Compartmentalized organization of ecological niche occupation in insular invertebrate communities

Abstract

Understanding the mechanisms of species distribution within ecosystems is a fundamental question of ecological research. The current worldwide changes and loss of habitats associated with a decline in species richness render this topic a key element for developing mitigation strategies. Ecological niche theory is a widely accepted concept to describe species distribution along environmental gradients where each taxon occupies its own distinct set of environmental parameters, that is, its niche. Niche occupation has been described in empirical studies for different closely related taxa, like ant, ungulate, or skink species, just to name a few. However, how species assemblages of whole ecosystems across multiple taxa are structured and organized has not been investigated thoroughly, although considering all taxa of a community would be essential when analyzing realized niches. Here, we investigated the organization of niche occupation and species distribution for the whole ground-associated invertebrate community of small tropical insular ecosystems. By correlating environmental conditions with species occurrences using partial canonical correspondence analysis (pCCA), we demonstrated that the ground-associated invertebrate community does not spread evenly across the overall niche space, but instead is compartmentalized in four distinct clusters: crustacean and gastropod taxa occurred in one cluster, attributable to the beach habitat, whereas hexapods and spider taxa occurred in three distinct inland clusters, attributable to distinct inland habitats, that is, grassland, open forest, and dense forest. Within the clusters, co-occurrence pattern analysis suggested only a few negative interactions between the different taxa. By studying ground-associated insular invertebrate communities, we have shown that species distribution and niche occupation can be, similar to food webs, organized in a compartmentalized way. The compartmentalization of the niche space might thereby be a mechanism to increase ecosystem resilience, as disturbances cascade more slowly throughout the ecosystem.

Keywords: Niche clustering; ecological community; habitat; insular ecosystem; modularity; niche segregation; species assemblage.

Figure 1

Position of the Lhaviyani (Faadhippolhu) atoll within the Republic of the Maldives (left) and location of the sampled islands, Dhidhdhoo, Gaaerifaru, Lhossalafushi, Varihuraa, Vavvaru, and Veyvah (right). Dark gray indicates land masses, and light gray around the islands indicates the spatial extensions of the lagoons and reefs surrounding each coral island. Note that Lhossalafushi and Varihuraa are two separate islands that do not share any land bridge but have the same outer coral reef

Figure 2

Ecological niche space provided by the investigated uninhabited coral islands (N = 6). Calculation of the NMDS representation of the niche space is based on normalized values for the following parameters: soil temperature, soil grain size, seagrass detritus amount, terrestrial detritus amount, soil water content, grass & herb coverage, shrub coverage, tree coverage. Each data point represents one plot (N = 20 per island), and different colors indicate different islands. The spatial proximity of any two data points in the NMDS representation indicates the similarity of the two plots

Figure 3

CCA representation of the species distribution within the ecological niche space of the investigated uninhabited islands (CCA model: F = 1.990, p = .001; for details on model performance refer to Table 1). Each data point represents a single taxon within the ecological niche space, and different colors and hulls indicate the cluster assignments (NbClust method. blue: beach cluster, yellow: grassland cluster, green: open forest cluster, purple: dense forest cluster; see also Table S1 for detailed taxa identities of each cluster). The spatial proximity of any data point to a physical parameter vector indicates that this parameter influences the distribution/occurrence of the particular taxon. The vectors of physical parameters that point in the same direction indicate a positive correlation between them, and vectors that point in the opposite direction indicate a negative correlation between them

Figure 4

Co‐occurrence pattern analysis within the four identified clusters 1–4 (see also Table S1). Negative association, that is, occurrence of taxon 1 excludes taxon 2, between two taxa pairs indicated by yellow rectangles, positive co‐occurrence, that is, occurrence of taxon 1 favors occurrence of taxon 2, indicated by blue rectangles and random co‐occurrence, that is, no significant positive or negative association between two taxa, by gray rectangles