Using social network analysis of mixed-species groups in African savannah herbivores to assess how community structure responds to environmental change

Abstract

The dynamics of wildlife populations often depend heavily on interspecific interactions and understanding the underlying principles can be an important step in designing conservation strategies. Behavioural ecological studies can here provide useful insights into the structure and function of communities and their likely response to environmental changes. In this study of the Masai Mara herbivore community, we use a social network approach to investigate social affinities between species and how these change over the year in response to seasonal changes in ecological conditions. We find that even though social networks were correlated across different ecological conditions, for half the species dyads in the community, the strength of social affinities responded to changes in rainfall and/or the presence of migratory wildebeest. Several species consequentially adopted more or less central positions in the network depending on the ecological conditions. The findings point out interspecific social links that are likely to be attenuated or strengthened as a consequence of human-induced environmental changes and therefore call for particular attention from conservation managers. The eco-evolutionary ramifications of the perturbations of social affinities still require further study. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

Alarm communication networks as a driver of community structure in African savannah herbivores

“…In this context, it should also be noted that we focussed on general patterns in social affinity averaged over one year, and it is likely that seasonal and interannual variation in food availability affects the role of resource competition costs relative to antipredator benefits, with consequences for the compositions of MSGs. However, whereas evidence from the study system indeed shows that patterns in social affinity undergo seasonal changes (Kiffner et al ; Meise et al ), the ABM‐predicted increase in heterospecific affinity when resources are scarce during the dry season was not evident from our seasonal analysis (Meise et al ). The context‐dependent dynamics generated by seasonal variation in costs and benefits thus warrant further study.…”

“…Social affinity ( W ) within species pairs was determined by using the data from the species counts to calculate the social affinity index according to Meise et al (). This index takes into account the number of individuals of each species in each group as well as the relative abundance of all species in the population:where g is the number of groups, and N i is the number of individuals in the group i (note the subtraction of 1 is to exclude the focal individual).…”

“…Social affinity (W) within species pairs was determined by using the data from the species counts to calculate the social affinity index according to Meise et al (2019). This index takes into account the number of individuals of each species in each group as well as the relative abundance of all species in the population:…”

The role of habitat configuration in shaping animal population processes: a framework to generate quantitative predictions

“…Rapid habitat changes are also a major threat to wildlife, as they can alter the movement patterns of individuals which may have consequences for populations (Collingham and Huntley, 2000;Todd et al, 2009). As habitat changes, individual animals can experience different spatial distributions of resources and risks, which in turn can alter the patterns of both intraspecific interspecific (Farine et al, 2015;Meise et al, 2019) interactions among individuals, as well as other processes such as dispersal patterns and gene flow (Wey et al, 2015). In population ecology, for example, changes in habitat physical configurations can reduce rates of movements among neighbouring subpopulations, which potentially reduces gene flow at the scale of meta-populations (Keller and Largiader, 2003) and impacts the persistence of populations (Frankham, 2005).…”

Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation

“…Conceptually, new insights into individual variation in behavioural responses to environmental change come i.e. from recent studies of animal personalities [8][9][10], pace-of-life syndromes (POLS) [11,12], gene-by-environment interactions (GEI) [13,14] and definitions of fitness [15,16], while higher-order drivers of population responses are revealed by research into collective behaviour [17,18] and multi-species interactions [19][20][21], with spatial variation in fitness explicated by the field of movement ecology [22,23] and related concepts such as 'landscapes of fear' [24]. Technologically, the quantity and quality of data available have been revolutionized with major breakthroughs in animal tracking and remote-sensing [25], the omics [26] and the processing of Big Data [27].…”