DISCUSSION
In the analyses of richness and beta diversity, we found that
environmental conditions captured most of the variation in fish species
diversity, suggesting that environmental conditions were satisfactorily
represented using average values and standard deviations, whereas the
spatial component contributed little to structuring fish communities.
Interpretation of spatial processes and its association with dispersion,
made using spatial eigenvalue maps, has to be done carefully because
they bring not only information on spatial structuring but also on
environmental conditions (Diniz-Filho et al. 2003; Hawkins et al. 2007).
The beta diversity of different guilds, especially insectivores and
omnivores species, displayed little correlation with environment
conditions and a greater one with spatial processes. This result may be
explained by the spatial component representing collinear unmeasured
environmental conditions rather than effects of space itself, or that
insectivorous and omnivorous fish have greater dispersion abilities. A
higher dispersal capacity can hide effects of environmental gradients,
as species can rapidly colonize sites that have unfavorable conditions,
and suppress effects of local extinction (Grönroos et al. 2013). If this
was the case for insectivorous and omnivorous species, Mass Effect may
be the predominant mechanism structuring their communities. In contrast,
detritivores fish and the total community were structured by Species
Sorting effects, or an interaction between Mass Effect and Species
Sorting (Cottenie 2005), as these communities showed a strong
relationship with environmental conditions and a weak one with space.
Although the Local W model was the best representation of space for the
entire ichthyofauna community, we observed a weak relationship between
fish communities (richness and total beta diversity) and spatial
components. This weak association may have occurred due to two factors:
(i) the ability of fish to actively select habitats would be more
important than dispersion, indicating the SpeciesSorting mechanism of
metacommunity structure (Leibold 2004), which is considered the main
mechanism responsible for structuring natural meta communities (Cottenie
2005; Van der Gucht et al. 2007; Vanschoenwinkel et al. 2007; Landeiro
2011), (ii) the ”path” along which fish species have dispersed is
environmentally unsuitable, restricting their dispersion (Grönroos et
al. 2013). Although the characteristics of streams were controlled in
order to be representative of natural conditions, the connection between
these points was not controlled. Thus, it may be that sites, although
preserved, are connected by non-suitable drainage that act as a barrier
and limit the dispersion of ichthyofauna (Grönroos et al. 2013).
Linear distances without considering hydrographic units fail to
represent spatial process in stream fishes communities. The use of the
linear distance is a simplistic and insufficient way to measure spatial
processes in aquatic systems (Landeiro 2011). When including the
geographic barriers into the linear distance procedure (called Local W
here), the linear distance was able to provide a good representation of
the geographic patterns of the fish community. The performance of Local
W is better than the dendritic distance (W Water), shown previously as
the best means to represent spatial processes in aquatic systems. Using
Local W, we were able to identify a simple and robust way of
representing spatial processes considering the physical barriers
separating communities. This result was consistent across all components
of the community (i.e. overall community or discrete feeding
guilds) and ecological descriptors (i.e. species richness or beta
diversity).
A second feature of our results is related to the dispersion of
detritivores fish, which cannot be represented using simple Euclidian
distances between points, considering or not geographic barriers or
hydrological distances. The best way to represent space process for this
guild was applying the Hydalt W model. It considers the dendritic
distance between points (and barriers), and the direction of the flow.
The application of connectivity models associated with flow direction is
advocated by some authors as being the most suitable for aquatic
organisms (Pearson et al. 2007; Peterson and Ver Hoef 2010). However,
with the analysis of our data, we observed that this approach is more
complex than the Euclidian distance (considering barriers - Local W),
and was only necessary for detritivores fish.
The low dispersion of stream fish is evidenced by the negative
relationship between fish communities and spatial filters. Considering
that small eigenvalues are related to local structuring and higher
eigenvalues to larger scale structuring (Grffith et al. 2006; Blanchet
et al. 2008), we interpret that fishes from stream are dispersing across
small spatial scales, as richness and beta diversity were negatively
related to the filters. This result supports the idea of preserved
spots connected by altered ”paths”. Thus, fish species with low
dispersal ability tend to express spatial structure more clearly than
ones with higher dispersal ability (Thompson and Townsend 2006; Astorga
et al. 2011).
Species Sorting predicts a correlation of metacommunity structure only
with environmental gradients (Leibold et al. 2004). The interaction of
space (dispersion) and environment in the structuring of metacommunities
is attributed solely to the Mass Effect model2.
However, is it not possible to separate these two mechanisms, and
metacommunities that are related to space and environment are understood
as interaction between Species Sorting and Mass Effect (Cottenie 2005;
Vieira and Tejerina-Garro 2020; Brasil et al. 2019). This interaction
was found in 29% (46) of the communities analyzed by Cottenie (2005)
and also found for fish (Landeiro et al. 2011; Vieira and Tejerina-Garro
2020; Vieira et al. 2020) and other groups (Brasil et al. 2019).
However, the ichthyofauna show a greater correlation with environmental
conditions than spatial processes, suggesting that Species Sorting is
the key mechanism in structuring fish communities (37% of the
metacommunity analyzed by Cottenie (2005) show this result). This result
does not rule out the occurrence of dispersion (Cottenie 2005; Landeiro
et al. 2011; Vieira and Tejerina-Garro 2020; Brasil 2019), but
reinforces the idea that dispersion occurs locally and weakly (negative
relation with the spatial eigenvectors maps).
Species Sorting is related to many freshwater organisms, such as
macroinvertebrates (Grönroos et al. 2013; Heino et al. 2013), snails
(Hoverman et al. 2011) and bacteria (Van der Gucht et al. 2007). The
influence of the Species Sorting mechanism in communities at large
scales (three basins) was found indicating that there was no variation
in the metacommunities among basins, but a continuous variation
according to an environmental gradient (Heino et al. 2014). Dispersion
has little influence on metacommunity patterns at large scales (Grönroos
et al. 2013; Heino et al. 2013). In fact, dispersion decrease at large
scales as the same way that environmental gradient increase the
correlation with metacommunity structure (Grönroos et al. 2013; Astorga
et al. 2011). In addition, fish can only migrate using drainage and some
species tend not to migrate or are prevented from migrating due to
physical barriers such waterfalls or dams. Furthermore, species that
actively disperse tend to select the environment in which they will
settle, further reducing effects of spatial structure (Grönroos et al.
2013).
The variation partitioning of fish communities between environmental
conditions and geographic space tend to associate environmental
conditions with niche (i.e. environmental conditions) or neutral (i.e.
geographic distances) theory (Smith and Lundholm 2010). When communities
are more correlated with environmental conditions than geographic
distance, the communities are structured by niche theory. On the other
hand, when the geographic distance are more correlated than environment,
the discussion is focused on neutral theory. This dichotomous view is
overly simplistic and does not reflect the complexities of the multiple
mechanisms that concurrently structure natural communities. Communities
are not the effect of only one of these two theories, but the
interaction between them (Juen and De Marco 2012). More recent analyses
(Cottenie 2005; Van der Gucht et al. 2007; Grönroos et al. 2013; Astorga
et al. 2011; Vieira and Tejerina-Garro 2020; Vieira et al. 2020; Brasil
et al. 2019; Heino 2011) demonstrate the association of the community
with the mechanisms proposed by Leibold et al. (2004). In this case, the
relationship between communities and environmental conditions are
related to the Species Sorting mechanism, the relationship between
community and space to the neutral or Patch Dynamic mechanisms, and the
interaction between space and conditions related to the Mass Effect
mechanism (Cottenie 2005). However, the dissociation of Mass Effect and
Species Sorting is not trivial, since the dispersion limitation in
communities within Species Sorting can produce a pattern with
relationship between space and environmental conditions, a Mass Effect
dynamic (Cottenie 2005).
Therefore, we conclude that the ichthyofauna of Cerrado streams are
structured by an interaction between Mass Effect and Species Sorting
mechanisms. Among the trophic guilds considered, only the beta diversity
of insectivores and omnivores is influenced by the geographical space,
suggesting an effect of Neutral or Patch Dynamic models. Finally, we
found that the linear distance measures that take into account the
physical barriers (Local W in this study) are the best representations
of spatial patterns for the fish communities, except for the
detritivores that are influenced by the flow direction variable in the
connectivity models (Hydalt W). Regarding the environmental conditions,
it is necessary that these were represented by the average and some
metric (e.g. heterogeneity of substrates, beta diversity and metrics
variance) that measures their variation to best evaluate the degree of
environmental heterogeneity.