Null model analysis of species nestedness patterns

Nestedness is a common biogeographic pattern in which small communities form proper subsets of large communities. However, the detection of nestedness in binary presence-absence matrices will be affected by both the metric used to quantify nestedness and the reference null distribution. In this study, we assessed the statistical performance of eight nestedness metrics and six null model algorithms. The metrics and algorithms were tested against a benchmark set of 200 random matrices and 200 nested matrices that were created by passive sampling. Many algorithms that have been used in nestedness studies are vulnerable to type I errors (falsely rejecting a true null hypothesis). The best-performing algorithm maintains fixed row and fixed column totals, but it is conservative and may not always detect nestedness when it is present. Among the eight indices, the popular matrix temperature metric did not have good statistical properties. Instead, the Brualdi and Sanderson discrepancy index and Cutler's index of unexpected presences performed best. When used with the fixed-fixed algorithm, these indices provide a conservative test for nestedness. Although previous studies have revealed a high frequency of nestedness, a reanalysis of 288 empirical matrices suggests that the true frequency of nested matrices is between 10% and 40%.     

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (-25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.     

Nestedness of remnant sonoran desert plant communities in metropolitan Phoenix, Arizona

Urbanization can have profound effects on the plant communities persisting in remnant habitats. That process can be explored by examining patterns of nestedness. Species composition for a set of communities exhibits a nested pattern if species present in progressively richer assemblages form a series of subsets. Nestedness can form as a result of the dynamic processes of extinction or colonization. It can also reflect a nested distribution of habitats among the sites or the differential abundance properties of species through passive sampling. This study investigated whether Sonoran Desert woody vegetation in remnant islands within metropolitan Phoenix is nested and explored which mechanisms are responsible for the pattern. It also examined whether vegetation is nested in similar habitat types across islands, and how species abundance relates to the nested pattern and hypothesized mechanisms. All data sets were significantly nested, indicating a nested pattern at the island and habitat levels. Community-level analyses did not indicate a primary mechanism leading to the nested pattern. Among species with abundances correlated with the nested rank-order of sites, abundance properties were significantly related to different variables. This suggests that individual taxa respond to divergent ecological mechanisms, leading to nestedness. Thus, nestedness in plant communities can result from a complex set of contributors and may not be attributable to a single factor.     

Simulation of information propagation in real-life primate networks: longevity, fecundity, fidelity

In many vertebrate species, we find temporally stable traditions of socially learned behaviors. The social structure of animal populations is highly diverse and it has been proposed that differences in the social organization influence the patterns of information propagation. Here, we provide results of a simulation study of information propagation on real-life social networks of 70 primate groups comprising 30 different species. We found that models that include the social structure of a group differ significantly from those that assume random associations of individuals. Information spreads slower in the structured groups than in the well-mixed groups. While we found only a minor effect on the path lengths of the transmission chains, robustness against information extinction was strongly influenced by the group structure. Interestingly, robustness against information loss was not correlated with propagation speed but could be predicted reasonably well by relative strength assortativity—a structural network metric. In those groups where highly pro-social individuals preferentially interact with other pro-social individuals, information was more likely to be lost. Our results show that incorporating group structure in any social propagation model significantly alters predictions for spreading patterns, speed, and robustness of information.     

Microbial diversity and ecological networks as indicators of environmental quality

Evaluating the quality of ecosystems in terms of biological patrimony and functioning is of critical importance in the actual context of intensified human activities. Microbial diversity is commonly used as a bioindicator of ecosystems functioning. However, there is a lack of sensitivity of microbial diversity indicators in the case of moderate and chronic environmental degradation, such as atmospheric deposition of pollutants, agricultural practices, diffuse pollution by wastewater and climate change. As a consequence, there is a need for alternative bioindicators of soils and water quality. Here, we discuss the interest of adopting a more integrative approach based on biotic interaction networks beyond the simple diversity indicators. We review how the various biotic interactions can be integrated in the various microbial networks such as trophic, mutualistic and co-occurrence networks. Then we discuss the efficiency of microbial networks and associated metrics to detect changes in microbial communities. We conclude that the connectance, the number of links and the average degree of co-occurrence networks could vary from 10 to 50% in response to minor perturbations when microbial diversity parameters remain stable. Finally, we analyze studies that aimed at linking microbial networks and activity to evaluate the potential of such networks for providing simple and operational indicators of ecosystem quality and functioning.     

Direct and indirect control of grassland community structure by litter, resources, and biomass

Multiple factors linked through complex networks of interaction including fertilization, aboveground biomass, and litter control the diversity of plant communities. The challenge of explaining plant diversity is to determine not only how each individual mechanism directly influences diversity, but how those mechanisms indirectly influence diversity through interactions with other mechanisms. This approach is well established in the study of plant species richness, but surprisingly little effort has been dedicated toward understanding the controls of community evenness, despite the recognition that this aspect of diversity can influence a variety of critical ecosystem functions. Similarly, studies of diversity have predominantly focused on the influence of shoot, rather than root, biomass, despite the fact that the majority of plant biomass is belowground in many natural communities. In this study, I examine the roles of belowground biomass, live aboveground biomass, litter, and light availability in controlling the species richness and evenness of a rough fescue grassland community using structural equation modeling. Litter was the primary mechanism structuring grassland diversity, with both richness and evenness declining with increasing litter cover. There were few relationships between shoot biomass, shading, and diversity, and more importantly, no relationship between root biomass and diversity. The lack of relationship between root biomass and species richness and evenness suggests that, even though root competition in grasslands is intense, belowground interactions may not play an important role in structuring community diversity or composition.     

Food webs are built up with nested subwebs

Nested structure, in which specialists interact with subsets of species with which generalists interact, has been repeatedly found in networks of mutualistic interactions and thus is considered a general feature of mutualistic communities. However, it is uncertain how exclusive nested structure is for mutualistic communities since few studies have evaluated nestedness in other types of networks. Here, we show that 31 published food webs consist of bipartite subwebs that are as highly nested as mutualistic networks, contradicting the hypothesis that antagonistic interactions disfavor nested structure. Our findings suggest that nested networks may be a common pattern of communities that include resource-consumer interactions. In contrast to the hypothesis that nested structure enhances biodiversity in mutualistic communities, we also suggest that nested food webs increase niche overlap among consumers and thus prevent their coexistence. We discuss potential mechanisms for the emergence of nested structure in food webs and other types of ecological networks.     

Nested Subsets and the Distribution of Birds on Isolated Woodlots

Abstract. Distribution of bird species among isolated habitat patches (e.g., woodlots in an agricultural landscape) often appears to be nonrandom; species present in small, species-poor patches also are found in larger patches that support more species. Bird communities form 'nested subsets' (after Patterson & Atmar 1986) if all species found in small faunas also are found in more species-rich assemblages. Occurrence of a nested subset pattern implies an underlying, nonrandom pattern of species distributions. I used computer simulations to analyze the degree of nestedness exhibited by bird communities in east-central Illinois. Results demonstrated that the distribution of bird species breeding in isolated woodlots (1.8 to 600 ha) differed significantly from that predicted by a random distribution model; species assemblages were more "nested" than expected by chance. Most species present in small, species-poor woodlots also were found in larger, species-rich woodlots. As groups, species requiring forest interior habitat for breeding and species wintering in the tropics showed highly nested distributions. In contrast, short-distance migrants and species breeding in forest edge habitat showed more variable distribution patterns, species recorded on smaller woodlots were not always recorded on larger, more species-rich wood-lots. Apparent absences from larger woodlots may have reflected real distribution patterns or insufficient sampling of edge habitats. These results support previous conclusions that small habitat patches are insufficient for preservation of many species.     

Currents connecting communities: nearshore community similarity and ocean circulation

Understanding the mechanisms that create spatial heterogeneity in species distributions is fundamental to ecology. For nearshore marine systems, most species have a pelagic larval stage where dispersal is strongly influenced by patterns of ocean circulation. Concomitantly, nearshore habitats and the local environment are also influenced by ocean circulation. Because of the shared dependence on the seascape, distinguishing the relative importance of the local environment from regional patterns of dispersal for community structure remains a challenge. Here, we quantify the "oceanographic distance" and "oceanographic asymmetry" between nearshore sites using ocean circulation modeling results. These novel metrics quantify spatial separation based on realistic patterns of ocean circulation, and we explore their explanatory power for intertidal and subtidal community similarity in the Southern California Bight. We find that these metrics show significant correspondence with patterns of community similarity and that their combined explanatory power exceeds that of the thermal structure of the domain. Our approach identifies the unique influence of ocean circulation on community structure and provides evidence for oceanographically mediated dispersal limitation in nearshore marine communities.     

Large-scale diversity and biogeography of benthic copepods in European waters

A large-scale database concerning benthic copepods from the Arctic, Baltic Sea, North Sea, British Isles, Adriatic Sea and Crete was compiled to assess species richness, biodiversity, communities, ecological range size and biogeographical patterns. The Adriatic showed the highest evenness and the most species-rich communities. Assemblages from the North Sea, British Isles, Baltic and Crete had a lower evenness. The British Isles were characterised by impoverished communities. The ecological specificity of copepod species showed two diverging trends: higher specificity of species in more diverse assemblages was observed in the Adriatic, North Sea and Baltic. A uniformly high species specificity disregarding sample diversity was found on Crete and in the British Isles. Benthic copepod communities showed distinct patterns that clearly fit the predefined geographical regions. Communities were distinguishable and β-diversity was found to be high around Europe, indicating a high species turnover on the scale of this investigation. The British Isles and the North Sea were found to be faunistic links to the Baltic and the Arctic.     

Dominant species identity, not community evenness, regulates invasion in experimental grassland plant communities

While there has been extensive interest in understanding the relationship between diversity and invasibility of communities, most studies have only focused on one component of diversity: species richness. Although the number of species can affect community invasibility, other aspects of diversity, including species identity and community evenness, may be equally important. While several field studies have examined how invasibility varies with diversity by manipulating species identity or evenness, the results are often confounded by resource heterogeneity, site history, or disturbance. We designed a mesocosm experiment to examine explicitly the role of dominant species identity and evenness on the invasibility of grassland plant communities. We found that the identity of the dominant plant species, but not community evenness, significantly impacted invasibility. Using path analysis, we found that community composition (dominant species identity) reduced invasion by reducing early-season light availability and increasing late-season plant community biomass. Nitrogen availability was an important factor for the survival of invaders in the second year of the experiment. We also found significant direct effects of certain dominant species on invasion, although the mechanisms driving these effects remain unclear. The magnitude of dominant species effects on invasibility we observed are comparable to species richness effects observed in other studies, showing that species composition and dominant species can have strong effects on the invasibility of a community.     

Comparative social network analysis in a leaf-roosting bat

Even though social network analysis provides an important tool to characterize and compare societies, no studies have used its analytical applications to characterize patterns of sociality in bats. Here I use social network analysis to characterize and compare patterns of sociality between three populations of the leaf-roosting bat Thyroptera tricolor. Sites differed in the density of furled leaves used by T. tricolor for roosting. Finca had more leaves per hectare (77), followed by Ureña (58), and Esquinas (7). The time period over which the probability of association is halved based on fitted models was 1,086 days for Finca, 714 days for Ureña, and 303 days for Esquinas. Finca and Ureña had very similar network topologies, with several small clusters, high-clustering coefficients, short path lengths, low node betweenness, and high network robustness. Social networks at Esquinas were composed of one large cluster and several small isolated ones. Esquinas also had high-clustering coefficients, but path length and node betweenness were high. Network resilience was lower in Esquinas compared to Finca and Ureña. These results show that, unlike many other forest-dwelling bats that switch roosts regularly, T. tricolor does not exhibit a typical fission–fusion social system, and that resource availability seems to affect social networks in this bat. In addition, this study highlights the importance of emigrating individuals in maintaining social cohesion, establishing network connectedness, and determining network robustness.     

Sampling animal association networks with the gambit of the group

Ecologists increasingly use network theory to examine animal association patterns. The gambit of the group (GoG) is a simple and useful assumption for accumulating the data necessary for a network analysis. The gambit of the group implies that each animal in a group is associating with every other individual in that group. Sampling is an important issue for networks in wild populations collected assuming GoG. Due to time, effort, and resource constraints and the difficulty of tracking animals, sampled data are usually a subset of the actual network. Ecologists often use association indexes to calculate the frequency of associations between individuals. These indexes are often transformed by applying a filter to produce a binary network. We explore GoG sampling using model networks. We examine assortment at the level of the group by a single dichotomous trait, along with many other network measures, to examine the effect of different sampling regimes, and choice of filter on the accuracy and precision with which measures are estimated. We find strong support for the use of weighted, rather than filtered, network measures and show that different filters have different effects depending on the nature of the sampling. We make several practical recommendations for ecologists planning GoG sampling.     

Assessing sensitivities of marine areas to stressors based on biological traits

Analysis of the biological traits (e.g., feeding mode and size) that control how organisms interact with their environment has been used to identify environmental drivers of, or impacts on, species and to explain the importance of biodiversity loss. Biological trait analysis (BTA) could also be used within risk-assessment frameworks or in conservation planning if one understands the groups of traits that predict the sensitivity of habitats or communities to specific human activities. Deriving sensitivities from BTA should extend sensitivity predictions to a variety of habitats, especially those in which it would be difficult to conduct experiments (e.g., due to depth or risk to human life) and to scales beyond the norm of most experiments. We used data on epibenthos, collected via video along transects at 27 sites in a relatively pristine region of the seafloor, to determine scales of natural spatial variability of derived sensitivities and the degree to which predictions of sensitivity differed among 3 stressors (extraction of species, sedimentation, and suspended sediments) or were affected by underlying community compositions. We used 3 metrics (weighted abundance, abundance of highly sensitive species, and number of highly sensitive species) to derive sensitivity to these stressors and simulated the ability of these metrics to detect a range of stressor intensities. Regardless of spatial patterns of sensitivities across the sampled area, BTA distinguished differences in sensitivity to different stressors. The BTA also successfully separated differences in community composition from differences in sensitivity to stressors. Conversely, the 3 metrics differed widely in their ability to detect simulated impacts and likely reflect underlying ecological processes, suggesting that use of multiple metrics would be informative for spatial planning and allocating conservation priorities. Our results suggest BTA could be used as a first step in strategic prioritization of protected areas and as an underlying layer for spatial planning.     

Determining the community structure of the coral Seriatopora hystrix from hydrodynamic and genetic networks

The exchange of genetic information between coral reefs through the transport of larvae can be described in terms of networks that capture the linkages between distant populations. A key question arising from these networks is the determination of the highly connected modules (communities). Communities can be defined using genetic similarity or distance statistics between multiple samples but due to limited specimen sampling capacity the boundaries of the communities for the known coral reefs in the seascape remain unresolved. In this study we use the microsatellite composition of individual corals to compare sample populations using a genetic dissimilarity measure (F_ST) which is then used to create a complex network. This network involved sampling 1025 colonies from 22 collection sites and examining 10 microsatellites loci. The links between each sampling site were given a strength that was created from the pair wise F_ST values. The result is an undirected weighted network describing the genetic dissimilarity between each sampled population. From this network we then determined the community structure using a leading eigenvector algorithm within graph theory. However, given the relatively limited sampling conducted, the representation of the regional genetic structure was incomplete. To assist with defining the boundaries of the genetically based communities we also integrated the communities derived from a hydrodynamic and distance based networks. The hydrodynamic network, though more comprehensive, was of smaller spatial extent than our genetic sampling. A Bayesian Belief network was developed to integrate the overlapping communities. The results indicate the genetic population structure of the Great Barrier Reef and provide guidance on where future genetic sampling should take place to complete the genetic diversity mapping.     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

Influence of Forest Fragmentation on Community Structure of Frogs and Lizards in Northeastern Costa Rica

Abstract:  To better understand responses of reptiles and amphibians to forest fragmentation in the lowland Neotropics, we examined community and population structure of frogs and lizards in the fragmented landscape surrounding La Selva Biological Station in the Sarapiquí region of northeastern Costa Rica. We used diurnal quadrats and nocturnal transects to sample frogs and lizards in nine forest fragments (1–7 ha each) and La Selva (1100 ha). Species richness in all fragments combined was 85% of that found in La Selva with comparable sampling effort. Richness varied from 10 to 24 species among forest fragments, compared with 36 species at La Selva. Lizard density was higher and frog density was lower in forest fragments than in La Selva. Community composition varied among sites and by fragment size class, and species occurrence was nested with respect to fragment area. Isolation and habitat variables did not significantly affect species richness, composition, or nestedness. We classified 34% of species as fragmentation sensitive because they were absent or occurred at low densities in fragments. Nevertheless, the relatively high diversity observed in the entire set of fragments indicates that preserving a network of small forest patches may be of considerable conservation value to the amphibians and reptiles of this region.     

Different response of bacterial community to the changes of nutrients and pollutants in sediments from an urban river network

• Bacterial community varied spatially in sediments from the urban river network. • Key environmental factors shaping bacterial community were detected by RDA. • Bacterial co-occurrence networks changed at different levels of nutrient and metal. • Potential indicator species were selected to predict pollution risk in sediment. Microbial communities in sediment are an important indicator linking to environmental pollution in urban river systems. However, how the diversity and structure of bacterial communities in sediments from an urban river network respond to different environmental factors has not been well studied. The goal of this study was to understand the patterns of bacterial communities in sediments from a highly dense urbanized river network in the lower Yangtze River Delta by Illumina MiSeq sequencing. The correlations between bacterial communities, the environmental gradient and geographical distance were analyzed by redundancy analysis (RDA) and network methods. The diversity and richness of bacterial community in sediments increased from upstream to downstream consistently with the accumulation of nutrient in the urban river network. Bacterial community composition and structure showed obvious spatial changes, leading to two distinct groups, which were significantly related to the characteristics of nutrient and heavy metal in sediments. Humic substance, available nitrogen, available phosphorus, Zn, Cu, Hg and As were selected as the key environmental factors shaping the bacterial community in sediments based on RDA. The co-occurrence patterns of bacterial networks showed that positive interaction between bacterial communities increased but the connectivity among bacterial genera and stability of sediment ecosystem reduced under a higher content of nutrient and heavy metal in average. The sensitive and ubiquitous taxa with an overproportional response to key environmental factors were detected as indicator species, which provided a novel method for the prediction of the pollution risk of sediment in an urban river network.     

Multispecies genetic objectives in spatial conservation planning

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear‐cut guidance on how genetic features can be incorporated into conservation‐planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation‐priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected‐area networks that appropriately preserve community‐level evolutionary patterns.