Amy E. Hessl

DROUGHT AND PACIFIC DECADAL OSCILLATION LINKED TO FIRE OCCURRENCE IN THE INLAND PACIFIC NORTHWEST

Historical variability of fire regimes must be understood within the context of climatic and human drivers of disturbance occurring at multiple temporal scales. We describe the relationship between fire occurrence and interannual to decadal climatic var- iability (Palmer Drought Severity Index (PDSI), El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO)) and explain how land use changes in the 20th century affected these relationships. We used 1701 fire-scarred trees collected in five study sites in central and eastern Washington State (USA) to investigate current year, lagged, and low frequency relationships between composite fire histories and PDSI, PDO, and ENSO (using the Southern Oscillation Index (SOI) as a measure of ENSO variability) using superposed epoch analysis and cross-spectral analysis. Fires tended to occur during dry summers and during the positive phase of the PDO. Cross-spectral analysis indicates that percentage of trees scarred by fire and the PDO are spectrally coherent at 47 years, the approximate cycle of the PDO. Similarly, percentage scarred and ENSO are spectrally coherent at six years, the approximate cycle of ENSO. However, other results suggest that ENSO was only a weak driver of fire occurrence in the past three centuries. While drought and fire appear to be tightly linked between 1700 and 1900, the relationship between drought and fire occurrence was disrupted during the 20th century as a result of land use changes. We suggest that long-term fire planning using the PDO may be possible in the Pacific Northwest, potentially allowing decadal-scale management of fire regimes, prescribed fire, and vege- tation dynamics.

Climate drivers of regionally synchronous fires in the inland northwest (1651-1900)

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TAKING THE PULSE OF MOUNTAINS: ECOSYSTEM RESPONSES TO CLIMATIC VARIABILITY

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Pluvials, droughts, the Mongol Empire, and modern Mongolia

Significance A 1,112-y tree-ring record of moisture shows that in opposition to conventional wisdom, the climate during the rise of the 13th-century Mongol Empire was a period of persistent moisture, unprecedented in the last 1,000 y. This 15-y episode of persistent moisture likely led to a period of high grassland productivity, contributing fuel to the Mongol Empire. We also present evidence that anthropogenic warming exacerbated the 21st-century drought in central Mongolia. These results indicate that ecosystems and societies in semiarid regions can be significantly affected by unusual climatic events at the decadal time scale. Although many studies have associated the demise of complex societies with deteriorating climate, few have investigated the connection between an ameliorating environment, surplus resources, energy, and the rise of empires. The 13th-century Mongol Empire was the largest contiguous land empire in world history. Although drought has been proposed as one factor that spurred these conquests, no high-resolution moisture data are available during the rapid development of the Mongol Empire. Here we present a 1,112-y tree-ring reconstruction of warm-season water balance derived from Siberian pine (Pinus sibirica) trees in central Mongolia. Our reconstruction accounts for 56% of the variability in the regional water balance and is significantly correlated with steppe productivity across central Mongolia. In combination with a gridded temperature reconstruction, our results indicate that the regional climate during the conquests of Chinggis Khan’s (Genghis Khan’s) 13th-century Mongol Empire was warm and persistently wet. This period, characterized by 15 consecutive years of above-average moisture in central Mongolia and coinciding with the rise of Chinggis Khan, is unprecedented over the last 1,112 y. We propose that these climate conditions promoted high grassland productivity and favored the formation of Mongol political and military power. Tree-ring and meteorological data also suggest that the early 21st-century drought in central Mongolia was the hottest drought in the last 1,112 y, consistent with projections of warming over Inner Asia. Future warming may overwhelm increases in precipitation leading to similar heat droughts, with potentially severe consequences for modern Mongolia.

Pathways for climate change effects on fire: Models, data, and uncertainties:

Fire is a global process affecting both the biosphere and the atmosphere. As a result, measuring rates of change in wildland fire and understanding the mechanisms responsible for such changes are important research goals. A large body of modeling studies projects increases in wildfire activity in future decades, but few empirical studies have documented change in modern fire regimes. Identifying generalizable pathways through which climate change may alter fire regimes is a critical next step for understanding, measuring, and modeling fire under a changing climate. In this progress report, I review recent model-, empirical-, and fire history-based studies of fire and climate change and propose three pathways along which fire regimes might respond to climate change: changes in fuel condition, fuel volume, and ignitions. Model- and empirical-based studies have largely focused on changes in fuel condition with some models projecting up to 50% increases in area burned under a 2 x CO2 climate. Fire history data derived from tree-rings, sediment charcoal, and soil charcoal have helped identify past trajectories of change in fire regimes and can point to possible future conditions. However, most fire history research has focused on changes in area burned and fire frequency. Changes in fire severity may be equally important for the earth system and require further attention. Critical research needs include next generation dynamic vegetation models (DGVMs) that consider changes in vegetation alongside changes in human activities and long fire history records from a variety of vegetation types suitable for validating these DGVMs.

The Legacy of Episodic Climatic Events in Shaping Temperate, Broadleaf Forests

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning ∼840 000 km2 and 5327 tree recruitment dates spanning ∼1.4 million km2 across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as “heavy tailed,” with most of the years from 1775 to 1780 comprising th...

Mapping Paleo-Fire Boundaries from Binary Point Data: Comparing Interpolation Methods

Abstract Fire history studies have traditionally emphasized temporal rather than spatial properties of paleo-fire regimes. In this study we compare four methods of mapping paleo-fires in central Washington from binary point data: indicator kriging, inverse distance weighting, Thiessen polygons, and an expert approach. We evaluate the results of each mapping method using a test (validation) dataset and receiver operating characteristic plots. Interpolation methods perform well, but results vary with fire size and spatial pattern of points. Though all methods involve some subjectivity, automated interpolation methods perform well, are replicable, and can be applied across varying landscapes.

Spatial models for inferring topographic controls on historical low-severity fire in the eastern Cascade Range of Washington, USA

Fire regimes are complex systems that represent an aggregate of spatial and temporal events whose statistical properties are scale dependent. Despite the breadth of research regarding the spatial controls on fire regime variability, few datasets are available with sufficient resolution to test spatially explicit hypotheses. We used a spatially distributed network of georeferenced fire-scarred trees to investigate the spatial structure of fire occurrence at multiple scales. Mantel’s tests and geostatistical analysis of fire-occurrence time series led to inferences about the mechanisms that generated spatial patterns of historical fire synchrony (multiple trees recording fire in a single year) in eastern Washington, USA. The spatial autocorrelation structure of historical fire regimes varied within and among sites, with clearer patterns in the complex rugged terrain of the Cascade Range than in more open and rolling terrain further north and east. Results illustrate that the statistical spatial characteristics of fire regimes change with landform characteristics within a forest type, suggesting that simple relationships between fire frequency, fire synchrony, and forest type do not exist. Quantifying the spatial structures in fire occurrence associated with topographic variation showed that fire regime variability depends on both landscape structure and the scale of measurement. Spatially explicit fire-scar data open new possibilities for analysis and interpretation, potentially informing the design and application of fire management on landscapes, including hazardous fuel treatments and the use of fire for ecosystem restoration.

Climate remains an important driver of post‐European vegetation change in the eastern United States

Department of Geography, University of Wisconsin-Madison, 550 North ParkStreet, Madison, WI 53706, USAThe influence of climate on forest change during thepast century in the eastern United States was evalu-ated in a recent paper (Nowacki & Abrams, 2014)that centers on an increase in ‘highly competitivemesophytic hardwoods’ (Nowacki & Abrams, 2008)and a concomitant decrease in the more xerophyticQuercus species. Nowacki & Abrams (2014) con-cluded that climate change has not contributed sig-nificantly to observed changes in forest composition.However, the authors restrict their focus to a singleelement of climate: increasing temperature since theend of the Little Ice Age ca. 150 years ago. In theirstudy, species were binned into four classifications(e.g., Acer saccharum – ‘cool-adapted’, Acer rubrum –‘warm-adapted’) based on average annual tempera-ture within each species range in the United States,reducing the multifaceted character of climate into asingle, categorical measure. The broad temperatureclasses not only veil the many biologically relevantaspects of temperature (e.g., seasonal and extremetemperatures) but they may also mask other influ-ences, both climatic (e.g., moisture sensitivity) andnonclimatic (e.g., competition).Understanding the primary drivers of forest changeis critically important. However, using annual tem-perature reduces the broad spectrum of climaticinfluence on forests (e.g., Jackson & Overpeck, 2000;Jackson et al., 2009) to a single variable. Tsuga canad-ensis illustrates one example of the complex interac-tion between trees and temperature. In the southernpart of its range, Tsuga canadensis growth is weakly,but positively correlated with early growing-seasontemperature. However, this relationship becomesstronger and shifts to later in the season toward thenorthern part of its range (Cook & Cole, 1991). More-over, Tsuga canadensis growth is significantly andnegatively correlated with just May temperaturesduring the current growing season in the northeast-ern United States (Cook, 1991; Cook & Cole, 1991;Vaganov et al., 2011), while in the southeastern Uni-ted States it is strongly and negatively correlatedwith summer (June–August) temperatures (Hart et al.,2010). Trees can also be sensitive to diverse and ofteninteracting climate variables at various stages of theirlife cycles (Jackson et al., 2009). Interactions betweenprecipitation and temperature are clearly important(Harsch & Hille Ris Lambers, 2014; Martin-Benito &Pederson, accepted), and often lead to counterintui-tive responses. For example, some plant species thatwould have been expected to move north and ups-

Using neutral models to identify constraints on low-severity fire regimes.

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes. With a suitable neutral model, characteristics of natural fire regimes estimated from fire history data can be compared to a “null hypothesis”. We generated random landscapes of fire-scarred trees via a point process with sequential spatial inhibition. Random ignition points, fire sizes, and fire years were drawn from uniform and exponential family probability distributions. We compared two characteristics of neutral fire regimes to those from five watersheds in eastern Washington that have experienced low-severity fire. Composite fire intervals (CFIs) at multiple spatial scales displayed similar monotonic decreases with increasing sample area in neutral vs. real landscapes, although patterns of residuals from statistical models differed. In contrast, parameters of the Weibull distribution associated with temporal trends in fire hazard exhibited different forms of scale dependence in real vs. simulated data. Clear patterns in neutral landscapes suggest that deviations from them in empirical data represent real constraints on fire regimes (e.g., topography, fuels). As with any null model, however, neutral fire-regime models need to be carefully tuned to avoid confounding these constraints with artifacts of modeling. Neutral models show promise for investigating low-severity fire regimes to separate intrinsic properties of stochastic processes from the effects of climate, fuel loadings, topography, and management.