Considerable attention was received by the proposed “harmonization” process between forest condition monitoring (FCM) and “traditional” national forest inventories (NFIs) networks. While some harmonization has been achieved and documented within the FCM at European level, it is not so for NFIs. Since the two systems may show remarkable differences also at country level, the extent to which a fully harmonized European-scale FCM-NFI system can be achieved is rather uncertain, if ever possible. In contrast, different harmonization perspectives may be considered at national level: (i) harmonization of assessment/measurement methods, (ii) functional integration of network while keeping them separate, and (iii) full integration of networks. Unfortunately while the cost-benefit balance of this harmonization processes was not clarified, actions were already undertaken that may lead to the disruption of the FCM data series initiated in the 1980s. The conclusion of the process may be ironical: will the current effort in “harmonizing” NFIs and FCM results into the disruption of the European-wide longest and most harmonized time series of forest condition data?
Considerable attention was received by the proposed “harmonization” between large-scale monitoring of forest condition and traditional national forest inventories currently being developed by the Life+ project FutMon (http://www.futmon.org/). The issue was discussed at an international meeting held in Firenze, Italy, on March 20, 2009 (http://www.aisf.it/futmon/20.htm). The reason is clear: while the subject is of general importance (e.g.,
The large-scale monitoring of forest condition (hereafter referred to as FCM) started in Europe in the 1980s under the auspices of UN/ECE Convention on Long Range Transboundary Air Pollution (with its ICP Forests) and of the European Union Regulation 3528/86 (
sampling design in terms of sampling scheme, density and plot design (e.g., fixed area
revisions of the FCM network to account for changes in forest coverage are not harmonized across Europe;
tree condition assessment criteria (reference standard, assessable crown, defoliation
Although the above limitations may be so important to hamper the value of the data (
Unlike FCM, National Forest Inventories (NFIs) were traditionally designed to provide country-based estimates of different forest areas and timber, non-timber attributes. As such and because of historical, commercial, and environmental justification (
In general terms, NFI and FCM have similar features: they are typical sample surveys and their objective - loosely speaking - is to obtain reliable estimates of population parameter for the attribute(s) of concern, and to estimate time changes. Thus, harmonized FCM and NFI networks, or may be a single network of field plots supporting both NFI and FCM information needs, would offer considerable logical, logistical, technical, financial and information advantages, raising the value of FCM in Europe. As resulted from opinion collected in the reported meeting, these advantages were advocated to promote the harmonization process between FCM and NFI. Unfortunately, no formal cost-benefit analysis was presented to support the intuitive advantages reported above. For this reason, and at this very stage, it is important to carefully consider the meaning, process and costs of this “harmonization”: wrong decisions may result into the fall, rather than the raise, of harmonized FCM in Europe.
According to the on-line Webster’s, “harmonization” is the process of establishment, recognition, and application of internationally recognized measures or standards. In my understanding, and in the present context, “harmonization” needs to consider three main subjects (attributes and assessment methods, plots and tree selection, network structure) and - according to the chosen subject - may have three practical meanings.
Harmonization of FCM and NFI attributes and relevant assessment/measurement methods. This implies adopting typical FCM attributes and assessment/measurement methods within the set of the NFI ones (and/or the other way round). This not necessitates any change in network and plot design: networks may stay separated, plots may keep their own characteristics, but the adoption of consistent methods will led to harmonized datasets in terms of attributes. This is the slightest possible “harmonization” action to be undertaken;
Functional integration of FCM and NFI networks. Under this harmonization perspective, networks remain separated, but they will use not only the same attributes and methods (see above), but also the same plot design, which implies consistency in tree selection criteria. In this perspective, FCM plots may adopt the design used in the NFIs, while keeping the assessment also on trees that were previously considered. Assessment will be done on both FCM and NFI networks, although not necessarily with the same time frequency (see below). This implies some work to be done to adapt the plots, but - under the assumption of a common target population - results can be used jointly to derive more precise and robust estimates.
Full integration of FCM and NFI networks (all-in-one). Under this perspective, original FCM plots will be ceased and FCM attributes will be measured only on NFI plots. The other way round (closing NFI plots in favour of FCM) is also possible, although less likely. A single, fully integrated and harmonized set of data will be obtained. However, if FCM plots are closed and moved to NFI ones, the FCM data series will be lost, at country level, and - as a consequence - at European level.
Another perspective is the harmonization of the estimation process. It is worth noting that none of the above harmonization perspectives will solve the problem that NFIs network and plot designs differ across Europe, so it will be for FCM. Thus, harmonization will be possible only at the estimation stage (e.g.,
The process by which “harmonization” can be achieved rests on the existing relationship between NFIs and FCM networks at national level. Some cases can be identified.
This may have occurred because FCM was established on existing NFI networks (most frequent) (e.g., Austria, Switzerland) or the otherway round (e.g., Romania). In general, a subsample of NFI plots was used for FCM. In these cases networks are fully integrated, no assumption about nature of target populations is needed, and harmonization exists in facts at national level. Some further “harmonization” may be necessary due possible adaptation of survey methods in agreement to international procedure, but such a process can be traced and documented. The existing differences of NFIs and FCM across Europe will remain. Case 1 will be not discussed further here.
This may have happened because:
there was no NFI in the past, and FCM was created before NFI;
the NFI and FCM were developed independently, as the agencies managing FCM and NFI were different and not communicating;
countries with a former joint NFI-FCM network (Case 1) abandoned (for a variety of reasons) their original NFI for a newly designed one, thus having now two separate networks. For example Italy, where FCM was installed on a subsample of the 1st NFI (see
In every case the result is that today NFI and FCM are carried out on different networks. In these cases, harmonization can have each of the three meanings reported above.
Harmonization of methods implies that FCM and NFI will adopt similar protocols for assessment/measurements. This also mean common training, and Quality Assurance/Quality Control (e.g.,
A further step in the harmonization process would be to keep the two networks (FCM and NFI), with the following adjustments:
add FCM attributes and assessment methods to a comparable number of NFI plots (to be selected according to the country NFI design), and carry out the FCM measurements on (a sample of) trees at the selected NFI plots. Avoid permanent numbering on trees and annual visits on NFI plots in order to keep the plot as anonymous and undisturbed as possible. Rather, carry out FCM assessment on these plots at each NFI cycle (e.g., every 5 years);
adopt the NFI plot design and attributes also for the existing FCM plots. At the same time keep also the former sample trees at the FCM plots. Do annual FCM on the “old” and the newly selected sample trees.
This will results in several advantages: the existing time series is maintained; comparison between the two dataset will be possible at defined time intervals; combined (and more precise) estimates may be possible at defined intervals. This latter possibility rests however on the very nature of the FCM network (its origin and target statistical population), and under the assumption that FCM and NFI samples concern the same statistical population. NFI plots will stay undisturbed. Disadvantage is a slight increase of costs (FCM plots adaptation at first year; some new attributes on NFIs at each inventory cycle). Differences of NFIs and FCM across Europe will remain.
Regardless what network will be abandoned, this process implies cutting a data series (or keep it on a very limited number of plots). The longer and the more consistent the data series, the higher the cost in terms of vanished investments and lost of data series. Two cases may occur: FCM is moved to NFI or the other way round.
FCM moved to NFI. Under this scenario, FCM attributes will be measured on NFI plots only. The advantage is often identified in “more representative” sample and the possibility for sound statistical estimates. However, at the above referred workshop, in most cases “representative” was intended to mean that the tree species composition of the NFI sample is more “updated” than the FCM one, and not to mean the statistical properties of the sample (e.g., elements of randomness in the selection, known and positive selection probability, independency). It is certainly true that FCM networks are getting biased: they were installed in 1980s and seldom updated; in addition, the “fixed-number-of-trees” plot concept implies the assessed trees remain the same across time, nearly ignoring ingrowth and suffering from a progressive ageing; further, tree selection a probabilistic sample (e.g., angle count). However, these drawbacks can be solved by simple actions: (i) shifting from the “fixed-number-of- trees” plot concept to the “fixed-area” plot, and by (ii) updating the coverage of the plots in order to account for changes in forest area. By the way action (i) was already largely done in the frame of the BioSoil project on the FCM plots (
NFI moved to FCM. This is unlikely as in general NFI requirements cannot be attained by FCM networks, which are based (in general) on more relaxed sampling density and have - in general - trees with permanent numbering. However, it may occur when financial constrains require to have one single network and/or the FCM has the longest time series (
A concrete example of shift from FCM to NFI was in Bavaria (Germany), were the shift was suggested to optimize existing networks: the FCM (installed in 1983, 4 x 4 km grid); the NFI (installed in 1987, on a different 4 x 4 km grid, shifted by 200 m east and 200 north. The NFI was repeated in 2002); the first soil inventory (installed in 1986-1989 on a subsample of the FCM network, with plot centres not permanently marked). When a new soil inventory was launched (to be installed in Bavaria by 2006), problems in identifying former plot centres lead to the decision to move the grids (FCM and soil) onto a subsample (8 x 8 km) of the NFI. The advantage is that all the three data series (soil, FCM, NFI) may be evaluated together; the disadvantage is that the 1983-2006 data series is going to be ceased (Bauer A, pers. comm.).
It was not the intention of this paper to “defend” the FCM against NFI: in the past I was critical enough to the FCM (see
Quoting
I am grateful to Dr. Patrizia Gasparini and Dr. Lucio Di Cosmo (CRA-MPF, Trento, Italy) for the open discussion, and to Dr. Markus Neumann (BFW, Wien, Austria) for a number of stimulating comments on the manuscript. I am in debt also with Prof. Lorenzo Fattorini (University of Siena, Italy) for additional discussion on the topic. Dr. Arthur Bauer (LWF, Freising, Germany) provided a detailed explanation about the FCM and NFI processes in Bavaria (Germany).