The frugivory network properties of a simplified ecosystem: Birds and plants in a Neotropical periurban park

Frugivory networks exhibit a set of properties characterized by a number of network theory‐derived metrics. Their structures often form deterministic patterns that can be explained by the functional roles of interacting species. Although we know lots about how these networks are organized when ecosystems are in a complete, functional condition, we know much less about how incomplete and simplified networks (such as those found in urban and periurban parks) are organized, which features are maintained, which ones are not, and why. In this paper, we examine the properties of a network between frugivorous birds and plants in a small Neotropical periurban park. We found a frugivory network composed of 29 species of birds and 23 of plants. The main roles in this network are played by four species of generalist birds (three resident, one migratory: Myiozetetes similis, Turdus grayi, Chlorospingus flavopectus, and Dumetella carolinensis) and three species of plants (one exotic, two early successional: Phoenix canariensis, Phoradendron sp., and Witheringia stramoniifolia). When compared to reference data from other locations in the Neotropics, species richness is low, one important network‐level metric is maintained (modularity) whereas another one is not (nestedness). Nestedness, a metric associated with network specialists, is a feature this network lacks. Species‐level metrics such as degree, species strength, and module roles, are not maintained. Our work supports modularity as the most pervasive network‐level metric of altered habitats. From a successional point of view, our results suggest that properties revealed by species‐level indices may be developed at a later time, lagging the acquisition of structural elements.     

Population fluctuations affect inference in ecological networks of multi‐species interactions

Local abundance and population fluctuations are key factors affecting the realized interaction frequencies in biotic interactions, but they are commonly ignored when network metrics are calculated over aggregated sets of observations. Here we studied how abundance fluctuations (i.e. demographic and stochastic population dynamics in one of the trophic levels) may affect derived network‐level inferences in bipartite ecological networks. Variation at both the species and network level in network indices (d’, Dependence, Fisher's alpha diversity for both levels, H₂’, weighted NODF) were strongly correlated with the extent of abundance fluctuations, with a strong effect of environmental stochasticity on all indices except NODF; this was the only index for which considerable variation was caused by varying carrying capacities among species. Binary connectance, in turn, does not take interaction frequency (and thus abundance) into account and was only influenced by abundance fluctuations at low population sizes if this led to non‐occurrence of ‘true’ interactions. Overall, abundance and population dynamics are likely to play an important role in determining what is commonly observed and summarized into ecological networks. We suggest that ecological network inference should account for underlying population dynamics and uncertainty in what is observed as interaction frequencies, modelling mechanisms at operative organisational levels below the network rather than using aggregated data of observations. Modelling population dynamics may be a valuable tool in this field to conceptualize and tease apart different sources of variation and express uncertainty in our inference from small samples.     

landscapemetrics: an open‐source R tool to calculate landscape metrics

Quantifying landscape characteristics and linking them to ecological processes is one of the central goals of landscape ecology. Landscape metrics are a widely used tool for the analysis of patch‐based, discrete land‐cover classes. Existing software to calculate landscape metrics has several constraints, such as being limited to a single platform, not being open‐source or involving a complicated integration into large workflows. We present landscapemetrics, an open‐source R package that overcomes many constraints of existing landscape metric software. The package includes an extensive collection of commonly used landscape metrics in a tidy workflow. To facilitate the integration into large workflows, landscapemetrics is based on a well‐established spatial framework in R. This allows pre‐processing of land‐cover maps or further statistical analysis without importing and exporting the data from and to different software environments. Additionally, the package provides many utility functions to visualize, extract, and sample landscape metrics. Lastly, we provide building‐blocks to motivate the development and integration of new metrics in the future. We demonstrate the usage and advantages of landscapemetrics by analysing the influence of different sampling schemes on the estimation of landscape metrics. In so doing, we demonstrate the many advantages of the package, especially its easy integration into large workflows. These new developments should help with the integration of landscape analysis in ecological research, given that ecologists are increasingly using R for the statistical analysis, modelling and visualization of spatial data.     

Phylogenetic diversity and the conservation biogeography of African primates

Aim Phylogenetics has an important role in conservation biogeography. However, there are few data on the phylogenetic diversity of African primates. The phylogenetic diversity (PD) of a species is a measure of its taxonomic distinctness and can be estimated by looking at the phylogenetic relationships among taxa. Species‐specific metrics on PD can then be used to determine conservation priorities at various biogeographical scales. We used PD metrics to rank 55 African primate species according to their conservation priorities at the country level and within six African biogeographical regions. We also addressed the following question: are there differences in conservation rankings between the IUCN Red List and our PD metrics? Location Africa. Methods We created a consensus phylogeny for all African primate clades based on genetic studies. Analyses of species distributions were determined using presence/absence scores at two levels: country and biogeographical region. A node‐based method that standardizes for widespread taxa and endemicity was used to calculate PD indices. Hierarchical cluster analysis was used to convert one of the standardized, phylogenetic indices into three clusters that could be ranked and compared with the main IUCN conservation rankings of endangered, vulnerable, and lower risk. Results At the country and region levels, the top‐priority species in terms of PD are Pan paniscus, Macaca sylvanus, Arctocebus calabarensis, Gorilla beringei, Arctocebus aureus, Allenopithecus nigroviridis, Gorilla gorilla, Procolobus verus, Cercopithecus solatus, Cercocebus galeritus, Colobus angolensis, Theropithecus gelada, Galagoides zanzibaricus, Galagoides granti, and Procolobus (Piliocolobus) badius. Geographic rankings were highest for the Democratic Republic of the Congo (country level) and Central Africa (region level). Although there were no overall differences between IUCN conservation ranks and the PD rankings, there were significant differences between the two systems for vulnerable and endangered primate taxa. Main conclusions There are few ecological and behavioural data on populations of some of the African primates that represent the highest levels of phylogenetic diversity. Studies of primate taxa with high PD rankings should focus on identifying sites suitable for intensive studies of population densities, feeding ecology, and reproductive behaviour. We suggest that PD metrics can serve as an important, complementary data set in the IUCN ranking system for primates.     

Cross‐scale effects of structural and functional connectivity in pond networks on amphibian distribution in agricultural landscapes

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Dispersal ability and habitat requirements determine landscape‐level genetic patterns in desert aquatic insects

Species occupying the same geographic range can exhibit remarkably different population structures across the landscape, ranging from highly diversified to panmictic. Given limitations on collecting population‐level data for large numbers of species, ecologists seek to identify proximate organismal traits—such as dispersal ability, habitat preference and life history—that are strong predictors of realized population structure. We examined how dispersal ability and habitat structure affect the regional balance of gene flow and genetic drift within three aquatic insects that represent the range of dispersal abilities and habitat requirements observed in desert stream insect communities. For each species, we tested for linear relationships between genetic distances and geographic distances using Euclidean and landscape‐based metrics of resistance. We found that the moderate‐disperser Mesocapnia arizonensis (Plecoptera: Capniidae) has a strong isolation‐by‐distance pattern, suggesting migration–drift equilibrium. By contrast, population structure in the flightless Abedus herberti (Hemiptera: Belostomatidae) is influenced by genetic drift, while gene flow is the dominant force in the strong‐flying Boreonectes aequinoctialis (Coleoptera: Dytiscidae). The best‐fitting landscape model for M. arizonensis was based on Euclidean distance. Analyses also identified a strong spatial scale‐dependence, where landscape genetic methods only performed well for species that were intermediate in dispersal ability. Our results highlight the fact that when either gene flow or genetic drift dominates in shaping population structure, no detectable relationship between genetic and geographic distances is expected at certain spatial scales. This study provides insight into how gene flow and drift interact at the regional scale for these insects as well as the organisms that share similar habitats and dispersal abilities.     

Compositional turnover in host and parasite communities does not change network structure

Decreasing similarity between ecological communities with increasing geographic distance (i.e. distance‐decay) is a common biogeographical observation in free‐living communities, and a slightly less common observation for parasite communities. Ecological networks of interacting species may adhere to a similar pattern of decreasing interaction similarity with increasing geographic distance, especially if species interactions are maintained across space. We extend this further, examining if host–parasite networks – independent of host and parasite species identities – become more structurally dissimilar with increasing geographic distance. Utilizing a global database of helminth parasite occurrence records, we find evidence for distance‐decay relationships in host and parasite communities at both regional and global scales, but fail to detect similar relationships in network structural similarity. Host and parasite community similarity were strongly related, and both decayed rapidly with increasing geographic distance, typically resulting in complete dissimilarity after approximately 2500 km. Our failure to detect a decay in network structural similarity suggests the possibility that different host and parasite species are filling the same functional roles in interaction networks, or that variation in network similarity may be better explained by other geographic variables or aspects of host and parasite ecology.     

Modelling geographic patterns of population density of the white‐tailed deer in central Mexico by implementing ecological niche theory

Conservation and management of species require basic knowledge on their geographic distribution and abundance. Here, we propose a novel approach, based on the theory of the ecological niche, to model the spatial patterns of the white‐tailed deer Odocoileus virginianus population density in two regions of central Mexico (Balsas Basin and Tehuacán‐Cuicatlán Valley). We used an ecological niche model to generate binary geographic distribution maps of the white‐tailed deer in each region based on occurrence data and a set of environmental variables. Then, the centroid of the distributions was calculated in ecological space (niche centroid) and the multidimensional Euclidian ecological distance of each pixel to the niche centroid was estimated. Finally, for each region the distance to the niche centroid (DNC) was regressed against 14 independent occurrence points in each site containing white‐tailed deer density information to determine the function describing the DNC‐density relationship, which was used to generate maps describing the distribution of white‐tailed deer density. Our results indicated an inverse DNC‐density relationship in both regions (Balsas Basin: r² = 0.90 and Tehuacán‐Cuicatlán: r² = 0.76) that was validated via bootstrapping resulting in a predicting capacity of near 62% for Balsas Basin and 65% for Tehuacán‐Cuicatlán Valley. Our results suggest that the distance to the niche centroid method is a robust, science‐based correlative approach that resulted useful to predict the population density of the white‐tailed deer in a spatially explicit fashion. The proposed approach is suitable for predicting the distribution of density for white‐tailed deer for which occurrence data with accompanying density information exists, but relative abundance can also be estimated when no abundance data are available.     

Local population genetic structure of the montane caddisfly Drusus discolor is driven by overland dispersal and spatial scaling

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Quantitative metrics of overlaps in Grinnellian niches: advances and possible drawbacks

Aim Studies of environmental niche shift/niche conservatism that are based on species distribution modelling require a quantification of niche purity and potential overlap. Although various metrics have been proposed for this task, no comparisons of their performance are available yet that express the linearity of range shifts and error‐proneness. Herein, we assess the performance of six niche overlap metrics using three sister pairs of plethodontid salamanders as well as artificial species to test for linearity of overlap curves, impacts of varying potential distribution sizes and study area sizes. Location North America, artificial environments. Methods Species distribution models for the salamanders were performed with Maxent , and artificial species were created in the R environment. Potential distributions of species with varying range sizes and extents of the study area were compared using the Bray–Curtis distance BC, Schoener's D, two different modifications of the Hellinger distance I_mod, I_cor, Pianka's O and Horn's R. Niche overlaps in ecological space were compared using linear discriminant analyses based on principal components. Results Simulations of niche overlaps revealed strong variations in the performance of the niche overlap metrics. In artificial species, BC and D performed best, followed by O, R and I_cor, but the modified Hellinger distance I_mod showed a nonlinear slope and a truncated range. Furthermore, the simulations suggest that, in proportionally small potential distributions on large grids, an inclusion of a high proportion of grid cells with low occurrence probabilities representing background noise may bias assessments of niche overlaps. Main conclusions Both the salamander examples and simulations suggest that Schoener's D and the Bray–Curtis distance BC are best suited to compute niche overlaps from potential distributions derived from species distribution models. However, like all analysed metrics, both D and BC are seriously affected by the inclusion of high numbers of grid cells where the species are probably absent, i.e. with low occurrence probabilities. Therefore, pre‐processing to eliminate background noise in the potential distribution grids is highly recommended.     

Its all about connections: hubs and invasion in habitat networks

During the early stages of invasion, the interaction between the features of the invaded landscape, notably its spatial structure, and the internal dynamics of an introduced population has a crucial impact on establishment and spread. By approximating introduction areas as networks of patches linked by dispersal, we characterised their spatial structure with specific metrics and tested their impact on two essential steps of the invasion process: establishment and spread. By combining simulations with experimental introductions of Trichogramma chilonis (Hymenoptera: Trichogrammatidae) in artificial laboratory microcosms, we demonstrated that spread was hindered by clusters and accelerated by hubs but was also affected by small‐population mechanisms prevalent for invasions, such as Allee effects. Establishment was also affected by demographic mechanisms, in interaction with network metrics. These results highlight the importance of considering the demography of invaders as well as the structure of the invaded area to predict the outcome of invasions.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Functional Roles of Centridini Oil Bees and Malpighiaceae Oil Flowers in Biome‐wide Pollination Networks

Interactions between oil‐collecting bees and oil‐producing flowers are a very specialized mutualism, whose natural history is well known at the organism and population levels. In this study, we assessed these interactions at the biome level with a network approach, and hypothesized that widespread bee and plant species would occupy different ecological functional roles (Eltonian niches) in different biomes. Furthermore, we expected the most important functional roles in each network to be occupied more frequently by Byrsonima oil flowers and Centris oil bees, which share the longest coevolutionary history in the Neotropics. By compiling data from 40 articles on oil flower interactions within the Malpighiaceae family, we built six networks for different Brazilian biomes. We assessed the ecological functional role of each species in pollination networks of oil flowers through the metric known as ‘network functional role’. Although 90 percent of the species occupied peripheral roles in each network, some were found to occupy highly central roles. Oil flowers of the genera Byrsonima and Banisteriopsis and oil bees of the genera Centris and Epicharis were the most important species in all networks, as they made a disproportionally high number of interactions (hubs), or helped bind together different modules (connectors). Our findings suggest that functional roles vary geographically and seem to be affected by local conditions in different biomes. Furthermore, coevolutionary history seems to play an important role in determining functional roles in oil flower networks, although other factors are probably also important, especially the degree of specialization in this kind of interaction.     

Opposed latitudinal patterns of network‐derived and dietary specialization in avian plant–frugivore interaction systems

Latitudinal patterns of biodiversity have been studied for centuries, but it is only during the last decades that species interaction networks have been used to examine the proposed latitudinal gradient of biotic specialization. These studies have given idiosyncratic results, which may either be because of genuine biological differences between systems, different concepts and scales used to quantify biotic specialization or because the methodological approaches used to compare interaction networks were inappropriate. Here we carefully examine the latitudinal specialization gradient using a global dataset of avian plant–frugivore assemblages and interaction networks. In particular, we test whether network‐derived specialization patterns differ from patterns based on assemblage‐level information on avian dietary preferences on specific food types. We found that network‐derived measures of specialization (complementary specialization H₂′ and < d’>, modularity Q) increased with latitude, i.e. frugivorous birds divide the niche of fruiting plants most finely at high latitudes where they also formed more modular interaction networks than at tropical latitudes. However, the strength and significance of the relationship between specialization metrics and latitude was influenced by the methodological approach. On the other hand, assemblage‐level information on avian specialization on fruit diet (i.e. the proportion of obligate frugivorous bird species feeding primarily on fruit) revealed an opposed latitudinal pattern as more bird species were specialized on fruit diet in tropical than in temperate assemblages. This difference in the latitudinal specialization gradient reflects that obligate frugivores require a high diversity of fruit plants, as observed in tropical systems, and fulfil more generalized roles in plant–frugivore networks than bird species feeding on different food types. Future research should focus on revealing the underlying ecological, historical and evolutionary mechanisms shaping these patterns. Our results highlight the necessity of comparing different scales of biotic specialization for a better understanding of geographical patterns of specialization in resource–consumer interactions.     

The temporal dimension in individual‐based plant pollination networks

The pollination success of animal‐pollinated plants depends on the temporal coupling between flowering schedules and pollinator availability. Within a population, individual plants exhibiting disparate flowering schedules will be exposed to different pollinators when the latter exhibit temporal turnover. The temporal overlap between individual plants and pollinators will result in a turnover of interactions, which can be analyzed through a network approach. We have explored the temporal dynamics of individual‐based plant networks resulting from pairwise similarities in pollinator composition. During two flowering seasons, we surveyed the phenology and pollinator fauna of the individual plants from a population of Erysimum mediohispanicum (Brassicaceae). We analyzed the topology of these networks by means of their modularity, clustering, and core–periphery structure. These metrics are related to network functional properties such as cohesion, transitivity and centralization respectively. Afterwards, we analyzed the influence of each pollinator functional group on network topology. We found that network topology varied widely over time as a consequence of the differences in plant phenology and the idiosyncratic and contextual effect of pollinators. When integrating all temporary networks, the network became cohesive (non modular), transitive (locally clusterized), and centralized (core–periphery topology). These topologies could entail important consequences for plant reproduction. Our results highlight the importance of considering the entire flowering season and the necessity of making comprehensive temporal sampling when trying to build reliable interaction networks.     

Phylogeography of the cold‐water barnacle Chthamalus challengeri in the north‐western Pacific: effect of past population expansion and contemporary gene flow

Aim Phylogeographical patterns of marine organisms in the north‐western Pacific are shaped by the interaction of past sea‐level fluctuations during glacial maxima and present‐day gene flow. This study examines whether observed population differentiation in the barnacle Chthamalus challengeri, which is endemic to the north‐western Pacific, can be explained by the interactions between historical glacial events and patterns of contemporary gene flow. Location Eleven locations in the north‐western Pacific. Methods Partial sequences of mitochondrial cytochrome c oxidase subunit I (COI), 12S, 16S and nuclear internal transcribed spacer 1 (ITS1) were obtained from 312 individuals. Parsimony haplotype networks and analysis of molecular variance (AMOVA) were used to determine whether the observed genetic structure corresponds to marine provinces (Kuroshio Current and China Sea Coastal Provinces), zoogeographical zones (oriental and Japan warm‐temperate zones) and/or potential refugial areas (Sea of Japan and East China Sea) in the north‐western Pacific. Neutrality tests, mismatch distribution analysis and Bayesian skyline plots were used to infer the demographic history of C. challengeri. Results In total, 312, 117, 182 and 250 sequences were obtained for COI, 12S, 16S and ITS1, respectively. A panmictic population was revealed, which did not conform to the ‘isolation by distance’ model. None of the a priori population groupings based on marine provinces, zoogeographical zones or potential refugial areas was associated with observed genetic patterns. Significant negative values from neutrality tests and the unimodal mismatch distribution and expansion patterns in Bayesian skyline plots for the COI and 16S data sets indicate a population expansion in the mid‐Pleistocene (c. 200 ka). Information from the fossil record suggests that there has been a northward range shift of this species from the East China Sea or the Palaeo‐Pacific coast of Japan to the Sea of Japan since the mid‐Pleistocene. Main conclusions Chthamalus challengeri has experienced a population expansion and range shift since the mid‐Pleistocene. The observed lack of population differentiation can be explained by this past population expansion and present‐day wide‐scale larval dispersal (owing to the long planktonic larval duration) across marine provinces, which have led to the successful establishment of the species in different zoogeographical zones and habitats.     

The number of breeders explains genetic connectivity in an endangered bird

Connectivity is central to ecology and evolution as it focuses on the movement of individuals or genes across landscapes. Genetic connectivity approaches aim to understand gene flow but often estimate it indirectly based on metrics of genetic differentiation, which can also be affected by other evolutionary forces such as genetic drift. Gene flow and genetic drift are driven by separate ecological mechanisms with potentially differing effects on genetic differentiation and interpretations of genetic connectivity. The ecological mechanisms contributing to gene flow and genetic drift are primarily effective dispersal, or movement followed by successful reproduction, and the number of breeders in a local population, N_b, respectively. Yet, rarely are these ecological mechanisms and genetic connectivity measured simultaneously across landscapes. We examine the roles of effective dispersal and N_b on genetic connectivity across the entire range of the endangered snail kite (Rostrhamus sociabilis plumbeus), between 2006–2015. We find that both N_b and effective dispersal are important predictors of genetic connectivity across this landscape, but that N_b has a 3 × stronger effect on genetic connectivity. Furthermore, N_b is positively correlated with heterozygosity and allelic richness within patches, suggesting a potentially important role of genetic drift, in addition to gene flow, on genetic connectivity. These results emphasize that conservation efforts should focus on not only between‐patch processes of movement but also within‐patch processes regarding habitat quality and local population size for increasing genetic connectivity.     

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Seasonal turnover in plant and floral visitor communities changes the structure of the network of interactions they are involved in. Despite the dynamic nature of plant–visitor networks, a usual procedure is to pool year‐round interaction data into a single network which may result in a biased depiction of the real structure of the interaction network. The annual temporal dynamics and the effect of merging monthly data have previously been described for qualitative data (i.e. describing the occurrence of interactions) alone, while its quantitative aspect (i.e. the actual frequency with which interactions occur) remain little explored. For this, we built a set of 12 monthly networks describing year‐round plant–floral visitor interactions in a 30‐hectare planted forest and its adjacent agricultural landscape at Bahauddin Zakariya University Multan, Pakistan. A total of 80 plant and 162 insect species, which engaged in 1573 unique interactions, were recorded. Most network properties (particularly the number of plants, visitors and unique interactions) varied markedly during the year. Data aggregation showed that while animal species, plant species, unique interaction, weighted nestedness, interaction diversity and robustness increased, connectance and specialization decreased. The only metric which seemed relatively unaffected by data pooling was interaction evenness. In general, quantitative metrics were relatively less affected by temporal data aggregation than qualitative ones. Avoiding data aggregation not only gives a more realistic depiction of the dynamic nature of plant–visitor community networks, but also avoids biasing network metrics and, consequently, their expected response to disturbances such as the loss of species.