Vegetation Diversity Assessment in Southern Belgium’s Permanent Forest Inventory 1
(Extended abstract)
C.Sanchez2, H.Claessens2, T.Puissant2, H.Lecomte3 and J.Rondeux2
1
Study carried out on behalf of :
Walloon Forest Inventory Committee, General Directory of Natural Resources
and Environment
and with the financial support of :
The Walloon Region, Nature and Forest Division, 15 Avenue Prince de Liège,
5100 Jambes, Belgium
2
Unit of Forest and Nature Management, Gembloux Agricultural University, Passage
des Déportés 2, 5030 Gembloux, Belgium. E-mail: rondeux.j@fsagx.ac.be
3
Walloon Forest Inventory, General Directory of Natural Resources and Environment,
Avenue Prince de Liège 15, 5100 Jambes, Belgium. E-mail:
h.lecomte@mrw.wallonie.be
_________________________________________________________________________
Key words : multipurpose forest inventory, biodiversity monitoring, vegetation
assessment, floristic database, forest habitat classification.
_________________________________________________________________________
Introduction
At an international scale, the resolutions of ministerial conferences on nature conservation
and forest protection policies suggest that sustainability, with special focus on biodiversity, is
to be considered in forest management.
A permanent forest inventory (IPRFW) was launched in 1994 in the Walloon Region to
provide large-scale forest information for use in forest policy and forest management in
Wallonia. This inventory is based on the sampling and measurement of permanent sample
plots over a 10-year cycle. In 1997, various observations concerning biological diversity were
integrated to characterise forest biodiversity, including deadwood, stand structure, forest
margins, tree health status, soil properties and ground vegetation. These ecological
observations were simply added to the existing data collection methods instead of
conducting a thorough review of the inventory’s methodology and its internal organisation.
The present paper only concerns vegetation investigations and aims at examining the
methodological aspects of vegetation assessment, the current and potential data processing
and results, and at analysing several problems related to the phenological aspects in plant
communities.
Vegetation assessment in the regional forest Inventory
Objectives
The objectives assigned to the inventory in regard to vegetation assessment are to
characterise forest biodiversity and the diversity of vegetation types and to contribute to the
assessment of long-term evolutions in biodiversity in a context of global change and human
activities.
Methodological aspects
The collecting method used is the phytosociology relevé method of Braun-Blanquet (BraunBlanquet, 1965). The relevés are carried out in a 12 m radius plot specially devoted to the
floristic study. The species are recorded in height strata and the cover extent of each layer is
estimated in percent of the plot area. The woody and semi-woody species are divided into
three height groups : plants higher than 10 m, plants between 3 and 10 m and smaller than 3
m. The herbaceous plants are listed in the herb layer.
Once the listing is complete, each plant is affected with a coefficient composed of 2 digits,
the first (Abundance-Dominance) to evaluate the plant’s abundance and the second
(Sociability-Dispersion) to evaluate its dispersion. A visual estimate of the extent of land
cover for each layer is also recorded as percentage of the plot area.
In order to determine the updated state of the Walloon forest, the inventory covers the whole
region on a annual basis. Every year, one tenth of the sample units are visited according to a
distribution per forest range.
The dates of observations in the sample units are determined mainly according to staff
availability and work schedule but also, in order to facilitate tree and stand measurements,
broad-leaved forests are preferentially visited in the winter, as the absence of leaves allows
more accurate height measurements.
All inventory data are recorded on-site on a laptop computer.
Some examples of the potential results
Spatial distribution of forest species
Owing to its systematic sampling-plot distribution throughout the whole territory, the Walloon
forest inventory data can give an objective picture of the spatial distribution of forest species.
Forest habitat classification
The vegetation data collected by the inventory enables the determination of the vegetation
type of the forest stand in which the sample unit is located. The classification used
(Noirfalise, 1984) is based on both phytosociological analysis of relevés and abiotic
characteristics of the site. The results of the classification procedure can be used to identify
the phytosociological association, and in some cases the sub-association.
This information can lead to further results such as the distribution of a particular forest
vegetation type (drawing points on an existing map), or comparison between the frequency
of the main forest habitats in Wallonia or between/within ecological regions (ecoregions).
Vegetation diversity characterisation
The well-known Shannon and Simpson indices combining both species richness and
evenness (Standover, 1996) are used to evaluate vegetation diversity. These diversity
indices are a useful tool for carrying out an objective comparative analysis of forest
vegetation diversity between different land covers in the various ecoregions as well as for all
Wallonia. They can also be used within one ecoregion scale or within one forest habitat, to
compare diversity between sample units. However, these indices are most useful as
indicators within the framework of a monitoring project, especially for assessing the longterm evolution of biodiversity.
Specific topics
Besides the main objectives given to vegetation study (forest biodiversity characterisation
and monitoring), IPRFW’s floristic database gives many other results. Site characteristics are
also collected for comparative scientific studies, especially regarding vegetation types and
plant indicator values.
An example of these specific analyses undertaken for a particular purpose is given by the
assessment of the Natura 2000 network in Wallonia (Claessens et al., 2004). In this analysis,
the sample units of the inventory were separated into two groups: those included in the
network of the Sites of Community Interest (SCI) and those not concerned by the Natura
2000 network. The two groups were then compared in terms of habitats in order to evaluate
the extent to which the SCI designation had successfully taken into account the habitats of
Community Interest and especially the Priority Habitats.
This analysis shows that the inventory data can be used to verify the completion of EU
objectives.
Other characteristics, such as diversity indices or ancient-forest species frequency, which
are considered when defining the Natura 2000 perimeters, should have been taken into
account in order to complete the analysis, but several methodological aspects prevented this
analysis.
Methodological aspects limiting vegetation assessment
Date of observations
Vegetation quantity, aspect and composition changes constantly throughout the year
because of the seasonal cycle in temperate forests. The precise phytosociological diagnosis
of a site can only be completed if an optimum number of species, especially characteristic
species that define vegetation types, are present. However, many of these species are not
visible during winter, especially vernal species.
As the field data of the inventory are collected all year round, the quality of the floristic data
obviously varies from sample to sample according to the date of the flora description. The
consequences of this are the following:
- the number of species present on the sample plot may not reflect the maximum species
diversity, which is assessed by diversity indices;
- the quality of the floristic data is geographically unequal;
- as the monitoring is based on two inventory phases, normally separated by a decade, the
comparison between the floristic data of the two phases becomes irrelevant given that
the date of observations is not necessarily the same between phases. Therefore,
evolution of flora cannot be meaningfully assessed.
In order to quantify the impact of the observation date on species number and diversity
indices, Sanchez (2003) performed a detailed analysis of the differences between the
number of species assessed in winter and in summer for 12 forest habitats.
Vegetation type classification method
Date of observations
Vegetation type is determined at the office using the reference types for Wallonia, i.e. the
Noirfalise (1984) forest communities model. The procedure is therefore qualified as “a
posteriori”. In the study cited above (Sanchez, 2003), determination of vegetation types was
performed at the office separately and consecutively with winter and summer relevés for the
same sample units. The results suggested 19% of differences at the syntaxonomic level of
the phytosociological association between the winter and summer relevés, underlining the
important impact of relevé date on the quality of the vegetation type determination, despite
the use of certain abiotic factors.
Operator effect
Another source of significant errors is the effect of different operators performing the
classification procedure. Sanchez (2003) compared the results of summer relevé
classifications made by two different operators on the data cited above concerning the 12
different habitats. At the phytosociological association level, 14% of the relevés showed
differences between operators.
Site heterogeneity
The inventory’s methodology specifies that if a sample unit overlaps an open habitat or a
different stand, the sample unit is displaced towards the predominant stand. However, a
homogenous stand does not necessarily mean that ground vegetation and abiotic factors are
homogeneous at the sample unit scale.
Proposals for methodological adjustments
Date of observations
It has been proposed that complete relevés performed in spring (from late April to early
June) would be limited to a restricted number of sample units. These relevés would concern
one tenth of the annual sample units that should also be selected for the detailed soil
analysis.
This proposal leads to the following advantages:
- a global ecological monitoring is possible;
- a link with soil analysis opens up possibilities for useful cross-analysis of soil and plant
studies;
- a great deal of time could be saved on the 90% of the remaining plots, for which
complete relevés become less important.
Habitat classification
Two main sources of errors impact negatively on the quality of the habitat classification: the
incomplete relevé, due to the date of the survey, and the operator effect, due to different
interpretations from different operators.
To improve information for forest habitats that are the most subject to seasonal changes,
one solution is to first evaluate the potential vegetation in the office, using cartographic
criteria. Data from the relevés of these particular habitats would be scheduled for a particular
date during spring.
A second solution would be the use of a field determination key, based on objective criteria
for performing habitat classification. The EUNIS habitat determination key developed by
Wibail et al. (2005) is based on both abiotic and floristic criteria, and does not require the
identification of all the species present on the site.
As seen above, because of difficulties in bryophyte identification, the latter are optionally
noted, only if identified by the field operator. However, it appears that taking into account
several bryophyte species can largely improve the habitat classification.
Data control
Errors are always possible at different levels of data collection and analysis: botanical
identification, mismatching during data recording, habitat classification, etc.
A computer program (Ecoflore) developed by the French State Forest Service (Office
National des Forêts) was designed to perform objective ecological diagnosis and calculate
indices that are easily compared between each other and over time, for one particular site
(Bruno and Bartoli, 2002). The principle of the program is based on the indicator value and
the autoecology of each plant species.
The Ecoflore application also provides the possibility of controlling the consistency of a
relevé by detecting any errors.
Discussion and concluding remarks
The sampling method for vegetation assessment at a regional level has proved its
descriptive capacity, but the IPRFW, which has to be performed all year round, is not free
from criticism. During autumn and winter, relevés do not provide a representative description
of vegetation diversity and habitats.
These difficulties result from the “multi-resource” nature of a national or regional forest
inventory. The IPRFW’s original objective concerned the state of timber resources, and
although sustainability and forest biodiversity assessments have been added, only minor
methodological adjustments have been made to compensate.
The proposal suggested in this paper can be considered as a good compromise solution as
it can also guarantee the inventory's role in biodiversity monitoring. At the forest habitats
level, the classification method can also be improved by using of a determination key directly
in the field.
However, if biodiversity assessment also becomes a main objective of the IPRFW, the
internal organisation of the inventory will have to be thoroughly adapted. Vegetation
assessment and monitoring will have to be performed by a specific team that can operate
independently of the constraints of the dendrometric measurements, and which is able to
reorganise its field work depending on phenological variations of the vegetation.
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