The pairwise approach to analysing species co‐occurrence

The analysis of species co‐occurrence patterns continues to be a main pursuit of ecologists, primarily because the coexistence of species is fundamentally important in evaluating various theories, principles and concepts. Examples include community assembly, equilibrium versus non‐equilibrium organization of communities, resource partitioning and ecological character displacement, the local–regional species diversity relationship, and the metacommunity concept. Traditionally, co‐occurrence has been measured and tested at the level of an entire species presence–absence matrix wherein various algorithms are used to randomize matrices and produce statistical null distributions of metrics that quantify structure in the matrix. This approach implicitly recognizes a presence–absence matrix as having some real ecological identity (e.g. a set of species exhibiting nestedness among a set of islands) in addition to being a unit of statistical analysis. An emerging alternative is to test for non‐random co‐occurrence between paired species. The pairwise approach does not analyse matrix‐level structure and thus views a species pair as the fundamental unit of co‐occurrence. Inferring process from pattern is very difficult in analyses of co‐occurrence; however, the pairwise approach may make this task easier by simplifying the analysis and resulting inferences to associations between paired species.     

From species distributions to meta‐communities

The extent that biotic interactions and dispersal influence species ranges and diversity patterns across scales remains an open question. Answering this question requires framing an analysis on the frontier between species distribution modelling (SDM), which ignores biotic interactions and dispersal limitation, and community ecology, which provides specific predictions on community and meta‐community structure and resulting diversity patterns such as species richness and functional diversity. Using both empirical and simulated datasets, we tested whether predicted occurrences from fine‐resolution SDMs provide good estimates of community structure and diversity patterns at resolutions ranging from a resolution typical of studies within reserves (250 m) to that typical of a regional biodiversity study (5 km). For both datasets, we show that the imprint of biotic interactions and dispersal limitation quickly vanishes when spatial resolution is reduced, which demonstrates the value of SDMs for tracking the imprint of community assembly processes across scales.     

Fire disturbance disrupts co‐occurrence patterns of terrestrial vertebrates in Mediterranean woodlands

Aim This paper uses null model analysis to explore the pattern of species co‐occurrence of terrestrial vertebrate fauna in fire‐prone, mixed evergreen oak woodlands. Location The Erico–Quercion ilicis of the Mediterranean belt (50–800 m a.s.l.) in the Madonie mountain range, a regional park in northern Sicily (37°50′ N, 14°05′ E), Italy. Methods The stratified sampling of vertebrates in a secondary succession of recent burned areas (BA, 1–2 years old), intermediate burned areas (INT, 4–10 years old) and ancient burned areas (CNB, > 50 years old), plus forest fragments left within burned areas (FF, 1–2 years old) permitted the comparison of patterns of species co‐occurrence using a set of separate presence/absence matrices. First, the breeding avifauna derived from standardized point counts was analysed using Stone & Roberts’C‐score, and by a null model algorithm (fixed/equiprobable). Secondly, the analysis was repeated using all vertebrate species recorded in the succession. Results Sixty‐five species were recorded in the 2‐year study period in the four sample treatments. Birds were found to make up the largest component (63%) of the recorded assemblage. The BA treatment had the lowest species richness, followed in order by the small, medium and large FFs, and then by the CNBs. For both analyses (birds and total vertebrates), the C‐scores were quite small and not significantly different from those that could be expected by chance in the BA and INT burned areas; this indicates a random co‐occurrence among vertebrates of those assemblages. Contrariwise, for both analyses in the CNBs, the C‐scores were large and significantly different from the simulated indices, thereby indicating a non‐random co‐occurrence pattern (segregation) of vertebrates in the undisturbed woodlands. In addition, C‐score values for the surviving FFs show a significant aggregation of species. Main conclusions The null model analyses highlighted a new aspect of fire disturbance in Mediterranean woodland ecosystems: the disruption in patterns of co‐occurrence in the terrestrial vertebrate community. Wildfire alters community organization, inducing, for at least 10 years, a random aggregate of species. Communities re‐assemble themselves, showing the occurrence of species segregation at least 50 years after fire.     

Trait hierarchies are stronger than trait dissimilarities in structuring spatial co‐occurrence patterns of common tree species in a subtropical forest

1. The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co‐occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co‐occur either due to environmental filtering or due to competitive exclusion of inferior competitors (hereafter hierarchical competition).
2. We used a fully mapped 50‐ha subtropical forest plot in southern China to explore how pairwise spatial associations between saplings and between adult trees were influenced by trait dissimilarity and hierarchy in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering, and hierarchical competition on species co‐occurrence.
3. We found that trait dissimilarity was generally negatively related to interspecific spatial associations for both saplings and adult trees across spatial scales, meaning that species with similar trait values were more likely to co‐occur and thus supporting environmental filtering or hierarchical competition. We further found that trait hierarchy outweighed trait dissimilarity in structuring pairwise spatial associations, suggesting that hierarchical competition played a more important role in structuring our forest community than environmental filtering across life stages.
4. This study employed a novel method, by offering the integration of pairwise spatial association and trait dissimilarity as well as trait hierarchy, to disentangle the relative importance of multiple assembly mechanisms in structuring co‐occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co‐occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.

     

Species co‐occurrence patterns and dietary resource competition in primates

Diamond (Assembly of species communities. In: Cody ML, Diamond JM, editors. Ecology and evolution of communities. Cambridge: Belknap. p 342–444 ( 1975 )) argued that interspecific competition between species occupying similar niches results in a nonrandom pattern of species distributions. In particular, some species pairs may never be found in the same community due to competitive exclusion. Rigorous analytical methods have been developed to investigate the possible role that interspecific competition has on the evolution of communities. Many studies that have implemented these methods have shown support for Diamond's assembly rules, yet there are numerous exceptions. We build on this previous research by examining the co‐occurrence patterns of primate species in 109 communities from across the world. We used EcoSim to calculate a checkerboard (C) score for each region. The C score provides a measure of the proportion of species pairs that do not co‐occur in a set of communities. High C scores indicate that species are nonrandomly distributed throughout a region, and interspecific competition may be driving patterns of competitive exclusion. We conducted two sets of analyses. One included all primate species per region, and the second analysis assigned each species to one of four dietary guilds: frugivores, folivores, insectivores, and frugivore‐insectivores. Using all species per region, we found significantly high C scores in 9 of 10 regions examined. For frugivores, we found significantly high‐C scores in more than 50% of regions. In contrast, only 23% of regions exhibited significantly high‐C scores for folivores. Our results suggest that communities are nonrandomly structured and may be the result of greater levels of interspecific competition between frugivores compared to folivores. Am J Phys Anthropol, 2010. © 2010 Wiley‐Liss, Inc.     

Ecological correlates of the spatial co‐occurrence of sympatric mammalian carnivores worldwide

The composition of local mammalian carnivore communities has far‐reaching effects on terrestrial ecosystems worldwide. To better understand how carnivore communities are structured, we analysed camera trap data for 108 087 trap days across 12 countries spanning five continents. We estimate local probabilities of co‐occurrence among 768 species pairs from the order Carnivora and evaluate how shared ecological traits correlate with probabilities of co‐occurrence. Within individual study areas, species pairs co‐occurred more frequently than expected at random. Co‐occurrence probabilities were greatest for species pairs that shared ecological traits including similar body size, temporal activity pattern and diet. However, co‐occurrence decreased as compared to other species pairs when the pair included a large‐bodied carnivore. Our results suggest that a combination of shared traits and top‐down regulation by large carnivores shape local carnivore communities globally.     

Testing the link between species interactions and species co‐occurrence in a trophic network

Species interactions are dynamic processes that vary across environmental and ecological contexts, and operate across scale boundaries, making them difficult to quantify. Nevertheless, ecologists are increasingly interested in inferring species interactions from observational data using statistical analyses of their spatial co‐occurrence patterns. Trophic interactions present a particular challenge, as predators and prey may frequently or rarely co‐occur, depending on the spatial or temporal scale of observation. In this study, we investigate the accuracy of inferred interactions among species that both compete and trophically interact. We utilized a long‐term dataset of pond‐breeding amphibian co‐occurrences from Mt Rainier National Park (Washington, USA) and compiled a new dataset of their empirical interactions from the literature. We compared the accuracy of four statistical methods in inferring these known species interactions from spatial associations. We then used the best performing statistical method, the Markov network, to further investigate the sensitivity of interaction inference to spatial scale‐dependence and the presence of predators. We show that co‐occurrence methods are generally inaccurate when estimating trophic interactions. Further the strength and sign of inferred interactions were dependent upon the spatial scale of observation and predator presence influenced the detectability of competitive interactions among prey species. However, co‐occurrence analysis revealed new patterns of spatial association among pairs of species with known interactions. Overall, our study highlights a limiting frontier in co‐occurrence theory and the disconnect between widely implemented methodologies and their ability to accurately infer interactions in trophically‐structured communities.     

Environmental heterogeneity,dispersal mode,and co‐occurrence in stream macroinvertebrates

Both environmental heterogeneity and mode of dispersal may affect species co‐occurrence in metacommunities. Aquatic invertebrates were sampled in 20–30 streams in each of three drainage basins, differing considerably in environmental heterogeneity. Each drainage basin was further divided into two equally sized sets of sites, again differing profoundly in environmental heterogeneity. Benthic invertebrate data were divided into three groups of taxa based on overland dispersal modes: passive dispersers with aquatic adults, passive dispersers with terrestrial winged adults, and active dispersers with terrestrial winged adults. The co‐occurrence of taxa in each dispersal mode group, drainage basin, and heterogeneity site subset was measured using the C‐score and its standardized effect size. The probability of finding high levels of species segregation tended to increase with environmental heterogeneity across the drainage basins. These patterns were, however, contingent on both dispersal mode and drainage basin. It thus appears that environmental heterogeneity and dispersal mode interact in affecting co‐occurrence in metacommunities, with passive dispersers with aquatic adults showing random patterns irrespective of environmental heterogeneity, and active dispersers with terrestrial winged adults showing increasing segregation with increasing environmental heterogeneity.     

Geospatial variation in co‐occurrence networks of nitrifying microbial guilds

Microbial communities transform nitrogen (N) compounds, thereby regulating the availability of N in soil. The N cycle is defined by interacting microbial functional groups, as inorganic N‐products formed in one process are the substrate in one or several other processes. The nitrification pathway is often a two‐step process in which bacterial or archaeal communities oxidize ammonia to nitrite, and bacterial communities further oxidize nitrite to nitrate. Little is known about the significance of interactions between ammonia‐oxidizing bacteria (AOB) and archaea (AOA) and nitrite‐oxidizing bacterial communities (NOB) in determining the spatial variation of overall nitrifier community structure. We hypothesize that nonrandom associations exist between different AO and NOB lineages that, along with edaphic factors, shape field‐scale spatial patterns of nitrifying communities. To address this, we sequenced and quantified the abundance of AOA, AOB, and Nitrospira and Nitrobacter NOB communities across a 44‐hectare site with agricultural fields. The abundance of Nitrobacter communities was significantly associated only with AOB abundance, while that of Nitrospira was correlated to AOA. Network analysis and geostatistical modelling revealed distinct modules of co‐occurring AO and NOB groups occupying disparate areas, with each module dominated by different lineages and associated with different edaphic factors. Local communities were characterized by a high proportion of module‐connecting versus module‐hub nodes, indicating that nitrifier assemblages in these soils are shaped by fluctuating conditions. Overall, our results demonstrate the utility of network analysis in accounting for potential biotic interactions that define the niche space of nitrifying communities at scales compatible to soil management.     

Predictor species: Improving assessments of rare species occurrence by modeling environmental co‐responses

Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co‐occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co‐responses among species. For species from a European peat bog community, our approach consistently performs better than single‐species models and better than conventional multi‐species approaches that include the presence of nontarget species as additional independent variables in regression models. Our approach performs particularly well with rare species and when calibration data are limited. Furthermore, we identify a group of “predictor species” that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices.     

Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways

1. Ecosystems are strongly influenced by land use practices. However, identifying the mechanisms behind these influences is complicated by the many potential pathways (often indirect) between land use and ecosystems and by the long‐lasting effects of past land use. To support ecosystem restoration and conservation efforts, we need to better understand these indirect and lasting effects. 2. We constructed structural equation models (SEM) to evaluate the direct and indirect effects of contemporary (2002) land use (agriculture and development) and change in land use from 1952 to 2002 on present‐day streams (n = 190) in Maryland, U.S.A. Additional variables examined included site location, system size, altitude, per cent sand in soils, riparian condition, habitat quality, stream water NO₃‐N and benthic macroinvertebrate and fish measures of stream condition. Our first SEM (2002 Land Use) included the proportions of contemporary agriculture and development in catchments in the model. The second SEM (Land Use Change) included five measures of land use change (proportion agricultural in both times, developed in both times, agricultural in 1952 and developed in 2002, forested in 1952 and developed in 2002 and agricultural in 1952 and forested in 2002). 3. The data set fit both SEMs well. The 2002 Land Use model explained 71% of variation in NO₃‐N and 55%, 42% and 38% of variation in riffle quality, macroinvertebrate condition and fish condition, respectively. The Land Use Change model explained similar amounts of variation in NO₃‐N (R² = 0.72), riffle quality (R² = 0.57) and macroinvertebrate condition (R² = 0.44) but slightly more variation in fish condition (R² = 0.43). 4. Both models identified pathways through which landscape variables affect stream responses, including negative direct effects of latitude on macroinvertebrate and fish conditions and positive direct and indirect effects of altitude on NO₃‐N, riffle quality and macroinvertebrate and fish conditions. The 2002 Land Use model showed contemporary development and agriculture had positive total effects on NO₃‐N (both through direct pathways); contemporary development had negative effects on macroinvertebrate condition. The Land Use Change model showed that contemporary developed land that was forested in 1952 had no effects on NO₃‐N; current developed land that was developed or agricultural in 1952 showed positive effects on NO₃‐N. Forests that were agricultural in 1952 had negative effects on NO₃‐N, suggesting reduced NO₃‐N export with reforestation. The Land Use Change model also showed negative total effects of all types of contemporary developed land (developed, agricultural or forested in 1952) on benthic condition. Developed land that was forested in 1952 had negative effects on fish condition. Forest sites that were agricultural in 1952 had negative effects on fish and macroinvertebrate conditions, suggesting a long‐term imprint of abandoned agriculture in stream communities. 5. Our analyses (i) identified multiple indirect effects of contemporary land use on streams, (ii) showed that current land uses with different land use histories can exhibit different effects on streams and (iii) demonstrated an imprint of land use lasting >50 years. Knowledge of these indirect and long‐term effects of land use will help to conserve and restore streams.     

Untangling the relationships among regional occupancy,species traits,and niche characteristics in stream invertebrates

The regional occupancy and local abundance of species are affected by various species traits, but their relative effects are poorly understood. We studied the relationships between species traits and occupancy (i.e., proportion of sites occupied) or abundance (i.e., mean local abundance at occupied sites) of stream invertebrates using small‐grained data (i.e., local stream sites) across a large spatial extent (i.e., three drainage basins). We found a significant, yet rather weak, linear relationship between occupancy and abundance. However, occupancy was strongly related to niche position (NP), but it showed a weaker relationship with niche breadth (NB). Abundance was at best weakly related to these explanatory niche‐based variables. Biological traits, including feeding modes, habit traits, dispersal modes and body size classes, were generally less important in accounting for variation in occupancy and abundance. Our findings showed that the regional occupancy of stream invertebrate species is mostly related to niche characteristics, in particular, NP. However, the effects of NB on occupancy were affected by the measure itself. We conclude that niche characteristics determine the regional occupancy of species at relatively large spatial extents, suggesting that species distributions are determined by environmental variation among sites.     

Spatial co‐localisation of extreme weather events: a clear and present danger

Extreme weather events have become a dominant feature of the narrative surrounding changes in global climate with large impacts on ecosystem stability, functioning and resilience; however, understanding of their risk of co‐occurrence at the regional scale is lacking. Based on the UK Met Office’s long‐term temperature and rainfall records, we present the first evidence demonstrating significant increases in the magnitude, direction of change and spatial co‐localisation of extreme weather events since 1961. Combining this new understanding with land‐use data sets allowed us to assess the likely consequences on future agricultural production and conservation priority areas. All land‐uses are impacted by the increasing risk of at least one extreme event and conservation areas were identified as the hotspots of risk for the co‐occurrence of multiple event types. Our findings provide a basis to regionally guide land‐use optimisation, land management practices and regulatory actions preserving ecosystem services against multiple climate threats.     

Importance of scale,land‐use,and stream network properties for riparian plant communities along an urban gradient

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