cannot generate shared distribution patterns (Humphries and Parenti 1999). Cladistic biogeographic methods are allegedly process-free: inference of the area cladogram is done with no consideration to the biogeographical events that may have generated the pattern. If any, these are inferred a posteriori through comparison of the area cladogram with the individual species patterns (Brooks 2005). Uncoupling the inference of biogeographic patterns from the underlying evolutionary processes made it difficult to compare alternative biogeographic scenarios (Sanmartín 2012).
The next biogeographic school was “event-based biogeography” (EBM, Ronquist 1997, 2003). Biogeographic processes or events are tied to weights or “costs”, and the analysis consists of finding the pattern of area relationships with the minimum cost in terms of these processes. Four biogeographic events are considered in EBMs (Figure 2.1): vicariance, duplication, dispersal and extinction. The last two are tied to a speciation event and have also been termed “partial dispersal”, or “sorting, extirpation, and range contraction” for partial extinction. Within dispersal, we may distinguish “jump dispersal”, where a lineage migrates from one area to another (A to B) followed by speciation, and “range expansion”, where a lineage expands its range, leading to a temporally widespread distribution (A to AB); the latter is termed “geodispersal” when it affects multiple lineages (Lieberman 2003). Two biogeographic events are not considered in EBMs because they leave no observable traces in the phylogeny, that is, no descendants survive in the ancestral range (Sanmartín 2012): “full dispersal”, colonization of an area that is not followed by speciation, and “full extinction”, when the lineage entirely disappears from its ancestral range, that is, lineage extinction (Figure 2.1).
Figure 2.1. Biogeographic processes. Four types of biogeographic processes are considered in event-based biogeography: vicariance (allopatric speciation in response to a general dispersal barrier affecting multiple lineages); duplication (speciation within the area, i.e. sympatry, or allopatric speciation in response to a temporary dispersal barrier); extinction (the disappearance of the lineage from part of its ancestral range); dispersal (colonization of a new area by crossing a pre-existent barrier). Two processes: full dispersal and full extinction (right) cannot be modeled by EBMs because they leave no observable traces in the phylogeny
2.2.1. Parsimony-based tree fitting
The two most popular EBMs are parsimony-based tree fitting and dispersalvicariance analysis (Ronquist and Sanmartín 2011). Parsimony-based tree fitting, implemented in the software TreeFitter, was born from methods used in host–parasite tree reconciliation, with which it shares many similarities (Ronquist 2003). In tree fitting, a taxon cladogram is fitted onto the area cladogram by searching for the sequence of events that explain the tip distributions according to the area cladogram and with the minimum cost. The area cladogram may be a hypothesis of relationships based on geological history, in which case we measure how much the observed distributions depart from geologically predicted vicariance (Sanmartín and Ronquist 2004). Alternatively, it may be an unknown parameter, in which case, tree fitting consists of finding the area relationships and the sequence of biogeographic events that explain the tip distributions in the phylogeny with the minimum cost. Searching for the optimal (minimum-cost) area-cladogram implies enumerating and fitting all possible hierarchical combinations of areas. If the number of areas is large, it is possible to use heuristic search tools such as those employed in parsimony phylogenetics (nearest-neighbor interchange, branch and bound, etc.). In Figure 2.2(a), the distribution of species 1– 3 in area A, which is the sister in the area cladogram to the clade BCD (Figure 2.2(b)), is explained by a sequence of events involving duplication of a widespread ancestor in ABCD, extinction of the ancestor of species 1 in part of this range (BCD), successive vicariance events, and dispersal of the ancestor of species 3 and 4 to A, followed by allopatric speciation (Figure 2.2(c)).
From the description above, it can be deduced that the most important problem in EBMs is to find the optimal cost assignments. The most common criterion is to select event costs that maximize the conservation of distribution ranges along the phylogeny (Ronquist 2003). Figure 2.1 shows that dispersal and extinction are not “phylogenetically conserved or constrained” processes because they interrupt the “vertical inheritance” of geographic ranges from ancestor to descendants. In dispersal, the colonized area B is not part of the ancestral range (Figure 2.1(c)); in extinction, part of the ancestral range (A) is lost in the right descendant (Figure 2.1(d)). Conversely, vicariance and duplication are phylogenetically constrained processes because either each descendant inherits the entire ancestral range (duplication) (Figure 2.1(b)) or the union of the two descendants’ ranges equals the ancestral range (vicariance, Figure 2.1(a)). A consequence of this cost assignment is that the frequency of dispersal and extinction events is minimized relative to vicariance and duplication in EBM reconstructions. A similar phylogenetic conservation criterion is used in parsimony-based inference to minimize homoplasies (convergence and parallelism), as evolutionary changes that are not identical by descent, that is, losses and gains of traits in unrelated lineages. In the TreeFitter reconstruction in Figure 2.2(c), extinction (e) receives a cost of 1 and dispersal (i) a cost of 2; vicariance (v) and duplication (d) are given minimum costs (0.01); the lower cost of extinction relative to dispersal is due to extirpation preserving part of the ancestral range (Figure 2.1; Sanmartín and Ronquist 2004).
Figure 2.2. Event-based biogeography. a) An organism phylogeny with six species (1–6) distributed in four areas (A–D). b) Area cladogram depicting relationships among areas of endemism. c) TreeFitter reconstruction: total cost = 3.04. d) DIVA reconstruction, total cost = 2.0. Notice that TreeFitter and DIVA provide a full description of ancestral ranges and explanatory events but differ in the treatment of duplication (see the text). Symbols: vicariance (circle), duplication (rhombus), dispersal (arrow or cross) and extinction (short line). For a color version of this figure, see www.iste.co.uk/guilbert/biogeography.zip
2.2.2. Dispersal–vicariance analysis
Dispersal–vicariance analysis (Ronquist 1997), implemented in the software DIVA, is arguably the most popular event-based method. DIVA resembles character-state reconstruction methods employed in phylogenetic inference to map the evolution of a trait, such as the optimization algorithm of Fitch Parsimony. Given a tree and associated geographic ranges, ancestral distributions are mapped (optimized) along internal nodes by finding the sequence of biogeographic events that minimizes the total cost of the reconstruction. A major difference with Fitch Parsimony is that, while phylogenetic inference assumes single-state ancestors, DIVA allows ancestors present in two or more states, that is, widespread ancestral ranges formed by two or more discrete areas. This difference implies that DIVA optimization is more complex than Fitch’s because it needs to include both anagenetic and cladogenetic events of range evolution. Changes in distribution range along the branches of the phylogeny (anagenetic change) are optimized as dispersal (range expansion: A to AB) or extinction (range contraction: AB to B) events. Range evolution at cladogenetic (speciation) nodes can involve duplication, if the ancestor occupies a single area (A/A), or vicariance, if a widespread ancestral range is divided into non-overlapping subsets (A/B). DIVA uses a slightly less complex cost-matrix than TreeFitter: dispersal and extinction are assigned a cost of 1, and duplication and vicariance, a cost of zero.
Figure 2.2(d) shows DIVA reconstruction for the same biogeographic scenario as in Figure 2.2(c). Notice that it is simpler than in TreeFitter, requiring only vicariance events interspersed with dispersal events. This example illustrates a difference between these two methods that is not always well understood (Wodcicki and Brooks 2005). As in cladistic biogeography, TreeFitter output is an area cladogram, whereas DIVA maps ancestral distributions and inferred biogeographic events onto the phylogeny.
