Ecological memory is central to how ecosystems respond to disturbance and is maintained by two types of legacies – information and material. Species life‐history traits represent an adaptive response to disturbance and are an information legacy; in contrast, the abiotic and biotic structures (such as seeds or nutrients) produced by single disturbance events are material legacies. Disturbance characteristics that support or maintain these legacies enhance ecological resilience and maintain a “safe operating space” for ecosystem recovery. However, legacies can be lost or diminished as disturbance regimes and environmental conditions change, generating a “resilience debt” that manifests only after the system is disturbed. Strong effects of ecological memory on post‐disturbance dynamics imply that contingencies (effects that cannot be predicted with certainty) of individual disturbances, interactions among disturbances, and climate variability combine to affect ecosystem resilience. We illustrate these concepts and introduce a novel ecosystem resilience framework with examples of forest disturbances, primarily from North America. Identifying legacies that support resilience in a particular ecosystem can help scientists and resource managers anticipate when disturbances may trigger abrupt shifts in forest ecosystems, and when forests are likely to be resilient.

THE CONCEPT of a natural unemployment rate has been central to most modern models of inflation and stabilization. According to these models, inflation will accelerate or decelerate depending on whether unemployment is below or above the natural rate, while any existing rate of inflation will continue if unemployment is at the natural rate. The natural rate is thus the minimum, and only, sustainable rate of unemployment, but the inflation rate is left as a choice variable for policymakers. Since complete price stability has attractive features, many economists and policymakers who accept the natural rate hypothesis believe that central banks should target zero inflation. We question the standard version of the natural rate model and each of these implications. Central to our analysis is the effect of downward nominal wage rigidity in an economy in which individual firms experience stochastic shocks in the demand for their output. We embed these features in a model that otherwise resembles a standard natural rate model and show there is no unique natural unemployment rate. Rather, the rate of unemployment that is consistent with steady inflation We would especially like to thank Neil Siegel, Justin Smith, and Jennifer Eichberger for invaluable research assistance. We are also grateful to Pierre Fortin, Harry Holzer, and Christina Romer for providing us with data, and to

[1] Estimates of wildfire aerosol and trace gas emissions are most commonly derived from assessments of biomass combusted. The radiative component of the energy liberated by burning fuel can be measured by remote sensing, and spaceborne fire radiative energy (FRE) measures can potentially provide detailed information on the amount and rate of biomass consumption over large areas. To implement the approach, spaceborne sensors must be able to derive fire radiative power (FRP) estimates from subpixel fires using observations in just one or two spectral channels, and calibration relationships between radiated energy and fuel consumption must be developed and validated. This paper presents results from a sensitivity analysis and from experimental fires conducted to investigate these issues. Within their methodological limits, the experimental work shows that FRP assessments made via independent hyperspectral and MIR radiance approaches in fact show good agreement, and fires are calculated to radiate 14 ± 3% [mean ± 1S.D.] of their theoretically available heat yield in a form capable of direct assessment by a nadir-viewing MIR imager. The relationship between FRE and fuel mass combusted is linear and highly significant (r 2 = 0.98, n = 29, p < 0.0001), and FRP is well related to combustion rate (r 2 = 0.90, n = 178, p < 0.0001), though radiation from the still-hot fuel bed can sometimes contribute significant FRP from areas where combustion has ceased. We conclude that FRE assessment offers a powerful tool for supplementing existing burned-area based fuel consumption measures, and thus shows significant promise for enhancing pyrogenic trace gas and aerosol emissions estimates.Citation: Wooster, M. J., G. Roberts, G. L. W. Perry, and Y. J. Kaufman (2005), Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release,

We describe a range of methods for the description and analysis of spatial point patterns in plant ecology. The conceptual basis of the methods is presented, and specific tests are compared, with the goal of providing guidelines concerning their appropriate selection and use. Simulated and real data sets are used to explore the ability of these methods to identify different components of spatial pattern (e.g. departure from randomness, regularity vs. aggregation, scale and strength of pattern). First-order tests suffer from their inability to characterise pattern at distances beyond those at which local interactions (i.e. nearest neighbours) occur. Nevertheless, the tests explored (first-order nearest neighbour, Diggle's G and F) are useful first steps in analysing spatial point patterns, and all seem capable of accurately describing patterns at these (shorter) distances. Among second-order tests, a density-corrected form of the neighbourhood density function (NDF), a noncumulative analogue of the commonly used Ripley's K-function, most informatively characterised spatial patterns at a range of distances for both univariate and bivariate analyses. Although Ripley's K is more commonly used, it can give very different results to the NDF because of its cumulative nature. A modified form of the K-function suitable for inhomogeneous point patterns is discussed. We also explore the use of local and spatially-explicit methods for point pattern analysis. Local methods are powerful in that they allow variations from global averages to be detected and potentially provide a link to recent spatial ecological theory by taking the 'plant's-eye view'. We conclude by discussing the problems of linking spatial pattern with ecological process using three case studies, and consider some ways that this issue might be addressed.