Biogeography is the science that studies the relationships among the distributions of organisms at present and in the past (Westhoff et al. 1970). On the basis of the recognition that certain plant families only occur in certain parts of the world, the world has been split up into five floral kingdoms , each with a set of characteristic plant families. With increasingly fine mechanisms of distinction, biogeographers have further subdivided those areas, using genera for the next level down, the regions and species for the provinces and lower subdivisions in the hierarchy. By bundling apparent coincidence of distributions among certain taxonomic groups, biogeography provides special information for identifying partially different assemblages of species with a tendency to share distribution ranges, without having to know them all. Hence, biogeographical units may be used as identifiers of distribution by proxy (Vreugdenhil 2002) or surrogates (Faith et al. 2001). With each further subdivision in the system, the number of distinguishing species decreases while the number of overlapping species increases, thus decreasing the degree of overall distinction.

Udvardy (1975) divided the world into eight realms, which were each subdivided into different biomes. Van der Hammen and Cleef (1986) and Van der Hammen and Hooghiemstra (1996, 2001) very convincingly present, respectively review, the latest insights on the origin of the phytogeographical distribution of vascular plant genera in the neotropical Andean forests on the basis of paleo-ecological analysis. It is fascinating to read how paleoecologists can trace back the spreading of families, genera and sometimes even species across the globe, spanning millions of years, using such inconspicuous clues as pollen, shells, imprints of plants, soil composition and nowadays, genetic composition. Paleoecological analysis in mountainous regions works much faster than in lowlands, as it is easier to interpret ecosystem changes along temperature gradients (Cleef, 1979, 1980). Lowland analysis requires a much broader net of systematically organised soil profiles and sediment sections (A.M. Cleef 2003, pers. com.). Particularly in the humid tropics, the distribution of species is much more difficult to define and consequently when staking out biogeographical units one is still likely to see less reliability and geographical precision in present-day distributions in tropical lowlands than in mountain regions (A.M. Cleef and T. van der Hammen, pers. com.).

Prance (1982 in 1989) proposed that during Pleistocene glacial advances, when the climate of the region became drier and cooler, forest became fragmented into “Pleistocene lowland forest refugia” in Central and Northern South America. Independent speciation within those refugia would have lead to a large amount of local endemism, often referred to as “centres of endemism”. These proposed refugia are mainly based on the distribution of four woody plant families, Caryocaraceae, Chrysobalanaceae, Dichapetalaceae and Lecythidaceae. Davis et al. (1996), somewhat seem to question this “popular theory”, stating “Whether or not they were refugia, the “fact” that centres of endemism¹ exist for a large number of different organisms has been well established”. Yet, there have been suggestions, that these apparent centres of richness are merely well-collected areas”. The latter warning must be taken seriously given such findings on endemic species (See 2.3.3) as presented for instance by House et al. (2002). The latter advised extreme caution considering how difficult it is to make any quantitative comparisons on species richness in a botanically relatively well-sampled² country like Honduras. If the knowledge about the distribution of all species - including endemic species - is so highly biased by road access and centres of investigation in such a small country, sampling bias is very likely to occur in the vastness of the Amazon as well. Vreugdenhil (e.g. 1992, 1997, 2002) has organised or participated in the organisation of the collection of data in most countries in Central America and has seen how lopsided and often fragmentary data sets can be. House et al. (2002) suspect there to be good reason to even doubt the status of a part of the less-conspicuous endemic or limited distribution species, as their distribution ranges just have not yet been discovered. To go from such sketchy information to identify “centres of richness” and “centres of endemism” requires great scientific caution. Other modifiers are likely to capture such situation.

The CBD approaches biodiversity selection on a country-by-country basis. Within a worldwide strategy to seek the greatest possible representation of ecosystems and species, this has a hidden advantage: not only does it deal with the fact that conservation must have a solid legal and management basis, which primarily is dependent on national legislation and national management organisations, but in most cases, the world’s division into national territories automatically leads to plural representation of the world’s recognised biogeographical regions, including the WWF’s “Global 200”. Only in some very large countries, like Brasil, Congo, India, Russia, Anglo-America would it be possible to develop a PA system with the omission of one or more entire biogeographical regions. For a national protected areas system composition analysis of medium sized to small countries, biogeographical divisions are not strictly necessary, as detailed ecosystem maps and the selection criteria elaborated later in this document lead to much more fine-tuned area composition than possible with biogeographical regionalisation while the country-based approach de facto serves as a course proxy for biogeographical regions. This is particularly the case if PA systems are spread across a country’s entire territory as recommended in Chapter IV. This method is also much more precise than the approach suggested by Prance or the EBAs of BirdLife International. Furthermore, Davis’ suggestion that concentrations of endemism and high species diversity would go together is not necessarily the case: in the humid tropics, high endemism is particularly expected at higher elevations of isolated mountains, where biodiversity is much lower than in the surrounding humid tropical lowlands.

Dinerstein at al. (1995) developed a hierarchical classification scheme that divides Latin America and the Caribbean (LAC) into 8 Bioregions, 5 Major Ecosystem Types (METs), 11 Major Habitat Types (MHTs), and 191 ecoregions.

A bioregion is defined as a geographically related assemblage of ecoregions that share a similar biogeographical history and thus have strong affinities at higher taxonomic levels (e.g. genera, families).

A MET is a set of ecoregions that:

1.      share comparable ecosystem dynamics(³*);

2.      have similar response characteristics to disturbance (*);

3.      exhibit similar degrees of beta diversity (dependent on vast data sets) and

4.      require an ecosystem specific conservation approach (*).

The following classes have been identified: Tropical Broadleaf Forests, Conifer/Temperate Broadleaved Forests, Grasslands/Savannahs/shrublands; Xeric Formations; Mangroves.

A MHT is a set of ecoregions that:

1.      experience comparable climatic regimes;

2.      have similar vegetation structure;

3.      display similar spatial patterns of biodiversity (*); and

4.      contain flora and fauna with similar guild structures and life histories(*).

The following MHTs have been distinguished for the study region. Tropical Moist Broadleaf Forests; Tropical Dry Broadleaf Forests; Temperate Forests; Tropical and Subtropical Coniferous Forests; Grassland Savannahs and Shrublands; Flooded Grasslands; Montane Grasslands; Mediterranean Scrub; Deserts and Xeric Shrublands, Restingas and Mangroves.

An ecoregion is a geographically distinct assemblage of natural communities that

1.      Share a large majority of their species and ecological dynamics [requires large data sets;

2.      Share similar environmental conditions; and

3.      Interact ecologically in ways that are critical for their long-term persistence (*).

Ecoregions within the same MHT can be similar in their structure and ecological processes, but they share few species.

When evaluating the suitability of the eco-region classification system of Dinerstein for biodiversity mapping purposes, the following observations should be made. In the definition, the system pretends leans heavily on biogeographical history and, in its classification levels use distinct physiognomic criteria. However, the system is not organised systematically and it uses modifiers that can’t be clearly be identified in the field. At the level of the MET, none of the four characteristics as formulated in the definition can be measured objectively and require expert consensus building through workshops. As such, they can’t be mapped from remotely sensed imagery and as result, the main ecoregions map in Dinerstein (1995 ) must be considered highly speculative. Of the MHT, only the first two criteria may be defined and identified objectively, but one would need a set of properly defined selection criteria. Again, the MHTs can’t be mapped from remotely sensed imagery, as half of its modifiers are unidentifiable.

The primary characteristics of the ecoregions as they appear in the definition cannot be measured objectively and analysis of these regions suggest that they are geographically distinct versions of the MHT, which are more than anything else, coarsely separated physiognomic climatic classes. The method is intrinsically weak as it builds on a combination of a set of modifiers consisting of consensus derived versus mappable criteria and a number of poorly defined modifiers. Therefore, it cannot be reproduced or complemented by independent researchers; with poorly defined modifiers, users cannot know the criteria of distinction of the species assemblages. The ecoregions approach has been designed for continental applications at a scale of 1:10,000,000 (D.J. Graham, pers. com). Yet, the map has been very useful for giving a first quick impression to analyse where major gaps occurred at a continental basis, using the available techniques of its time, but for national protected areas system analysis, it is too unspecific.

Each one of the levels of Dinerstein’s method has elements that can not be used as a classifier as they are either not defined and/or not readily identifiable in the field or from remotely sensed data. The method must be considered a one-time product that cannot be reproduced.

The biogeographical focus for demarcating species regionalisation patterns would be the strength of this mapping concept, but the scientific basis for it is weak. Biogeographical distinction should not be derived from consensus building workshops but from field-data showing patterns of distribution variation, and much more work needs to be done to consolidate the foundation of species regionalisation patterns. Usually workshops tend to strive for consensus, but the results are not always objective and reproducible. They are important for agreeing on objectives, methods, rules and criteria, verification and for joint evaluation of the results. Actual classification and delineation, however, should result from objectively identifiable and reproducible modifiers.

To summarise: as a distinct modifier biogeographical regionalisation may significantly contribute to an ecosystems classification system. However, the level of feasible detail is subject to the knowledge about the distribution of indicator families, genera or species for such regionalisation. A system primarily focussing on biogeographical patterns is too coarse for the design of national protected areas systems, but it may serve to pre-analyse worldwide representation of coarse sets of species, as seems to be applied by the Worldwide Fund for Nature, (WWF,

http://www.panda.org/resources/programmes/global200/pages/home.htm 2002).

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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