R. Brion Salter

Re-examining fire severity relations in pre-management era mixed conifer forests: inferences from landscape patterns of forest structure

For some time, ecologists have known that spatial patterns of forest structure reflected disturbance and recovery history, disturbance severity and underlying influences of environmental gradients. In spite of this awareness, historical forest structure has been little used to expand knowledge of historical fire severity. Here, we used forest structure to predict pre-management era fire severity across three biogeoclimatic zones in eastern Washington State, USA, that contained extensive mixed conifer forests. We randomly selected 10% of the subwatersheds in each zone, delineated patch boundaries, and photo-interpreted the vegetation attributes of every patch in each subwatershed using the oldest available stereo-aerial photography. We statistically reconstructed the vegetation of any patch showing evidence of early selective harvesting, and then classified them as to their most recent fire severity. Classification used published percent canopy mortality definitions and a dichotomized procedure that considered the overstory and understory canopy cover and size class attributes of a patch, and the fire tolerance of its cover type. Mixed severity fires were most prevalent, regardless of forest type. The structure of mixed conifer patches, in particular, was formed by a mix of disturbance severities. In moist mixed conifer, stand replacement effects were more widespread in patches than surface fire effects, while in dry mixed conifer, surface fire effects were more widespread by nearly 2:1. However, evidence for low severity fires as the primary influence, or of abundant old park-like patches, was lacking in both the dry and moist mixed conifer forests. The relatively low abundance of old, park-like or similar forest patches, high abundance of young and intermediate-aged patches, and widespread evidence of partial stand and stand-replacing fire suggested that variable fire severity and non-equilibrium patch dynamics were primarily at work.

DETECTING CHANGE IN FOREST SPATIAL PATTERNS FROM REFERENCE CONDITIONS

Timber harvest, fire suppression, road construction, and domestic livestock grazing have transformed spatial patterns of Interior Northwest forests. As a consequence, parameters of current disturbance regimes differ radically from historical regimes; present-day wildlife habitat distributions differ from historical distributions; and long-term survival of some native terrestrial species is uncertain. Public land managers are under increasing scientific and social pressure to mold existing forest spatial patterns to reflect those resulting from natural disturbance regimes and patterns of biophysical environments. However, knowledge of the characteristics of natural spatial patterns is unavailable. Using a dichotomized ordination procedure, we grouped the 343 forested subwatersheds (mean area, 8000 ha) on the eastern slope of the Cascade Mountains in Washington State into ecological subregions by similarity of area in potential vegetation and climate attributes. We built spatially continuous “historical” (1938–1956) and “current” (1985–1993) vegetation maps for 48 randomly selected subwatersheds from aerial photo interpretations. From remotely sensed attributes, we classified cover types, structural classes, and potential vegetation types and attributed them to individual patches. We then estimated a reference variation (RV) in spatial patterns of patch types (cover type and structural class), by subwatersheds and five forested ecological subregions, using the 48 historical vegetation maps stratified by subregion and a spatial pattern analysis program. Finally, we compared the current pattern of an example subwatershed (MET_11) with the RV estimates of its corresponding subregion to illustrate how reference conditions can be used to evaluate the importance of spatial pattern change. By evaluating pattern changes in light of RV estimates (nominally, the sample median 80% range of a metric) and the full range of class and landscape metrics, we could identify both current and historical conditions of MET_11 that fell outside the RV. This approach gives land managers a tool to compare characteristics of present-day managed landscapes with reference conditions to reveal significant pattern departures, as well as to identify specific pattern characteristics that might be modified through management. It also provides a means to identify “outlier” conditions, relative to subregion RV estimates, that may occasionally be the object of pattern restoration activities.

Restoring fire-prone Inland Pacific landscapes: seven core principles

ContextMore than a century of forest and fire management of Inland Pacific landscapes has transformed their successional and disturbance dynamics. Regional connectivity of many terrestrial and aquatic habitats is fragmented, flows of some ecological and physical processes have been altered in space and time, and the frequency, size and intensity of many disturbances that configure these habitats have been altered. Current efforts to address these impacts yield a small footprint in comparison to wildfires and insect outbreaks. Moreover, many current projects emphasize thinning and fuels reduction within individual forest stands, while overlooking large-scale habitat connectivity and disturbance flow issues.MethodsWe provide a framework for landscape restoration, offering seven principles. We discuss their implication for management, and illustrate their application with examples.ResultsHistorical forests were spatially heterogeneous at multiple scales. Heterogeneity was the result of variability and interactions among native ecological patterns and processes, including successional and disturbance processes regulated by climatic and topographic drivers. Native flora and fauna were adapted to these conditions, which conferred a measure of resilience to variability in climate and recurrent contagious disturbances.ConclusionsTo restore key characteristics of this resilience to current landscapes, planning and management are needed at ecoregion, local landscape, successional patch, and tree neighborhood scales. Restoration that works effectively across ownerships and allocations will require active thinking about landscapes as socio-ecological systems that provide services to people within the finite capacities of ecosystems. We focus attention on landscape-level prescriptions as foundational to restoration planning and execution.

Machine learning and linear regression models to predict catchment‐level base cation weathering rates across the southern Appalachian Mountain region, USA

Accurate estimates of soil mineral weathering are required for regional critical load (CL) modeling to identify ecosystems at risk of the deleterious effects from acidification. Within a correlative modeling framework, we used modeled catchment-level base cation weathering (BCw) as the response variable to identify key environmental correlates and predict a continuous map of BCw within the southern Appalachian Mountain region. More than 50 initial candidate predictor variables were submitted to a variety of conventional and machine learning regression models. Predictors included aspects of the underlying geology, soils, geomorphology, climate, topographic context, and acidic deposition rates. Low BCw rates were predicted in catchments with low precipitation, siliceous lithology, low soil clay, nitrogen and organic matter contents, and relatively high levels of canopy cover in mixed deciduous and coniferous forest types. Machine learning approaches, particularly random forest modeling, significantly improved model prediction of catchment-level BCw rates over traditional linear regression, with higher model accuracy and lower error rates. Our results confirmed findings from other studies, but also identified several influential climatic predictor variables, interactions, and nonlinearities among the predictors. Results reported here will be used to support regional sulfur critical loads modeling to identify areas impacted by industrially derived atmospheric S inputs. These methods are readily adapted to other regions where accurate CL estimates are required over broad spatial extents to inform policy and management decisions.

Steady-state sulfur critical loads and exceedances for protection of aquatic ecosystems in the U.S. southern Appalachian Mountains

Atmospherically deposited sulfur (S) causes stream water acidification throughout the eastern U.S. Southern Appalachian Mountain (SAM) region. Acidification has been linked with reduced fitness and richness of aquatic species and changes to benthic communities. Maintaining acid-base chemistry that supports native biota depends largely on balancing acidic deposition with the natural resupply of base cations. Stream water acid neutralizing capacity (ANC) is maintained by base cations that mostly originate from weathering of surrounding lithologies. When ambient atmospheric S deposition exceeds the critical load (CL) an ecosystem can tolerate, stream water chemistry may become lethal to biota. This work links statistical predictions of ANC and base cation weathering for streams and watersheds of the SAM region with a steady-state model to estimate CLs and exceedances. Results showed that 20.1% of the total length of study region streams displayed ANC <100 μeq∙L(-1), a level at which effects to biota may be anticipated; most were 4th or lower order streams. Nearly one-third of the stream length within the study region exhibited CLs of S deposition <50 meq∙m(-2)∙yr(-1), which is less than the regional average S deposition of 60 meq∙m(-2)∙yr(-1). Owing to their geologic substrates, relatively high elevation, and cool and moist forested conditions, the percentage of stream length in exceedance was highest for mountain wilderness areas and in national parks, and lowest for privately owned valley bottom land. Exceedance results were summarized by 12-digit hydrologic unit code (subwatershed) for use in developing management goals and policy objectives, and for long-term monitoring.

Landscape Evaluation and Restoration Planning

Contemporary land managers are beginning to understand that landscapes of the early 20th century exhibited complex patterns of compositional and structural conditions at several different scales, and that there was interplay between patterns and processes within and across scales. Further, they understand that restoring integrity of these conditions has broad implications for the future sustainability of native species, ecosystem services, and ecological processes. Many too are hungry for methods to restore more natural landscape patterns of habitats and more naturally functioning disturbance regimes; all in the context of a warming climate. Attention is turning to evaluating whole landscapes at local and regional scales, deciphering their changes and trajectories, and formulating scale-appropriate landscape prescriptions that will methodically restore ecological functionality and improve landscape resilience. Here, we review published landscape evaluation and planning applications designed in EMDS. We show the utility of EMDS for designing transparent local landscape evaluations, and we reveal approaches that have been used thus far. We begin by briefly reviewing six projects from a global sample, and then review in greater depth four projects we have developed with our collaborators. We discuss the goals and design of each project, its methods and utilities, what worked well, what could be improved and related research opportunities. It is our hope that this review will provide helpful insights into how spatial decision support technologies may be used to evaluate and plan for local and perhaps larger-scale landscape restoration projects.