighttime stomatal conductance values. We find that our modifications increase transpiration by up to 5 % globally, reduce modeled available soil moisture by up to 50 % in semi-arid regions, and increase the importance of the land surface in modulating energy fluxes. Carbon gain declines by up to  ∼ 4 % globally and  >  25 % in semi-arid regions. We advocate for realistic constraints of minimum stomatal conductance in future climate simulations, and widespread field observations to improve parameterizations.11 page(s

Seasonal variations in tree water use and physiology correlate with soil salinity and soil water content in remnant woodlands on saline soils

Ecophysiological studies of remnant woodlands in saline environments are scarce. We investigated seasonal fluctuations in soil water and salinity together with leaf and branch traits (area-based maximum assimilation (Amax), foliar nitrogen, specific leaf area (SLA) and Huber value (Hv)) and sap velocities of Eucalyptus macrorhyncha at four semi-arid sites in south-eastern Australia. Summer and winter soil salinities (10 cm depth) were 15-35 dS m⁻¹ and 8-10 dS m⁻¹ respectively. Gravimetric soil water content in the upper 20 cm was 2-5% in summer and 7-23% in winter, resulting in a significant inverse correlation between soil water and soil salinity. We found significant correlations between soil conditions and plant traits and function across seasons. Soil water content was significantly correlated with foliar N, SLA, Hv and maximum sap velocity while soil salinity was significantly correlated with Amax, Hv and maximum sap velocity. Correlations indicate co-variation of soil conditions and plant physiology in response to environmental conditions such as solar radiation and vapour pressure deficit (D). E. macrorhyncha tolerates the dual stresses of high salinity and low soil water during summer. While the plants appeared unhealthy, our data show that remnant vegetation can remain functional even in close proximity to saline scalds.9 page(s

Research frontiers in drought-induced tree mortality : crossing scales and disciplines

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Probability models of fire risk based on forest fire indices in contrasting climates over China

Fire weather indices have been widely applied to predict fire risk in many regions of the world. The objectives of this study were to establish fire risk probability models based on fire indices over different climatic regions in China. We linked the indices adopted in Canadian, US, and Australia with location, time, altitude, vegetation and fire characteristics during 1998–2007 in four regions using semi— parametric logistic (SPL) regression models. Different combinations of fire risk indices were selected as explanatory variables for specific regional probability model. SPL regression models of probability of fire ignition and large fire events were established to describe the non—linear relationship between fire risk indices and fire risk probabilities in the four regions. Graphs of observed versus estimated probabilities, fire risk maps, graphs of numbers of large fire events were produced from the probability models to assess the skill of these models. Fire ignition in all regions showed a significant link with altitude and NDVI. Indices of fuel moisture are important factors influencing fire occurrence in northern China. The fuel indices of organic material are significant indicators of fire risk in southern China. Besides the well skill of predicting fire risk, the probability models are a useful method to assess the utility of the fire risk indices in estimating fire events. The analysis presents some of the dynamics of climate-fire interactions and their value for management systems.13 page(s