Steve McNulty

Climate Change and Forest Disturbances

tudies of the effects of climate change on forestshave focused on the ability of species to tolerate tem-perature and moisture changes and to disperse,but they haveignored the effects of disturbances caused by climate change(e.g.,Ojima et al.1991).Yet modeling studies indicate the im-portance of climate effects on disturbance regimes (He et al.1999). Local, regional, and global changes in temperatureand precipitation can influence the occurrence, timing, fre-quency,duration,extent,and intensity of disturbances (Baker1995, Turner et al. 1998). Because trees can survive fromdecades to centuries and take years to become established,climate-change impacts are expressed in forests, in part,through alterations in disturbance regimes (Franklin et al.1992, Dale et al. 2000).Disturbances,both human-induced and natural,shape for-est systems by influencing their composition,structure,andfunctional processes.Indeed,the forests of the United Statesare molded by their land-use and disturbance history.Withinthe United States,natural disturbances having the greatest ef-fects on forests include fire,drought,introduced species,in-sect and pathogen outbreaks, hurricanes, windstorms, icestorms, and landslides (Figure 1). Each disturbance affectsforests differently. Some cause large-scale tree mortality,whereas others affect community structure and organizationwithout causing massive mortality (e.g., ground fires). For-est disturbances influence how much carbon is stored intrees or dead wood. All these natural disturbances interactwith human-induced effects on the environment,such as airpollution and land-use change resulting from resource ex-traction, agriculture, urban and suburban expansion, andrecreation.Some disturbances can be functions of both nat-ural and human conditions (e.g., forest fire ignition andspread) (Figure 2).

Forest Processes and Global Environmental Change: Predicting the Effects of Individual and Multiple Stressors

G change involves the simultaneous and rapid alteration of several key environmental parameters that control the dynamics of forests. We cannot predict with certainty, through direct experimentation, what the responses of forests to global change will be, because we cannot carry out the multisite, multifactorial experiments required for doing so. The physical extent, complexity, and expense of even single-factor experiments at the scale of the whole ecosystem challenge our abilities, although several such experiments have been successfully undertaken (e.g., DeLucia et al. 1999, Wright and Rasmussen 1998). To inform policy decisions, however, the scientific community can offer an interdisciplinary synthesis of existing information. When this synthesis takes the form of a computer model, quantitative predictions can be made that integrate what has been learned from single-factor experiments. The success of such an approach depends on the quality and completeness of the information base and on the rigor of the modeling effort. The direct and secondary physiological effects of changes in the physical and chemical climate on plants and soils are relatively well known. We also know which primary environmental drivers—precipitation, temperature, and atmospheric concentrations of carbon dioxide (CO2), ozone (O3), and nitrogen (N), for example—are being altered by human activities, and we can directly measure temporal change in these parameters. Despite this relatively rich information base, predictions of future responses of forests to environmental change show significant variation. This is due in part to differences between the models of ecosystem function derived from the existing database and in part to differences in climate scenarios generated by the general circulation models (GCMs) used to predict future climates. Understanding both the trend in predicted futures and the uncertainties surrounding those trends is critical to policy formation. At this time, the major mechanism for determining the degree of uncertainty in predictions is through comparison of results from runs of different models using identical input parameters. The purpose of this article is to review the state of prediction of forest ecosystem response to envisioned changes in the physical and chemical climate. These results are offered as one part of the forest sector analysis of the National Assessment

The interplay between climate change, forests, and disturbances

Climate change affects forests both directly and indirectly through disturbances. Disturbances are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. When disturbances exceed their natural range of variation, the change in forest structure and function may be extreme. Each disturbance affects forests differently. Some disturbances have tight interactions with the species and forest communities which can be disrupted by climate change. Impacts of disturbances and thus of climate change are seen over a board spectrum of spatial and temporal scales. Future observations, research, and tool development are needed to further understand the interactions between climate change and forest disturbances.

REGENERATION IN GAP MODELS: PRIORITY ISSUES FOR STUDYING FOREST RESPONSES TO CLIMATE CHANGE

Recruitment algorithms in forest gap models are examined withparticular regard to their suitability for simulating forestecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seedproduction, dispersal, storage, germination and seedling establishment) is likely to result in less accurate predictionsof responses as compared to treating each stage separately. Second, the related assumptions that seeds of all species are uniformly available and that environmental conditions arehomogeneous, are likely to cause overestimates of future speciesdiversity and forest migration rates. Third, interactions between herbivores (ungulates and insect pests) and forest vegetation are a big unknown with potentially serious impactsin many regions. Possible strategies for developing better gapmodel representations for the climate-sensitive aspects of eachof these key areas are discussed. A working example of a relatively new model that addresses some of these limitations is also presented for each case. We conclude that better modelsof regeneration processes are desirable for predicting effectsof climate change, but that it is presently impossible to determine what improvements can be expected without carrying outrigorous tests for each new formulation.

Observations and assessment of forest carbon dynamics following disturbance in North America

Disturbance processes of various types substantially modify ecosystem carbon dynamics both temporally and spatially, and constitute a fundamental part of larger landscape-level dynamics. Forests typically lose carbon for several years to several decades following severe disturbance, but our understanding of the duration and dynamics of post-disturbance forest carbon fluxes remains limited. Here we capitalize on a recent North American Carbon Program disturbance synthesis to discuss techniques and future work needed to better understand carbon dynamics after forest disturbance. Specifically, this paper addresses three topics: (1) the history, spatial distribution, and characteristics of different types of disturbance (in particular fire, insects, and harvest) in North America; (2) the integrated measurements and experimental designs required to quantify forest carbon dynamics in the years and decades after disturbance, as presented in a series of case studies; and (3) a synthesis of the greatest uncertainties spanning these studies, as well as the utility of multiple types of observations (independent but mutually constraining data) in understanding their dynamics. The case studies—in the southeast U.S., central boreal Canada, U.S. Rocky Mountains, and Pacific Northwest—explore how different measurements can be used to constrain and understand carbon dynamics in regrowing forests, with the most important measurements summarized for each disturbance type. We identify disturbance severity and history as key but highly uncertain factors driving post-disturbance carbon source-sink dynamics across all disturbance types. We suggest that imaginative, integrative analyses using multiple lines of evidence, increased measurement capabilities, shared models and online data sets, and innovative numerical algorithms hold promise for improved understanding and prediction of carbon dynamics in disturbance-prone forests.

Drought during canopy development has lasting effect on annual carbon balance in a deciduous temperate forest

* Climate change projections predict an intensifying hydrologic cycle and an increasing frequency of droughts, yet quantitative understanding of the effects on ecosystem carbon exchange remains limited. * Here, the effect of contrasting precipitation and soil moisture dynamics were evaluated on forest carbon exchange using 2 yr of eddy covariance and microclimate data from a 50-yr-old mixed oak woodland in northern Ohio, USA. * The stand accumulated 40% less carbon in a year with drought between bud-break and full leaf expansion (354 +/- 81 g C m(-2) yr(-1) in 2004 and 252 +/- 45 g C m(-2) yr(-1) in 2005). This was caused by greater suppression of gross ecosystem productivity (GEP; 16% = 200 g) than of ecosystem respiration (ER; 11% = 100 g) by drought. Suppressed GEP was traced to lower leaf area, lower apparent quantum yield and lower canopy conductance. The moisture sensitivity of ER may have been mediated by GEP. * The results highlight the vulnerability of the ecosystem to even a moderate drought, when it affects a critical aspect of development. Although the drought was preceded by rain, the storage capacity of the soil seemed limited to 1-2 wk, and therefore droughts longer than this are likely to impair productivity in the region.

Streamflow response to climate and landuse changes in a coastal watershed in North Carolina

It is essential to examine the sensitivity of hydrologic responses to climate and landuse change across different physiographic regions in order to formulate sound water management policies for local response to projected global change. This study used the U.S. Geological Surveys Precipitation Runoff Modeling System (PRMS) model to examine the potential impacts of climate and landuse changes on the monthly streamflow of the Trent River basin on the lower coastal plain of eastern North Carolina. The model was first calibrated and then validated using measured, historic, long-term daily streamflow. The model performed satisfactorily for simulating monthly streamflow, as indicated by an overall Nash-Sutcliffe simulation efficiency greater than 0.85. We examined the sensitivity of streamflow to changes in air temperature and precipitation. The simulations suggested that streamflow of individual years could change from -93% to 238%, depending on the two global circulation model (GCM) scenarios used (i.e., HadCMSul2 and CGC1). Streamflow of the Trent River will decrease with an increase in air temperature, and increase (or decrease) with an increase (or decrease) in precipitation. Streamflow was more sensitive to prescribed changes in precipitation than to air temperature for the study area, given its high and stable evapotranspiration rates in the humid climatic environment. Seven hypothetical landuse change scenarios representing forest conversion to crop lands and urban areas indicated that water yield could increase by 14% to 20%. The likely impacts of landuse changes may not be as high as those caused by predicted changes in climate, but moderate urbanization and extreme hydrologic events caused by climate change could pose significant water quantity and quality problems in the Trent River basin.

Loblolly pine hydrology and productivity across the southern United States

Abstract Concern over future changes in water yield and timber production in southern pine forests has increased the need for a well tested and validated forest ecosystem model which can be used to predict potential climate change effects on forest processes. However, before a model is used to project potential climate change impacts on forests, it should first be validated across a wide range of climates and site conditions. We used PnET-IIS, a physiologically-based, monthly time-step model that uses soil, vegetation, and climate parameter inputs to predict evapotranspiration, drainage, soil water stress and net primary productivity for loblolly pine ( Pinus taeda ) stands across the southern United States. Sensitivity analyses and model validation of predicted net primary productivity (NPP) were conducted. Predicted hydrology and productivity were most sensitive to temperature driven parameters (e.g. optimal temperature for photosynthesis, and changes in air temperature). Values of PnET-IIS predicted NPP were compared with measured annual site basal area growth from 12 stands located from eastern Texas to eastern Virginia, from the year of site canopy closure to 1990. Annual basal area growth ranged from 4.2 to 26.8 cm 2 per tree year −1 . Annual basal area growth was significantly correlated with predicted NPP ( r 2 = 0.30, P n = 164) and the correlation improved when annual basal area growth was averaged by site ( r 2 = 0.66, P n = 12). Total annual precipitation was the single climate variable which best correlated with annual basal area growth ( r 2 = 0.66, P n = 12). These result indicate that PnET-IIS could be useful in predicting the effect of changing patterns of precipitation and air temperature on southern pine hydrology and productivity.

Poplar plantation has the potential to alter the water balance in semiarid inner Mongolia

Poplar plantation is the most dominant broadleaf forest type in northern China. Since the mid-1990s plantation was intensified to combat desertification along Chinas northwestern border, i.e., within Inner Mongolia (IM). This evoked much concern regarding the ecological and environmental effects on areas that naturally grow grass or shrub vegetation. To highlight potential consequences of large-scale poplar plantations on the water budget within semiarid IM, we compared the growing season water balance (evapotranspiration (ET) and precipitation (PPT)) of a 3-yr old poplar plantation (Kp(3)) and a natural shrubland (Ks) in the Kubuqi Desert in western IM, and a 6-yr old poplar plantation (Bp(6)) growing under sub-humid climate near Beijing. The results showed that, despite 33% lower PPT at Kp(3), ET was 2% higher at Kp(3) (228 mm) as compared with Ks (223 mm) in May-September 2006. The difference derived mainly from higher ET at the plantation during drier periods of the growing season, which also indicated that the poplars must have partly transpired groundwater. Estimated growing season ET at Bp(6) was about 550 mm and more than 100% higher than at Kp(3). It is estimated that increases in leaf area index and net radiation at Kp(3) provide future potential for the poplars in Kubuqi to exceed the present ET and ET of the natural shrubland by 100-200%. These increases in ET are only possible through the permanent use of groundwater either directly by the trees or through increased irrigation. This may significantly change the water balance in the area (e.g., high ET at the cost of a reduction in the water table), which renders large-scale plantations a questionable tool in sustainable arid-land management.

Interactive effects of nocturnal transpiration and climate change on the root hydraulic redistribution and carbon and water budgets of southern United States pine plantations

Deep root water uptake and hydraulic redistribution (HR) have been shown to play a major role in forest ecosystems during drought, but little is known about the impact of climate change, fertilization and soil characteristics on HR and its consequences on water and carbon fluxes. Using data from three mid-rotation loblolly pine plantations, and simulations with the process-based model MuSICA, this study indicated that HR can mitigate the effects of soil drying and had important implications for carbon uptake potential and net ecosystem exchange (NEE), especially when N fertilization is considered. At the coastal site (C), characterized by deep organic soil, HR increased dry season tree transpiration (T) by up to 40%, and such an increase affected NEE through major changes in gross primary productivity (GPP). Deep-rooted trees did not necessarily translate into a large volume of HR unless soil texture allowed large water potential gradients to occur, as was the case at the sandy site (S). At the Piedmont site (P) characterized by a shallow clay-loam soil, HR was low but not negligible, representing up to 10% of T. In the absence of HR, it was predicted that at the C, S and P sites, annual GPP would have been diminished by 19, 7 and 9%, respectively. Under future climate conditions HR was predicted to be reduced by up to 25% at the C site, reducing the resilience of trees to precipitation deficits. The effect of HR on T and GPP was predicted to diminish under future conditions by 12 and 6% at the C and P sites, respectively. Under future conditions, T was predicted to stay the same at the P site, but to be marginally reduced at the C site and slightly increased at the S site. Future conditions and N fertilization would decrease T by 25% at the C site, by 15% at the P site and by 8% at the S site. At the C and S sites, GPP was estimated to increase by 18% and by >70% under future conditions, respectively, with little effect of N fertilization. At the P site, future conditions would stimulate GPP by only 12%, but future conditions plus N fertilization would increase GPP by 24%. As a consequence, in all sites, water use efficiency was predicted to improve dramatically with future conditions. Modeling the effect of reduced annual precipitation indicated that limited water availability would decrease all carbon fluxes, including NEE and respiration. Our simulations highlight the interactive effects of nutrients and elevated CO(2), and showed that the effect of N fertilization would be greater under future climate conditions.