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Vreugdenhil et al. (2002) recommended the review of the UNESCO classification system to learn from a quarter century of its application and to expand it to a classification system that could include all ecosystems of the earth, including the aquatic ones. Both the USNVC system and the LCCS have made valuable contributions into that direction; the USNVC system by so clearly distinguishing between different degrees of naturalness, and the LCCS by thoroughly organising the diagnostic criteria into a consistent system of classifiers and by redesigning the system for use with GIS systems. A web-version of the LCCS is viewable at:

http://www.fao.org/docrep/003/x0596e/x0596e00.htm ; and the software and manual are downloadable from: http://www.lccs-info.org/ . This site also provides training and a discussion forum.

In most systems, the full combination of diagnostic elements describing a class is not considered, as it would lead to too great a list of possibilities to handle. The UNESCO and USNVC have dealt with that issue by providing a mechanism to add classes following a certain hierarchy. One should note that in practice, not all classes are needed, as certain combinations of characteristics seldom or never occur. The developers of the LCCS created a standardised, hierarchical a priori – meaning that all classes are pre-defined - classification system for all the land and near-land water-covered areas. The developers identified a collection of “independent diagnostic classifiers” that may characterise any type of land and near-land water system, and organised them in a very consistent and complete hierarchy, allowing for almost any combination of classifiers. In the first three layers of its hierarchy, the system splits into respectively vegetated/non-vegetated, terrestrial/aquatic and non-natural/(semi-)natural. This leads to an very practical primary organisation of the landscape, in which one merely needs to deepen the category of focus, while the non-focus categories may remain visible but generic.

 

Figure 1: The LCCS Hierarchy. The upper classes categorise the system organise the system in: vegetated or not, terrestrial or aquatic and cultivated or natural. From there physiognomic and ecological modifiers allow detailed ecosystem characterisation.

Given the number of classifiers, the total number of classes of the system has become very high, and the system generates its classes using an MS Access-based programme, that generates a Boolean formula, a unique code and a name.

Generating the class with a software programme is very nice; the amount of time in the Central America Ecosystem map spent on mere linguistic nomenclature issues has been considerable. A computer-generated classification avoids nomenclature debates as well as coding, consistency and translation problems; a mere push on a button may even generate a nomenclature in a different language!

Figure 2: LCCS codes. The LCCS names and describes its classes in 4 different ways: listing of modifiers, Boolean formula, Standard Class Name and a code.

 

The developers (di Gregorio & Jansen 2000) object that most existing systems (both for vegetation cover and specific features like agriculture) are unable to define the whole range of possible land cover classes. This does not necessarily pose insurmountable drawbacks, as different complementary thematic classification systems may be applied to the same study area. Even the LCCS lives by that philosophy, as it states that for bare soil, the soil type can be added according to the FAO/UNESCO Revised Soil Legend. On the other hand, merging several land classes into one system may be convenient; care must be taken, however, to not lose the primary focus of a mapping project. By incorporating too many classifiers, the complexity of the data may clutter the information, while printed versions may become illegible. A national thematic ecosystem map needs to distinguish at least some thirty main classes; if it includes different levels of intervention of those classes, the number may more than double. Adding detailed agricultural information to such a map would unduly raise the complexity for the user. Additionally, it is difficult enough to obtain adequate funding for the field of focus of the map, and – depending on the country – it may not be wise to spend limited resources on non-target themes. Thirdly, maps almost always require some level of abstraction, and adding agricultural information on an ecosystems map risks applying a wrong category to some kind of field specifically known to a user. Such insignificant error in the context of the main theme may be of great significance to that user, and an overall disqualification of the map may result from non-focus classification errors.

An observation about the nomenclature in the UNESCO system, is pertinent, particularly related to elevation classes. Terms like “alpine, cloud forest, paramo”, etc. are not proper names of the modifiers they were intended to represent; at times, this can give rise to heated debates. When applying the system, it may be advisable to substitute such terms by more neutral terms reflecting the modifiers. This problem does not arise in the LCCS as it systematically defines each modifier, regardless of the location of its application.

While the LCCS pretends to systematically classify distinct ecological conditions - and it certainly does so more systematically than any other existing system – it still is likely to bunch criteria. The only systematic way of independently classifying each classifier is by creating an independent GIS layer for each characteristic or modifier, and then independently nominate each compound polygon resulting from mutual overlaying. Composing classes in such a way, however, risks the composition of large numbers of very small slightly different polygons that – for protected areas system analysis – may not be considered as significantly distinct ecosystems. Most biologists don’t map that way. They produce one map layer to identify polygons with certain homogeny and then classify it, thus implicitly bunching a number of classifiers in each polygon. The LCCS can be used to do that, but it requires some skilled decision-making. Thus applied, the LCCS would still conserve some of its subjective intuitiveness while classifying more systematically than possible with the previously mentioned systems. These issues need to be tested on a detailed case, which has already been mapped with the UNESCO or USNVC method as for Central America.

Ultimately, there is a concern regarding all three systems. Not all classifiers always lead to distinction, or they do so differently under different conditions. For instance, the effects of elevation differentiation in species composition are more pronounced under very moist evergreen forest conditions. Deciduous forests have only one ecosystem zone for the first two levels of humid tropical forest. On the very dry Western slopes of the Andes in Peru, one can see how the vegetation cover from being (almost) absent at sea level very gradually becomes denser and higher with increasing elevation, probably accompanied with a similarly slow increase of species. Using the same detail of elevation levels under these arid conditions as for humid tropical forests would create an ecosystem differentiation that in reality does not exist. Another case that needs attention in this context is that the changing climatic conditions with elevation on mountains isolated in the landscape, tend to occur more rapidly than on large mountain ranges. This effect was described by van Steenis (1961 and 1972) for Java, who called it “telescope effect” and by Grubb (1971), who referred to it as Massenenhebung. Ecosystem similarity would need to be identified where both mountain ranges and isolated mountains exist in the same region to be mapped.

The LCCS has made a commendable attempt to include aquatic ecosystems, but in this field, the system needs further work by creating a sliding scale from well-drained terrestrial ecosystems to permanent water systems. Furthermore, under-water aquatic classes, ranging to full oceanic classes, coral reef classes and tidal zone classes need further thought and development. For conservation purposes this is of crucial importance: Conservation programmes must at all cost start integrating the conservation of terrestrial and aquatic areas. One condition for achieving that is by integrating terrestrial and aquatic ecosystems in integrated maps with adequate levels of detail. For aquatic ecosystems, this requires greater detail than currently available in the LCCS.

At the bottom of the hierarchy, the system allows further division on the basis of floristic classifiers. At this level, the LCCS is likely to become rather subjective, just like the other systems. Whenever people try to organise nature in a human system, they make subjective choices. End-users will always have to deal with that.

With the appearance of the LCCS, the recommendation of Vreugdenhil et al. (2002) to review the UNESCO system has become obsolete; it has solved many of their concerns, but it needs true field testing for detailed mapping and improvement of the aquatic ecosystems. With such a much broader range of options, there is a great need for instructions from an ecologist’s point of view on what to map and classify - or what not - for a map of natural ecosystems, otherwise, many less-experienced users may get lost in the collection of less useful information for ecological studies. One suspects that similar thematic instructions would be welcome for other disciplines as well.

This page  is part of our web-book on Biodiversity Conservation. For organized reading go to our on-line Table of Content, or download our book in pdf format.

 

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