Elsevier

Applied Soil Ecology

Volume 123, February 2018, Pages 339-344
Applied Soil Ecology

Short communication
Methods for studying earthworm dispersal

https://doi.org/10.1016/j.apsoil.2017.09.006Get rights and content

Highlights

  • Dispersal is the movement of individuals away from their usual home range.

  • Dispersal drives community composition and local ecosystem functioning.

  • Dispersal can be active or passive.

  • We review the approaches to study patterns and mechanisms of earthworm dispersal.

Abstract

Dispersal is a key driver of species composition and functional traits in earthworm communities. However, it has been largely overlooked in ecological literature on earthworms because it is particularly difficult to study. In this publication, we review recent developments that have been made in this field of research. We present methods to assess dispersal distance, such as Capture-Mark-Recapture and molecular tools, and methods using dispersal corridors or X-ray imagery aiming at identifying the mechanisms triggering dispersal in earthworms communities.

Introduction

Dispersal plays a major role in shaping biodiversity, evolution, and ecosystem functioning. It connects localities together through fluxes of individuals and alleles. The direct consequence is that species abundance and genetic composition in different places of a landscape are not independent. In other words, local population abundance, genetic structure and community structure not only depend on local factors and processes such as habitat features, demography, genetic drift or species sorting and competition, but are also dependent on the properties of neighboring populations and communities (Leibold et al., 2004). In this perspective, we need to study local community and genetic structure at both local and regional scales in order to understand the structure of local populations or communities, as well as their functional role.

The magnitude of the dependence between local and regional scales directly results from dispersal rate. Theoretically, when dispersal is very high, local sites are well interconnected and tend to behave like a unique population or community (Economo and Keitt, 2008, Mouquet and Loreau, 2003). Local interactions are then a major driver of species composition and a low genetic differentiation among populations is expected. When dispersal is very low, local sites are isolated and behave like islands. Local populations and communities are well differentiated and severe genetic drift occurs. Extinction risk is then high for small populations. In nature, dispersal is generally between these two extremes, and complex behaviors such as source – sink dynamics may occur. In such case, certain sites can act as sources of dispersers (source), while others behave like sinks. Such dynamics can prevent extinction or speciation in certain sites. Local populations connected by dispersal are called “metapopulation” (Hanski and Gilpin, 1997), local communities connected by dispersal are called “metacommunity” (Leibold et al., 2004). In both cases, we need to understand the drivers and the magnitude of dispersal in order to understand the behavior and the properties of the system, either at local and regional scales.

Dispersal is usually defined as the movement of individuals away from their natal habitat, or from their usual home range, to a new habitat (Clobert et al., 2012). It is usually decomposed in three successive steps. First step is departure from the usual home range. Second is the transfer between the departure site and the arrival site. Third is the establishment in a new habitat (Fig. 1).

All these steps can originate from two very distinct processes: it can come from individuals' own willing, a process called “active dispersal”, or from movements driven by an external force such as wind, water runoff, displacement by another animal, or by human activities (Matthysen, 2012). Dispersal direction is generally controlled in active dispersal but not in passive dispersal.

Studying dispersal is challenging for all organisms (Nathan, 2001), because it is hard to track individuals. This is particularly true for earthworms, because they are subterranean and cannot be seen from surface. Several approaches have been developed to address these difficulties, and can be classified in two groups. The first ones focus on dispersal patterns. They intend to measure typical dispersal distances of organisms during life span, or during a precise period of time. This approach aims at producing a histogram of distances travelled over a period of time, the so called “dispersal kernel” (Nathan et al., 2012). It is thus centered on the spatio-temporal aspects of the dispersal. The second group of methods focuses on the factors that drive dispersal, such as habitat quality or conspecific density. The products of this approach are dispersal rules, like positive density dependent dispersal. This approach is often framed in game theory and evolutionary ecology. It aims at predicting dispersal behavior and understanding the reasons why different dispersal behaviors evolved.

In this work, we present techniques that are currently available to study earthworms’ dispersal from these two angles: 1) dispersal distances and 2) the factors that drive dispersal.

Section snippets

Methods for studying earthworm dispersal distance

One of the most basic question regarding dispersal of organisms is to determine how far they can move. In order to address this point, we need to estimate the distribution of the distances travelled for a given period of time. For this, two kinds of movements are often defined: the usual and most frequent movements, related to foraging, and the rare long distances movements (Nathan et al., 2008). In this framework, true dispersal usually refers to the rare and long distances dispersal events

Methods for studying mechanisms of earthworm dispersal

Another important aspect in the study of dispersal is to determine the conditions that drive individuals to disperse. These drivers can be internal, such as body size, hormonal status and age, or external, such as habitat quality or biotic interactions (Clobert et al., 2012). In earthworms, only external drivers of dispersal have been studied so far. Two techniques are now well established: the dispersal corridors (Mathieu et al., 2010), and the X ray imagery (Caro et al., 2012).

Conclusion

The several techniques that now exist to study earthworm dispersal (Table 1) can give us insights about dispersal distances and mechanisms leading to active dispersal, either in the field or in experimental devices. They offer new opportunities to quantify this process, and to estimate its contribution to population dynamics, community assembly, and finally ecosystem functioning.

Acknowledgment

We would like to thank Augusto Zanella for his commitment in this Special Issue of Applied Soil Ecology.

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