Aim We developed an ecosystem classification within a 110,000-ha Arizona Pinus ponderosa P. & C. Lawson (ponderosa pine) landscape to support ecological restoration of these forests. Specific objectives included identifying key environmental variables constraining ecosystem distribution and comparing plant species composition, richness and tree growth among ecosystems.
Location The Coconino National Forest and the Northern Arizona University Centennial Forest, in northern Arizona, USA.
Methods We sampled geomorphology, soils and vegetation on 66 0.05-ha plots in open stands containing trees of pre-settlement (c. 1875) origin, and on 26 plots in dense post-settlement stands. Using cluster analysis and ordination of vegetation and environment matrices, we classified plots into ecosystem types internally similar in environmental and vegetational characteristics.
Results We identified 10 ecosystem types, ranging from dry, black cinders/Phacelia ecosystems to moist aspen/Lathyrus ecosystems. Texture, organic carbon and other soil properties reflecting the effects of parent materials structured ecosystem distribution across the landscape, and geomorphology was locally important. Plant species composition was ecosystem-specific, with C3Festuca arizonica Vasey (Arizona fescue), for instance, abundant in mesic basalt/Festuca ecosystems. Mean P. ponderosa diameter increments ranged from 2.3–4.3 mm year−1 across ecosystems in stands of pre-settlement origin, and the ecosystem classification was robust in dense post-settlement stands.
Main conclusions Several lines of evidence suggest that although species composition may have been altered since settlement, the same basic ecosystems occurred on this landscape in pre-settlement forests, providing reference information for ecological restoration. Red cinders/Bahia ecosystems were rare historically and > 30% of their area has been burned by crown fires since 1950, indicating that priority could be given to restoring this ecosystem's remaining mapping units. Ecosystem classifications may be useful as data layers in gap analyses to identify restoration and conservation priorities. Ecosystem turnover occurs at broad extents on this landscape, and restoration must accordingly operate across large areas to encompass ecosystem diversity. By incorporating factors driving ecosystem composition, this ecosystem classification represents a framework for estimating spatial variation in ecological properties, such as species diversity, relevant to ecological restoration.