An ecoregion assessment of projected tree species vulnerabilities in western North America through the 21st century.

Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this study was to identify which ecological regions might expect the greatest changes to occur. We used the process-based growth model 3-PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of one km. Projected suitable areas for tree species were compared to their current ranges based on observations at >40 000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to <200 m yr-1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types.

Predicting large wildfires across western North America by modeling seasonal variation in soil water balance.

A lengthening of the fire season, coupled with higher temperatures, increases the probability of fires throughout much of western North America. Although regional variation in the frequency of fires is well established, attempts to predict the occurrence of fire at a spatial resolution <10 km2 have generally been unsuccessful. We hypothesized that predictions of fires might be improved if depletion of soil water reserves were coupled more directly to maximum leaf area index (LAImax) and stomatal behavior. In an earlier publication, we used LAImax and a process-based forest growth model to derive and map the maximum available soil water storage capacity (ASWmax) of forested lands in western North America at l km resolution. To map large fires, we used data products acquired from NASA's Moderate Resolution Imaging Spectroradiometers (MODIS) over the period 2000-2009. To establish general relationships that incorporate the major biophysical processes that control evaporation and transpiration as well as the flammability of live and dead trees, we constructed a decision tree model (DT). We analyzed seasonal variation in the relative availability of soil water (fASW) for the years 2001, 2004, and 2007, representing respectively, low, moderate, and high rankings of areas burned. For these selected years, the DT predicted where forest fires >1 km occurred and did not occur at ~100,000 randomly located pixels with an average accuracy of 69 %. Extended over the decade, the area predicted burnt varied by as much as 50 %. The DT identified four seasonal combinations, most of which included exhaustion of ASW during the summer as critical; two combinations involving antecedent conditions the previous spring or fall accounted for 86 % of the predicted fires. The approach introduced in this paper can help identify forested areas where management efforts to reduce fire hazards might prove most beneficial.

Satellite observed widespread decline in Mongolian grasslands largely due to overgrazing.

The Mongolian Steppe is one of the largest remaining grassland ecosystems. Recent studies have reported widespread decline of vegetation across the steppe and about 70% of this ecosystem is now considered degraded. Among the scientific community there has been an active debate about whether the observed degradation is related to climate, or over-grazing, or both. Here, we employ a new atmospheric correction and cloud screening algorithm (MAIAC) to investigate trends in satellite observed vegetation phenology. We relate these trends to changes in climate and domestic animal populations. A series of harmonic functions is fitted to Moderate Resolution Imaging Spectroradiometer (MODIS) observed phenological curves to quantify seasonal and inter-annual changes in vegetation. Our results show a widespread decline (of about 12% on average) in MODIS observed normalized difference vegetation index (NDVI) across the country but particularly in the transition zone between grassland and the Gobi desert, where recent decline was as much as 40% below the 2002 mean NDVI. While we found considerable regional differences in the causes of landscape degradation, about 80% of the decline in NDVI could be attributed to increase in livestock. Changes in precipitation were able to explain about 30% of degradation across the country as a whole but up to 50% in areas with denser vegetation cover (P < 0.05). Temperature changes, while significant, played only a minor role (r(2)  = 0.10, P < 0.05). Our results suggest that the cumulative effect of overgrazing is a primary contributor to the degradation of the Mongolian steppe and is at least partially responsible for desertification reported in previous studies.

Evaluating theories of drought-induced vegetation mortality using a multimodel-experiment framework.

SUMMARY: Model-data comparisons of plant physiological processes provide an understanding of mechanisms underlying vegetation responses to climate. We simulated the physiology of a piñon pine-juniper woodland (Pinus edulis-Juniperus monosperma) that experienced mortality during a 5 yr precipitation-reduction experiment, allowing a framework with which to examine our knowledge of drought-induced tree mortality. We used six models designed for scales ranging from individual plants to a global level, all containing state-of-the-art representations of the internal hydraulic and carbohydrate dynamics of woody plants. Despite the large range of model structures, tuning, and parameterization employed, all simulations predicted hydraulic failure and carbon starvation processes co-occurring in dying trees of both species, with the time spent with severe hydraulic failure and carbon starvation, rather than absolute thresholds per se, being a better predictor of impending mortality. Model and empirical data suggest that limited carbon and water exchanges at stomatal, phloem, and below-ground interfaces were associated with mortality of both species. The model-data comparison suggests that the introduction of a mechanistic process into physiology-based models provides equal or improved predictive power over traditional process-model or empirical thresholds. Both biophysical and empirical modeling approaches are useful in understanding processes, particularly when the models fail, because they reveal mechanisms that are likely to underlie mortality. We suggest that for some ecosystems, integration of mechanistic pathogen models into current vegetation models, and evaluation against observations, could result in a breakthrough capability to simulate vegetation dynamics.

Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes.

Predicting tree diversity across the United States as a function of modeled gross primary production.

At the regional and continental scale, ecologists have theorized that spatial variation in biodiversity can be interpreted as a response to differences in climate. To test this theory we assumed that ecological constraints associated with current climatic conditions (2000-2004) might best be correlated with tree richness if expressed through satellite-derived measures of gross primary production (GPP), rather than the more commonly used, but less consistently derived, net primary production. To evaluate current patterns in tree diversity across the contiguous United States we acquired information on tree composition from the USDA Forest Service's Forest Inventory and Analysis program that represented more than 17,4000 survey plots. We selected 2693 cells of 1000 km2 within which a sufficient number of plots were available to estimate tree richness per hectare. Our estimates of forest productivity varied from simple vegetation indices indicative of the fraction of light intercepted by canopies at 16-d intervals, a product from the MODIS (Moderate Resolution Imaging Spectro-radiometer), to 8- and 10-d GPP products derived with minimal climatic data (MODIS) and SPOT-Vegetation (Systeme Pour l'Observation de la Terre), to 3-PGS (Physiological Principles Predicting Growth with Satellites), which requires both climate and soil data. Across the contiguous United States, modeled predictions of gross productivity accounted for between 51% and 77% of the recorded spatial variation in tree diversity, which ranged from 2 to 67 species per hectare. When the analyses were concentrated within nine broadly defined ecoregions, predictive relations largely disappeared. Only 3-PGS predictions fit a theorized unimodal function by being able to distinguish highly productive forests in the Pacific Northwest that support lower than expected tree diversity. Other models predicted a continuous steep rise in tree diversity with increasing productivity, and did so with generally better or nearly equal precision with fewer data requirements.

Lessons learned while extending physiological principles from growth chambers to satellite studies.

Over the last three decades, physiological principles established in laboratory studies have been applied to systems at progressively larger scales and are now firmly merged into the fields of ecology, ecosystem modeling, forest protection, and global change research. To expand the vision of any field requires that scientists from different disciplines build a bridge across the chasm that normally exists between the knowledge bases and perspectives of different fields. Bridges are built most quickly when representatives of different disciplines see the possibility of mutual advantage in collaboration and seek to quickly demonstrate that potential. Usually, however, the process is laborious because approaches and techniques must be modified to address problems at a different level of integration. Successful bridge builders have, almost without exception, established credibility in their own field and have then identified a kindred spirit with similar credentials in another. They usually establish a pilot study that involves apprentices as well as established scientists. If the approach is successful, the younger members of the team often take the lead in further advancements. Managers of large centralized programs should foster interdisciplinary exchange, particularly at times when advancement in one field languishes. To expand collaboration, it is often necessary for scientists to seek common properties that simplify relations across a wide range of biological and physical conditions. This integrative perspective is essential and is fostered by participating in cross-disciplinary workshops and conferences and by reading outside one's field.

Effects of branch length on carbon isotope discrimination in Pinus radiata.

Gas exchange was measured on a pruned Pinus radiata D. Don hedge and on a long-branch P. radiata tree near Hamilton, New Zealand, in spring 1993 when soil water content was close to field capacity. Foliage at the end of long branches (9.0 m) showed a marked drop in net photosynthetic rate and stomatal conductance as the saturation deficit increased, whereas foliage on short branches (0.5 m) showed little change. Mean foliage delta(13)C was -30.1 per thousand for short branches and -26.3 per thousand for long branches. Foliage delta(13)C was correlated with branch length in two genetically improved P. radiata seedlots at four stocking densities. The multinodal seedlot had shorter branches and more (13)C-depleted foliage compared with branches and foliage from the long internode seedlot. There was a strong effect of stocking density on carbon isotope composition in both seedlots. We conclude that branch morphology affects foliage gas exchange properties and foliage carbon isotope composition.

Woody tissue maintenance respiration of four conifers in contrasting climates.

We estimate maintenance respiration for boles of four temperate conifers (ponderosa pine, western hemlock, red pine, and slash pine) from CO2 efflux measurements in autumn, when construction respiration is low or negligible. Maintenance respiration of stems was linearly related to sapwood volume for all species; at 10°C, respiration per unit sapwood volume ranged from 4.8 to 8.3 µmol CO2 m-3 s-1. For all sites combined, respiration increased exponentially with temperature (Q 10 =1.7, r 2=0.78). We estimate that maintenance respiration of aboveground woody tissues of these conifers consumes 52-162 g C m-2 y-1, or 5-13% of net daytime carbon assimilation annually. The fraction of annual net daytime carbon fixation used for stem maintenance respiration increased linearly with the average annual temperature of the site.