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.

Aim  The assumption of equilibrium between organisms and their environment is a standard working postulate in species distribution models (SDMs). However, this assumption is typically violated in models of biological invasions where range expansions are highly constrained by dispersal and colonization processes. Here, we examined how stage of invasion affects the extent to which occurrence data represent the ecological niche of organisms and, in turn, influences spatial prediction of species’ potential distributions. Location  Six ecoregions in western Oregon, USA. Methods  We compiled occurrence data from 697 field plots collected over a 9‐year period (2001–09) of monitoring the spread of invasive forest pathogen Phytophthora ramorum. Using these data, we applied ecological‐niche factor analysis to calibrate models of potential distribution across different years of colonization. We accounted for natural variation and uncertainties in model evaluation by further investigating three hypothetical scenarios of varying equilibrium in a simulated virtual species, for which the ‘true’ potential distribution was known. Results  We confirm our hypothesis that SDMs calibrated in early stages of invasion are less accurate than models calibrated under scenarios closer to equilibrium. SDMs that are developed in early stages of invasion tend to underpredict the potential range compared to models that are built in later stages of invasion. Main conclusions  A full environmental niche of invasive species cannot be effectively captured with data from a realized distribution that is restricted by processes preventing full occupancy of suitable habitats. If SDMs are to be used effectively in conservation and management, stage of invasion needs to be considered to avoid underestimation of habitats at risk of invasion.

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A central challenge to studying emerging infectious diseases (EIDs) is a landscape dilemma: Our best empirical understanding of disease dynamics occurs at local scales, whereas pathogen invasions and management occur over broad spatial extents. The burgeoning field of landscape epidemiology integrates concepts and approaches from disease ecology with the macroscale lens of landscape ecology, enabling examination of disease across spatiotemporal scales in complex environmental settings. We review the state of the field and describe analytical frontiers that show promise for advancement, focusing on natural and human-altered ecosystems. Concepts fundamental to practicing landscape epidemiology are discussed, including spatial scale, static versus dynamic modeling, spatially implicit versus explicit approaches, selection of ecologically meaningful variables, and inference versus prediction. We highlight studies that have advanced the field by incorporating multiscale analyses, landscape connectivity, and dynamic modeling. Future research directions include understanding disease as a component of interacting ecological disturbances, scaling up the ecological impacts of disease, and examining disease dynamics as a coupled human-natural system.

Summary1. Few pathogens are the sole or primary cause of species extinctions, but forest disease has caused spectacular declines in North American overstorey trees and restructured forest ecosystems at large spatial scales over the past 100 years. These events threaten biodiversity associated with impacted host trees and other resources valued by human societies even when they do not directly cause host extinction. 2. Invasion of Phytophthora ramorum and emergence of the forest disease sudden oak death has caused a large-scale decline of tanoak (Notholithocarpus densiflorus) in Californian coastal forests. Here, we describe structural changes to tanoak forests and develop predictive models of infection rates, mortality rates and changes in tanoak biomass and abundance by combining regionally extensive longitudinal field studies and mathematical modelling. 3. Pathogen-invaded stands had smaller average tanoak tree size and higher proportions of large dead tanoak trees compared with uninvaded stands. This pattern is caused in part by a positive relationship between tanoak size and mortality rate, as well as prolific basal sprouting from trees killed by the disease. Tanoak infection, mortality and biomass decline rates were positively related to the prevalence of infection in sporulation-supporting species, especially California bay laurel (Umbellularia californica). 4. We developed a stage-structured and spatially explicit mathematical model including species dynamics and P. ramorum transmission, where the long-term outcome of disease ranges from host extinction when densities of bay laurel are high to limited or no disease outbreak. Low densities of tanoak in a matrix of non-susceptible neighbouring species resulted in slow-enough transmission to retain overstorey tanoak, suggesting host-density thresholds may exist in real forests. 5. Synthesis. Tanoak is likely to persist in many disease-impacted forests via vegetative reproduction, but overstorey trees may be eliminated or greatly reduced in abundance, a pattern similar to other forest diseases that have emerged in the last century including chestnut blight and beech bark disease. Our results support a general model of disease-caused changes to forest trees useful for the analysis of emerging forest pathogens where vegetative reproduction, community-level epidemiology and stage-specific mortality rate interact to determine local disease intensity and host decline.