Historical Range of Variability in Landscape Structure: A Simulation Study in Oregon, Usa

Abstract

We estimated the historical range of variability (HRV) of forest landscape structure under natural disturbance regimes at the scale of a physiographic province (Oregon Coast Range, 2 million ha) and evaluated the similarity to HRV of current and future landscapes under alternative management scenarios. We used a stochastic fire simulation model to simulate presettlement landscapes and quantified the HRV of landscape structure using multivariate analysis of landscape metrics. We examined two alternative policy scenarios simulated by two spatially explicit simulation models: (1) current management policies for 100 years into the future and (2) the wildfire scenario with no active management until it reached the HRV.The simulation results indicated that historical landscapes of the province were dynamic, composed of patches of various sizes and age classes ranging from 0 to Ͼ800 years including numerous, small, unburned forest islands. The current landscape was outside the HRV. The landscape did not return to the HRV in the 100 years under either scenario, largely because of lack of old-growth forests and the abundance of young forests. Under the current policy scenario, development of landscape structure was limited by the spatial arrangement of different ownerships and the highly contrasting management regimes among ownerships. As a result, the vegetation pattern after 100 years reflected the ownership pattern. Surprisingly, the wildfire scenario initially moved the landscape away from the HRV during the first 100 years, after which it moved toward the HRV, but it required many more centuries to reach it. Extensive forest management and human-caused fires in the 20th century have left legacies on the landscape that could take centuries to be obliterated by wildfire.Departure from the HRV can serve as an indicator of landscape conditions, but results depend on scale and quantification of landscape heterogeneity. The direct application of the concept of HRV to forest policy and management in large landscapes is often limited since not all ownerships may have ecological goals and future climate change is anticipated. Natural disturbance-based management at large scales would not show the projected effects on landscape structure within a typical policy time frame in highly managed landscapes.

Ecological History vs. Social Expectations: Managing Aquatic Ecosystems

“…Multiple studies have identified and used HRV in forest structures and processes to help guide management and conservation of biodiversity. These studies have been done for many regions of the western United States, including the southwest (Moore et al 1999, Swetnam et al 1999, the Oregon Cascades (Cissel et al 1999), the Sierra Nevada (Millar and Woolfenden 1999), the sequoia forest area of California (Stephenson 1999), and the Oregon Coast Range (Wimberly et al 2000, Nonaka andSpies 2005). Landres et al (1999) provide an overview of the natural variability concepts underlying biodiversity management.…”

The Effects of Spatial Legacies following Shifting Management Practices and Fire on Boreal Forest Age Structure

“…Wallin and others (1994) demonstrated that shifts from a dispersed to an aggregated harvest pattern did not immediately result in a change in forest attributes such as patch size and edge density. Similarly, Nonaka and Spies (2005) found that more than 100 years was required for the system to regain its historical condition in the absence of human management. Ecologically, the interactions between spatial legacies and new management practices can push forest landscape patterns out of their historical range of variability (Paine and others 1998;Schrö der and others 2005), alter successional pathways, and change regional patterns of forest composition (Hessburg and others 1999;Friedman and Reich 2005).…”

Evaluating indices that measure departure of current landscape composition from historical conditions

“…Instead, it appears that reducing historical time series could be a viable option for land managers who cannot store or manage large historical data sets. This is especially important as more land managers obtain their HRV time series from simulation modeling (Keane and others 2002;Nonaka and Spies 2005;Wimberly and others 2000) because models can produce extensive outputs of simulated historical conditions. However, these synthesis options could result in less variability in the historical record that may make it difficult to detect subtle changes in the reference landscape.…”