No abstract

No abstract

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Applied historical ecology is the use of historical knowledge in the management of ecosystems. Historical perspectives increase our understanding of the dynamic nature of landscapes and provide a frame of reference for assessing modern patterns and processes. Historical records, however, are often too brief or fragmentary to be useful, or they are not obtainable for the process or structure of interest. Even where long historical time series can be assembled, selection of appropriate reference conditions may be complicated by the past influence of humans and the many potential reference conditions encompassed by nonequilibrium dynamics. These complications, however, do not lessen the value of history; rather they underscore the need for multiple, comparative histories from many locations for evaluating both cultural and natural causes of variability, as well as for characterizing the overall dynamical properties of ecosystems. Historical knowledge may not simplify the task of setting management goals and making decisions, but 20th century trends, such as increasingly severe wildfires, suggest that disregarding history can be perilous.We describe examples from our research in the southwestern United States to illustrate some of the values and limitations of applied historical ecology. Paleoecological data from packrat middens and other natural archives have been useful for defining baseline conditions of vegetation communities, determining histories and rates of species range expansions and contractions, and discriminating between natural and cultural causes of environmental change. We describe a montane grassland restoration project in northern New Mexico that was justified and guided by an historical sequence of aerial photographs showing progressive tree invasion during the 20th century. Likewise, fire scar chronologies have been widely used to justify and guide fuel reduction and natural fire reintroduction in forests. A southwestern network of fire histories illustrates the power of aggregating historical time series across spatial scales. Regional fire patterns evident in these aggregations point to the key role of interannual lags in responses of fuels and fire regimes to the El Niñ o-Southern Oscillation (wet/dry cycles), with important implications for long-range fire hazard forecasting. These examples of applied historical ecology emphasize that detection and explanation of historical trends and variability are essential to informed management.

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

[1] We present a tree-ring based reconstruction of the Atlantic Multidecadal Oscillation (AMO) which demonstrates that strong, low-frequency (60 -100 yr) variability in basin-wide (0 -70°N) sea surface temperatures (SSTs) has been a consistent feature of North Atlantic climate for the past five centuries. Intervention analysis of reconstructed AMO indicates that 20th century modes were similar to those in the preceding $350 yr, and wavelet spectra show robust multidecadal oscillations throughout the reconstruction. Though the exact relationships between low-frequency SST modes, higher frequency ($7-25 yr) atmospheric modes (e.g., North Atlantic Oscillation/Arctic Oscillation), and terrestrial climates must still be resolved, our results confirm that the AMO should be considered in assessments of past and future Northern Hemisphere climates.

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.biogeography ͉ climate change ͉ paleoecology ͉ regeneration niche

Fire scar and tree growth chronologies (1700 to 1905) and fire statistics (since 1905) from Arizona and New Mexico show that small areas burn after wet springs associated with the low phase of the Southern Oscillation (SO), whereas large areas burn after dry springs associated with the high phase of the SO. Through its synergistic influence on spring weather and fuel conditions, climatic variability in the tropical Pacific significantly influences vegetation dynamics in the southwestern United States. Synchrony of fire-free and severe fire years across diverse southwestern forests implies that climate forces fire regimes on a subcontinental scale; it also underscores the importance of exogenous factors in ecosystem dynamics.