Reference : Prospects for harmonized biodiversity assessments using national forest inventory data
Parts of books : Contribution to collective works
Life sciences : Agriculture & agronomy
Life sciences : Environmental sciences & ecology
Life sciences : Phytobiology (plant sciences, forestry, mycology...)
http://hdl.handle.net/2268/98261
Prospects for harmonized biodiversity assessments using national forest inventory data
English
McRoberts, Ronald E. [ > > ]
Chirici, Gherardo [ > > ]
Winter, Susanne [ > > ]
Barbati, A. [ > > ]
Corona, P. [ > > ]
Marchetti, Marco [ > > ]
Hauk, E. [ > > ]
Brändli, Urs-Beat [ > > ]
Beranova, J. [ > > ]
Rondeux, Jacques mailto [Université de Liège - ULg > Forêts, Nature et Paysage > Gestion des ressources forestières et des milieux naturels >]
Sanchez, C. [ > > ]
Bertini, R. [ > > ]
Barsoum, N. [ > > ]
Alberdi Asensio, I. [ > > ]
Condes, S. [ > > ]
Saura, S. [ > > ]
Neagu, S. [ > > ]
Cluzeau, C. [ > > ]
Hamza, N. [ > > ]
2011
National Forest Inventories - contributions to Forest Biodiversity Assessments
Chirici, Gherardo
Winter, Susanne
McRoberts, Ronald E.
Springer
Managing Forest Ecosystems, volume 20
41-97
978-94-007-0481-7
[en] Harmonized biodiversity assessments ; National forest inventory data
[en] After selection of the 13 biodiversity variables (Sect. 2.3) based on their importance and feasibility for assessment by NFIs, responses were solicited from participating countries regarding the degree to which the variables are now assessed. Two conclusions were evident: (1) most countries currently assess most of the variables, but (2) consensus is lacking on assessment methods and necessary field crew expertise, suggesting that harmonization would require emphasis on field operations. For each of the seven essential features into which the 13 variables were grouped, more detailed assessments were conducted. For forest categories, the conclusion was that the only major difference in classification systems used by European NFIs was whether potential or actual vegetation was used to define classes. Thus, the prospects for harmonization of forest categories are considered excellent. For forest structure, the prospects depend on the variable. For tree species, the prospects are excellent because the variable is assessed in the same manner by all NFIs. For dbh and height, considerable variability in measurementthresholds were found, but otherwise the harmonization prospects are good. For social position, definitions of classes varied, but harmonized estimates of proportions for dominant, intermediate, and suppressed classes are considered possible. Prospects for harmonized estimates of layers are consideraly poorer because of different definitions, thresholds and the uncertainty associated with visual assessment methods. Harmonized estimation of forest age is impeded by the increasing proportion of uneven-aged stands for which age is often not assessed, different definitions, and different assessment methods. However, agreement on dominant age as a reference definition would greatly increase the prospects. Deadwood is becoming an increasingly popular indicator of sustainable forest management. Unfortunately, considerable variability was found in deadwood definitions, components (e.g., stumps, limbs), sampling methods, and measurement thresholds. Thus, harmonized deadwood estimation will require development of bridges. Harmonization of regeneration estimates faces challenges due to differences in assessment approaches such as presence/absence versus coverage and all species versus dominant species. Harmonized estimation may be restricte to change in regeneration success. Harmonized estimation for ground vegetation also faces serious challenges due to differences in the components assessed (e.g., small trees, shrubs, herbs, bryophytes, lichens), difference in height thresholds, and differences in categories for which ground vegetation is reported. Forest naturalness integrates many of the other essential feature. However, many countries do not assess naturalness, and among those that do, assessment variables, methods, and reporting classes vary considerably. For harmonized assessment using NFI variables, the hemeroby approach, which emphasizes indications of human influence, is extremely sensitive to plot size. Harmonization using the ecosystem processes approach requires a common dbh threshold and similar plot sizes. The overall conclusion is that harmonization will be considerably easier for some essential features than for others. The factors leading to difficulties often are related to different definitions, different reporting classes, different measurement thresholds, and different features of sampling protocols such as plot sizes and configurations. Nevertheless, construction of reference definitions and bridges greatly facilitate harmonization for all essential features as is illustrated in Chap. 5.
COST
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/98261

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