DOI: 10.1016/j.foreco.2016.10.032
Scopus记录号: 2-s2.0-84992756929
论文题名: Two scales are better than one: Monitoring multiple-use northern temperate forests
作者: White M.A. ; Cornett M.W. ; Wolter P.T.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2017
卷: 384 起始页码: 44
结束页码: 53
语种: 英语
英文关键词: Adaptive capacity
; Adaptive management
; Complexity
; Evidence base
; Remote sensing
; Species diversity
Scopus关键词: Biodiversity
; Decision making
; Ecology
; Ecosystems
; Forestry
; Reforestation
; Remote sensing
; Adaptive capacity
; Adaptive Management
; Complexity
; Evidence base
; Global environmental change
; Multi-temporal remote sensing
; Northern temperate forests
; Structural characteristics
; Information management
; adaptive management
; archaeological evidence
; chronosequence
; complexity
; coniferous tree
; conservation management
; decision making
; ecosystem function
; environmental change
; environmental monitoring
; evergreen tree
; forest management
; remote sensing
; species diversity
; temperate forest
; vegetation structure
; Great Lakes [North America]
; Minnesota
; United States
; Betula alleghaniensis
; Picea glauca
; Pinus strobus
; Thuja occidentalis
英文摘要: Managing forests for multiple, often conflicting values, coupled with the uncertainty of global environmental change, requires a more flexible approach to maintaining functioning ecosystems into the future. Adaptive management offers such flexibility, but is often hampered by a lack of targeted monitoring data collected in a consistent manner—the evidence base. Moreover, effective management of expansive forest ecosystems requires data on both landscape scale processes, as well as finer-scale data on vegetation structure and composition. To address the challenges of adaptive management in forest ecosystems, we tested the ability of a small set of multi-scale indicators to inform management of Minnesota's Northern Great Lakes forest. Using remotely sensed and field data, we monitored changes in forest condition over a 20-year period in the 42,000 ha Manitou forest landscape in northeastern Minnesota. We used multi-temporal remote sensing data to assess landscape-scale changes in disturbance rates, patch size and age structure. With field data, we used a chronosequence method to assess management effects over time on finer scale characteristics such as canopy composition, tree regeneration, vertical structure and coarse woody debris. Combining remotely sensed and field data provided a more robust evidence base for decision-making than either approach could have provided alone. For example, examining remote-sensing data alone indicates that the rate of severe disturbance (timber harvest) peaked during the 20-year analysis period, and has declined in recent years. As disturbance rates declined, patch size and the proportion of forest in later successional stages all increased from year 2000 levels. These indicators of landscape structure showed positive shifts towards conservation objectives, but only tell part of the whole story. Field data elucidate a number of negative trends, including poor regeneration of key species (Picea glauca, Pinus strobus, Thuja occidentalis, Betula alleghaniensis), and simplified structure in young and mature growth stages. In addition, much of the mature forest transitioning into later-successional growth stages lacks the long-lived species and structural characteristics needed to develop late-successional conditions. An evidence base compiled from data gathered at both the stand and landscape scale provides the flexibility on which sound adaptive management depends. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64589
Appears in Collections: 影响、适应和脆弱性
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作者单位: The Nature Conservancy, Minnesota, North and South Dakota, 394 Lake Avenue South, Duluth, MN, United States; Iowa State University, Natural Resource Ecology and Management, Ames, IA, United States
Recommended Citation:
White M.A.,Cornett M.W.,Wolter P.T.. Two scales are better than one: Monitoring multiple-use northern temperate forests[J]. Forest Ecology and Management,2017-01-01,384