Research Article: Does a Species’ Extinction–Proneness Predict Its Contribution to Nestedness? A Test Using a Sunbird-Tree Visitation Network

Date Published: January 19, 2017

Publisher: Public Library of Science

Author(s): Charles A. Nsor, Hazel M. Chapman, William Godsoe, Jeff Ollerton.

http://doi.org/10.1371/journal.pone.0170223

Abstract

Animal pollinators and the plants they pollinate depend on networks of mutualistic partnerships and more broadly on the stability of such networks. Based mainly on insect-plant visitation networks, theory predicts that species that are most prone to extinction contribute the most to nestedness, however empirical tests are rare. We used a sunbird-tree visitation network within which were both extinction prone vs non extinction prone sunbird species to test the idea. We predicted that the extinction prone species would contribute the most to nestedness. Using local abundance as a proxy for extinction risk we considered that locally rare sunbird species, by virtue of their small population size and associated demographic stochasticity to be more at risk of extinction than the common species. Our network was not strongly nested and all sunbird species made similar contributions to nestedness, so that in our empirical test, extinction proneness did not predict contribution to nestedness. The consequences of this finding remain unclear. It may be that network theory based on plant-insect mutualisms is not widely applicable and does not work for tree- sunbird mutualistic networks. Alternatively it may be that our network was too small to provide results with any statistical power. Without doubt our study highlights the problems faced when testing network theory in the field; a plethora of ecological considerations can variously impact on results.

Partial Text

Pollinator declines are of global concern for biodiversity and food security [1] so that understanding how plant-pollinator networks respond to perturbations has applications in both conservation biology and agricultural science [2]. For example, individual species make different functional contributions to network properties, so that their decline will have differing implications for the stability of a network [3, 4]. This is especially relevant in networks where one/some of the players are threatened with extinction [3]. In some cases losing a single species will trigger cascade effects, where the loss of one species sets off a cascade of secondary extinctions [5]. However, it is difficult to use current network theory to accurately predict how the loss of single species within a network affects the stability of the whole network; there is controversy in the literature as to which network properties most influence species survival and network stability [6, 7, 8].

Our study was conducted in and around Ngel Nyaki Forest Reserve (NNFR; 07° 05′ N 11° 04′ E) on the eastern edge of the Mambilla Plateau in Taraba State, Nigeria at an elevation of approximately 1650 m a.s.l. NNFR is 46 km2, comprising c. 7.5 km2 of montane forest surrounded by overgrazed Sporobilus grassland and small riparian forest fragments [35] (Fig 1). Sunbirds use a variety of habitats in NNFR, including forest, forest edge and riparian fragments [36] and can be envisaged as an island of sunbird habitat within a sea of grassland. Ngel Nyaki forest is the only forest of its kind remaining on the Mambilla Plateau [35].

Table 1 illustrates the relative abundance of all sunbird species in our network. The least abundant sunbird the collared sunbird, Hedydipna collaris was not recorded at all in our transect survey while the most common species in the network, the variable sunbird, was recorded 525 times. In our network (Fig 2, S1 Table) the total number of tree species (14) was greater than the number of sunbird species (7). The overall network nestedness (NODF value) was 73.23 This degree of nestedness is substantially higher than expected if all bird-tree interactions occurred at random (P<0.005), But it is not significantly different from what would be expected from chance alone when we constrain for connectance and species’ degree using the curveball algorithm (Strona et al. 2014). Our bird-tree visitation network is the first of its kind to be described from a West African montane habitat. While it is a sub-set of a larger network (we didn’t include insect or bat visitors in this network) it nevertheless adds to our knowledge and understanding of bird-plant visitation networks and provides valuable base-line data from which we can refine both our questions and empirical methods.   Source: http://doi.org/10.1371/journal.pone.0170223

 

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