7. Metapopulations and Biodiversity on the Metacommunity Landscape

Headwater streams dominate stream channel length in catchments. They are important sources of water, sediment and biota for downstream reaches and critical sites for organic matter and nutrient processing. Aquatic biodiversity in headwater streams has been overlooked in comparison to higher-order rivers, and few studies have considered spatial biodiversity patterns in headwater streams, or streams in general. I reviewed studies of macroinvertebrate diversity in headwater streams and found equivocal evidence to support the view that headwater streams harbour high biodiversity. Headwater streams might still make an important contribution to γ (regional) diversity at the landscape (catchment) scale by virtue of high β (among-assemblage) diversity. I studied eight headwater streams from three forested, upland catchments along the Great Dividing Range, Victoria, Australia to test my hypothesis of high β diversity and to understand the spatial patterns and determinants of macroinvertebrate diversity in headwater stream networks. Diversity partitioning showed that reaches each had high α (within-assemblage) diversity, while β diversity made only a small contribution to γ diversity at both the reach and catchment scales. β diversity may have been lower than hypothesized due to relatively small distances between sites and high levels of dispersal among reaches and catchments in the study area. Contrary to other studies that have found environmental factors to be important for explaining variation in macroinvertebrate assemblage structure in headwater streams, I found a limited role for environmental factors structuring macroinvertebrate assemblages in the study area. In one year (2008), spatial factors (independent of environmental factors) were the dominant factor structuring macroinvertebrate assemblages. Therefore, metacommunity structure in the study area aligns most closely with the neutral/patch dynamic metacommunity model. This pattern of spatial structuring, coupled with low β diversity, suggests that high neighbourhood dispersal might be the main factor structuring macroinvertebrate assemblages in the study area. Flow permanence had only a seasonal effect on macroinvertebrate diversity and so there is a temporal component to the spatial diversity patterns in this system. The explicit recognition of stream ecosystems as spatially structured networks has increased our understanding of ecological patterns and processes, and provided the impetus for this research. Recent advances in the study of networks, particularly in the fields of physics and network theory, offer an opportunity to considerably extend the current application of the network concept in stream ecology. Determining the relative contributions of α and β diversity to γ diversity, and the scale dependence of α and β components, provides vital information for conservation planning because optimal reserve designs will differ depending on the relative contributions of α and β diversity. My finding of high α and low β diversity indicates that each stream in the study area can be considered to have low irreplaceability and the capacity to contribute a large portion of species to regional conservation targets. Information on spatial patterns of diversity is urgently required for systematic conservation planning for freshwater reserves if we are to halt the rapid decline in global freshwater biodiversity.

Increasing human demands for production and goods continuously leads to the loss and fragmentation of habitat and eutrophication and threatens biodiversity. Organisms that comprise biodiversity interact with each other and depend on each other and thus, biodiversity is organised in complex interaction network. On the one hand, food-web research has addressed how trophic interactions shape local communities and how global change drivers such as eutrophication affects them. On the other hand, metacommunity research has been focused on spatial distributions and geographic drivers of local and regional biodiversity and how global change drivers such as habitat fragmentation species communities. These two realms have, however, mostly been separate. In this thesis, I present a meta-food-web model that synthesizes local trophic interactions and interpatch dispersal. This model employs species body masses as an interlinking trait that creates food webs and trophic dynamics through predator-prey body mass ratios and spatial networks through species dispersal capacities. With the meta-food-web model, I uncover mechanisms shaping biodiversity that only arise as a consequence of the synthesis of spatial and trophic interactions. The perspective from meta-food-webs reveals that the effect of global change drivers such as eutrophication and habitat fragmentation are highly context dependent and their effect depends on food-web and landscape structures. Furthermore, I show that interacting global change drivers can create non-linearities in biodiversity responses. Thus, this thesis provides a tool and theory derived hypotheses to shed light on consequences of global change and on what may be important to conserve biodiversity.

A recurring question in ecology is how species diversity arises and persists. Theoretical ecology tries to find underlying principles that explain spatial and temporal species diversity. Models are a valuable tool for this endeavour as they allow to study systems in well-known settings and pin down decisive processes that shape diversity. Consensus on the core mechanisms that shape diversity is achieved, namely an interplay of evolutionary and spatial processes, but many aspects still need to be included in an overarching theory. One aspect often neglected in models for the sake of simplicity is spatial heterogeneity even though heterogeneity is considered a main driver for species diversity. A similar problem exists for trophic structure. Food web theory has successfully reduced the high dimensional complexity of an ecosystem to predator-prey interactions and proven to capture essential features of empirical food webs like fraction of basal, intermediate and top species. Still many models that try to answer which processes shape diversity neglect food web structure. This work incorporates both aspects, food web structure and spatial heterogeneity, into the model-based examination of species diversity. Two different food web models considering different scales of space and time are studied: First, a meta-food web model on smaller spatial scales with classical population dynamics to examine diversity patterns found in heterogeneous landscapes and particularly at ecotones. The model suggests that the coupling strength between habitats is crucial for the final outcome of species diversity. A hump-shaped diversity-dispersal relation is observed which is enhanced compared to former studies in homogeneous spatial settings. Second, a new evolutionary food web model developed in this work which is employed to study species diversity on large spatial and temporal scales first in homogeneous and then in heterogeneous landscapes. In both settings the model reproduces a set of well-known empirical diversity patterns, namely species-area relationship, range size distribution, similarity decay of diversity with distance as well as lifetime distributions and evolution of species range sizes, but the exact shape of the relations depends on the spatial setting. Trophic levels have major impacts on the dynamics of species in both settings. Basal species have larger ranges and longer lifetimes than species on higher trophic levels. The most striking difference occurs in geographic range size evolution curves. Homogeneous spatial settings lead to symmetric curves for basal species, whilst in heterogeneous systems these curves become asymmetric. This work demonstrates that heterogeneity and complex trophic structure must not be neglected and can easily extend existing ecological models. This enhances the usability of such tools in tackling the questions related to the emergence of biodiversity in space and time. The good agreement with many results found in real systems indicates that the models presented here, despite their simplicity, capture the essence of the processes at work in reality. Consequently such models can guide future research direction and help specify empirical testable hypotheses.