Species Co-occurrence Patterns Research Articles

The diversity of within-community plant species combinations: A new tool for assessing changes in forests and guiding protection actions

Biodiversity is changing rapidly, and ecologists use various measures to monitor and conserve it, but not all are equally effective. In the European temperate forests, ecologists are tasked with assessing the impact of global changes on plant species richness; however, this fails at capturing vital information about plant interactions. Using a chronosequence of beech forest stands, spanning 600 years of growth, we demonstrate the application of a different measure of diversity compared to classical species richness in the understorey. This measure, called compositional diversity (CD), considers the number of species combinations and their relative frequency within a community. The response of both classical species richness and CD along with succession, corresponded with our expectations based on ecological theory’s U-shape prediction of diversity along the successional gradient. However, after 300 years, there was a significant decoupling between the two measures’ responses. While species richness remained low and constant across old-growth and primeval forests, CD peaked in primeval forests, implying that the same number of late-successional species generated more diverse assemblages. This new information emphasises the need to protect old-growth and primeval forests not only to conserve species richness but also to preserve their unique network of species co-occurrence patterns – a factor not well represented by the classical species richness measure.

Intraspecific alternative phenotypes contribute to variation in species' strategies for growth.

Ecologists have historically sought to identify the mechanisms underlying the maintenance of local species diversity. High-dimensional trait-based relationships, such as alternative phenotypes, have been hypothesized as important for maintaining species diversity such that phenotypically dissimilar individuals compete less for resources but have similar performance in a given environment. The presence of alternative phenotypes has primarily been investigated at the community level, despite the importance of intraspecific variation to diversity maintenance. The aims of this research are to (1) determine the presence or absence of intraspecific alternative phenotypes in three species of tropical tree seedlings, (2) investigate if these different species use the same alternative phenotypes for growth success, and (3) evaluate how findings align with species co-occurrence patterns. We model species-specific relative growth rate with individual-level measurements of leaf mass per area (LMA) and root mass fraction (RMF), environmental data, and their interactions. We find that two of the three species have intraspecific alternative phenotypes, with individuals within species having different functional forms leading to similar growth. Interestingly, individuals within these species use the same trait combinations, high LMA low RMF and low LMA high RMF, in high soil nutrient environments to acquire resources for higher growth. This similarity among species in intraspecific alternative phenotypes and variables that contribute most to growth may lead to their negative spatial co-occurrence. Overall, we find that multiple traits or interactions between traits and the environment drive species-specific strategies for growth, but that individuals within species leverage this multi-dimensionality in different ways for growth success.

Experimental evidence that competition strength scales with ecological similarity: a case study using Anolis lizards.

Interspecific competition is widely considered a powerful process underlying species coexistence and ecological community structure. Although coexistence theory predicts stronger competition between more ecologically similar species, empirical support has largely relied on inferring competition from patterns of species co-occurrence. Coexistence theory also posits that species can only coexist when individuals compete more with conspecifics than with other species, however, few field studies-particularly in reptiles-have simultaneously estimated the strength of both intra- and interspecific competition among co-occurring species. Using an array of 12 experimental plots, we manipulated species presence and population size by plot of three native Anolis lizard species to empirically estimate the strength of competition on one anole species driven by two other species of varying ecological similarity. We observed that the strength of competition-as determined by relative growth rates and gravidity-was highly predictable and correlated to ecological similarity. Interspecific competition was strongest among species of highest ecological similarity, and intraspecific competition-induced by the addition or removal of conspecifics-was consistently the most intense. By employing direct experimental manipulations, our study provides an empirical investigation of the strength of competition as it relates to ecological similarity.

Environmental variables influence patterns of mammal co-occurrence following introduced predator control.

Co-occurring species often overlap in their use of resources and can interact in complex ways. However, shifts in environmental conditions or resource availability can lead to changes in patterns of species co-occurrence, which may be exacerbated by global escalation of human disturbances to ecosystems, including conservation-directed interventions. We investigated the relative abundance and co-occurrence of two naturally sympatric mammal species following two forms of environmental disturbance: wildfire and introduced predator control. Using 14 years of abundance data from repeat surveys at long-term monitoring sites in south-eastern Australia, we examined the association between a marsupial, the common brushtail possum Trichosurus vulpecula, and a co-occurring native rodent, the bush rat Rattus fuscipes. We asked: In a fox-controlled environment, are the abundances of common brushtail possums and bush rats affected by environmental disturbance and each other's presence? Using Bayesian regression models, we tested hypotheses that the abundance of each species would vary with changes in environmental and disturbance variables, and that the negative association between bush rats and common brushtail possums was stronger than the association between bush rats and disturbance. Our analyses revealed that bush rat abundance varied greatly in relation to environmental and disturbance variables, whereas common brushtail possums showed relatively limited variation in response to the same variables. There was a negative association between common brushtail possums and bush rats, but this association was weaker than the initial decline and subsequent recovery of bush rats in response to wildfires. Using co-occurrence analysis, we can infer negative relationships in abundance between co-occurring species, but to understand the impacts of such associations, and plan appropriate conservation measures, we require more information on interactions between the species and environmental variables. Co-occurrence can be a powerful and novel method to diagnose threats to communities and understand changes in ecosystem dynamics.

Power laws in species' biotic interaction networks can be inferred from co-occurrence data.

Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species' biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.

Can fish species co-occurrence patterns be predicted by their trait dissimilarities?

Trait-based analyses have been successful in determining and predicting species association outcomes in diverse communities. Most studies have limited the scope of this approach to the biotic responses of a small number of species or geographical regions. We focused on determining whether three biologically relevant traits (body size, temperature preference and trophic level) influence the patterns of co-occurrence between multiple species. We used fish species presence/absence from 9204 lakes in Ontario, Canada, to obtain effect sizes of 2001 species-pair co-occurrence values, using a null model approach. Euclidean distances between each species-pair were calculated for each of the three traits selected. Multiple regression models and randomization tests were used to determine the direction and significance of the relationship of each trait with the observed co-occurrence values. The results show that species temperature preference was significantly related to co-occurrence patterns, indicating the effect of environmental filtering. Trophic level was significantly related to co-occurrence values for both linear and quadratic terms, suggesting that segregation between species is driven by large differences in this trait (predation effects). Unexpectedly, body size was not significantly related to the observed co-occurrence patterns. We provide a new approach to test relationships between species assemblages and trait conditions.

A congeneric and non-randomly associated pair of larval trematodes dominates the assemblage of co-infecting parasites in fathead minnows (Pimephales promelas).

Individual hosts are often co-infected with multiple parasite species. Evidence from theoretical and empirical studies supports the idea that co-occurring parasites can impact each other and their hosts via synergistic or antagonistic interactions. The fundamental aim of understanding the consequences of co-infection to hosts and parasites requires an understanding of patterns of species co-occurrence within samples of hosts. We censused parasite assemblages in 755 adult, male fathead minnows collected from 7 lakes/ponds in southern Alberta, Canada between 2018 and 2020. Fifteen species of endoparasites infected fathead minnows, 98% of which were co-infected with between 2 and 9 parasite species (mean species richness: 4.4 ± 1.4). Non-random pairwise associations were detected within the overall parasite community. There were particularly strong, positive associations in the occurrences and intensities of the 2 congeneric larval trematodes Ornithodiplostomum sp. and Ornithodiplostomum ptychocheilus that comprised >96% of the 100 000+ parasites counted in the total sample of minnows. Furthermore, the occurrence of Ornithodiplostomum sp. was a strong predictor of the occurrence of O. ptychocheilus, and vice versa. Positive covariation in the intensities of these 2 dominants likely arises from their shared use of physid snails as first intermediate hosts in these waterbodies. These 2 species represent a predictable and non-random component within the complex assemblage of parasites of fathead minnows in this region.

Probabilistic approaches for investigating species co-occurrence from presence-absence maps.

In this research, we propose probabilistic approaches to identify pairwise patterns of species co-occurrence by using presence-absence maps only. In particular, the two-by-two contingency table constructed from a presence-absence map of two species would be sufficient to compute the test statistics and perform the statistical tests proposed in this article. Some previous studies have investigated species co-occurrence through incidence data of different survey sites. We focus on using presence-absence maps for a specific study plot instead. The proposed methods are assessed by a thorough simulation study. A Chi-squared test is used to determine whether the distributions of two species are independent. If the null hypothesis of independence is rejected, the Chi-squared method can not distinguish positive or negative association between two species. We propose six different approaches based on either the binomial or Poisson distribution to obtain p-values for testing the positive (or negative) association between two species. When we test to investigate a positive (or negative) association, if the p-value is below the predetermined level of significance, then we have enough evidence to support that the two species are positively (or negatively) associated. A simulation study is conducted to demonstrate the type-I errors and the testing powers of our approaches. The probabilistic approach proposed by Veech (2013) is served as a benchmark for comparison. The results show that the type-I error of the Chi-squared test is close to the significance level when the presence rate is between 40% and 80%. For extremely low or high presence rate data, one of our approaches outperforms Veech (2013)'s in terms of the testing power and type-I error rate. The proposed methods are applied to a tree data of Barro Colorado Island in Panama and a tree data of Lansing Woods in USA. Both positive and negative associations are found among some species in these two real data.

Mycobiota profile of oral fungal infections in head and neck cancer patients receiving radiotherapy: A 6-year retrospective MALDI-TOF mass spectrometry study

ObjectivesHead and neck cancer (HNC) impairs patient immunity and increases susceptibility to oral fungal infections (OFIs). Effectively treating such infections requires accurate identification of the causative pathogens. This study aimed to characterize the mycobiota profile of OFIs in HNC patients undergoing radiation treatment (RT). Materials and methodsA 6-year retrospective analysis of oral mucosal samples from HNC patients with a history of RT and OFIs between 2014 and 2019 was conducted using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) profiling. Samples from the Clinical Microbiology Laboratory at Karolinska University Hospital were evaluated for mycobiota diversity and species co-occurrence patterns in the ongoing-RT and post-RT groups. ResultsA total of 190 oral fungi (88% Candida, 5% Pichia) were isolated from 162 HNC patients receiving RT. In the ongoing-RT group, the emergent non-albicans Candida (NAC) species; F. solani and C. jadinii, were detected for the first time. The dominant pathogens in both ongoing and post-RT groups were C. albicans, C. glabrata, P. kudriavzevii, C. parapsilosis, and C. tropicalis, as shown by Venn analysis. Network analysis revealed greater fungi diversity and multi-species co-occurrence in the ongoing-RT group. C. albicans commonly co-occurred with C. glabrata in both ongoing-RT (21%) and post-RT groups (30%). ConclusionMALDI-TOF MS identified a wide range of oral fungal species in HNC patients receiving RT. While C. albicans remains the most prevalent OFIs pathogen, multi-species co-occurrence and novel NACs were noted. Understanding the ecological interactions among these causative pathogens could significantly advance the development of effective therapeutics for treating OFIs in HNC patients.

Ecological signals of arctic plant-microbe associations are consistent across eDNA and vegetation surveys

Understanding how different taxa respond to abiotic characteristics of the environment is of key interest for understanding the assembly of communities. Yet, whether eDNA data will suffice to accurately capture environmental imprints has been the topic of some debate. In this study, we characterised patterns of species occurrences and co-occurrences in Zackenberg in northeast Greenland using environmental DNA. To explore the potential for extracting ecological signals from eDNA data alone, we compared two approaches (visual vegetation surveys and soil eDNA metabarcoding) to describing plant communities and their responses to abiotic conditions. We then examined plant associations with microbes using a joint species distribution model. We found that most (68%) of plant genera were detectable by both vegetation surveys and eDNA signatures. Species-specific occurrence data revealed how plants, bacteria and fungi responded to their abiotic environment – with plants, bacteria and fungi all responding similarly to soil moisture. Nonetheless, a large proportion of fungi decreased in occurrences with increasing soil temperature. Regarding biotic associations, the nature and proportion of the plant-microbe associations detected were consistent between plant data identified via vegetation surveys and eDNA. Of pairs of plants and microbe genera showing statistically supported associations (while accounting for joint responses to the environment), plants and bacteria mainly showed negative associations, whereas plants and fungi mainly showed positive associations. Ample ecological signals detected by both vegetation surveys and by eDNA-based methods and a general correspondence in biotic associations inferred by both methods, suggested that purely eDNA-based approaches constitute a promising and easily applicable tool for studying plant-soil microbial associations in the Arctic and elsewhere.

Quantifying the overall effect of biotic interactions on species distributions along environmental gradients

Separating environmental effects from those of interspecific interactions on species distributions has always been a central objective of community ecology. Despite years of effort in analysing patterns of species co-occurrences and the developments of sophisticated tools, we are still unable to address this major objective. A key reason is that the wealth of ecological knowledge is not sufficiently harnessed in current statistical models, notably the knowledge on interspecific interactions.Here, we develop ELGRIN, a statistical model that simultaneously combines knowledge on interspecific interactions (i.e, the metanetwork), environmental data and species occurrences to tease apart their relative effects on species distributions. Instead of focusing on single effects of pairwise species interactions, which have little sense in complex communities, ELGRIN contrasts the overall effect of species interactions to that of the environment.Using various simulated and empirical data, we demonstrate the suitability of ELGRIN to address the objectives for various types of interspecific interactions like mutualism, competition and trophic interactions. We then apply the model on vertebrate trophic networks in the European Alps to map the effect of biotic interactions on species distributions. We find that altitude, species richness and connectance significantly impact the overall effect of biotic interactions.Data on ecological networks are everyday increasing and we believe the time is ripe to mobilise these data to better understand biodiversity patterns. ELGRIN provides this opportunity to unravel how interspecific interactions actually influence species distributions.

Influence of Natural and Man-Made Forests on Community Assembly and Species, Functional, and Soil Microbial Diversity

Although an increasing amount of attention is being paid to how human activities alter plant communities, little is known about the consequences of these changes on species’ assemblages and biodiversity patterns. Using three forest types (a Pinus yunnanensis man-made forest; Eucalyptus smithii man-made forest; and natural secondary forest) in mid-Yunnan, China, we investigated the distribution patterns of species and traits and analyzed diversity patterns and relationships, including those between species diversity, functional diversity, and soil microbial diversity. We found that species co-occurrence patterns in the Pinus yunnanensis man-made forest and natural secondary forest were non-random. The specific leaf area in the Eucalyptus smithii man-made forest and leaf nitrogen concentration in the Pinus yunnanensis man-made forest were both over-dispersed according to the mean Euclidean neighbor distance in the trait space. The natural secondary forest had higher values of species diversity, functional diversity, community-weighted means, and soil microbial diversity than the man-made forest types did. An overall low covariation between species diversity and community-weighted means suggested that the coexistence of many species does not necessarily support functional differentiation among these species. Variance partitioning revealed that soil microbial diversity was mainly regulated by community-weighted means. In conclusion, our results suggest that the naturally recovering forest was better than man-made plantations based on biodiversity patterns.

Modelling fish co-occurrence patterns in a small spring-fed river using a machine learning approach

Stopping biodiversity loss due to human activities is of great concern for ensuring ecosystem services for sustainable development. While species-habitat relationships are an important aspect of species conservation, considering species interactions remains challenging in habitat suitability modelling due to the complex nature of the species’ ecology and uncertainties present in ecological data. To cope with this challenge, a Random Forests (RF) multi-class classifier is built using a data set comprised of monthly fish habitat surveys conducted over a period of two years for analyzing the 16 co-occurrence patterns among four fish species, including endangered species and translocated domestic alien species, in a small spring-fed river in Japan. This multi-class habitat suitability model allows for assessing the instream habitat conditions under which multiple species co-occur. Variable importance and partial dependence plots are generated to extract ecological information for a deeper understanding of the species co-occurrence patterns. Results show that the model performance is greatly influenced by data prevalence as reported for single-species habitat suitability models. Ecological information extracted from the RF model illustrates instream habitat conditions that are important for each of the co-occurrence patterns. Such information can be used for prioritizing conservation sites and better designing habitat conditions in order for multiple native species to co-occur or for preventing non-native species to expand their distribution ranges.

The influence of landscape characteristics on breeding bird dark diversity

The exploration of factors and processes affecting biodiversity loss is central to nature management and wildlife conservation, but only recently has knowledge about the absence of species been recognized as a valuable asset to understand the current biodiversity crisis. In this paper, we explore the dark diversity (species that belong to a site-specific species pool but that are not locally present) of breeding birds in Denmark assessed through species co-occurrence patterns. We apply a nation-wide atlas survey of breeding birds (with a 5 × 5 km resolution), to investigate how landscape characteristics may influence avian diversity, and whether threatened and near threatened species are more likely to occur in dark diversity than least concern (LC) species. On average, the dark diversity constituted 41% of all species belonging to the site-specific species pools and threatened and near-threatened species had a higher probability of belonging to the dark diversity than least concern species. Habitat heterogeneity was negatively related to dark diversity and the proportional cover of intensive agriculture positively related, implying that homogeneous landscapes dominated by agricultural interests led to more absent avian species. Finally, we found significant effects of human disturbance and distance to the coast, indicating that more breeding bird species were missing when human disturbance was high and in near-coastal areas. Our study provides the first attempt to investigate dark diversity among birds and highlights how important landscape characteristics may shape breeding bird diversity and reveal areas of considerable species impoverishment.

Pan-Arctic marine biodiversity and species co-occurrence patterns under recent climate

The Arctic region is experiencing drastic climatic changes bringing about potential ecological shifts. Here, we explored marine biodiversity and potential species associations across eight Arctic marine areas between 2000 and 2019. We compiled species occurrences for a subset of 69 marine taxa (i.e., 26 apex predators and 43 mesopredators) and environmental factors to predict taxon-specific distributions using a multi-model ensemble approach. Arctic-wide temporal trends of species richness increased in the last 20 years and highlighted potential emerging areas of species accrual due to climate-driven species redistribution. Further, regional species associations were dominated by positive co-occurrences among species pairs with high frequencies in the Pacific and Atlantic Arctic areas. Comparative analyses of species richness, community composition, and co-occurrence between high and low summer sea ice concentrations revealed contrasting impacts of and detected areas vulnerable to sea ice changes. In particular, low (high) summer sea ice generally resulted in species gains (loss) in the inflow and loss (gains) in the outflow shelves, accompanied by substantial changes in community composition and therefore potential species associations. Overall, the recent changes in biodiversity and species co-occurrences in the Arctic were driven by pervasive poleward range shifts, especially for wide-ranging apex predators. Our findings highlight the varying regional impacts of warming and sea ice loss on Arctic marine communities and provide important insights into the vulnerability of Arctic marine areas to climate change.

Co-occurrence patterns and habitat selection of the mountain hare, European hare, and European rabbit in urban areas of Sweden

Assessing the underlying mechanisms of species co-occurrence patterns can be challenging as biotic and abiotic factors are hard to disentangle. To date, few studies have investigated co-occurrence patterns of mammals within urban areas. As urban areas are increasingly used as habitat by wildlife, there is a need for a better understanding of urban ecology to facilitate human-wildlife co-existence. Here, we investigated co-occurrence patterns and habitat selection of the European hare (Lepus europaeus), mountain hare (L. timidus), and European rabbit (Oryctolagus cuniculus) inside urban areas of Sweden, using joint species distribution models and generalized linear mixed models based on citizen science observations. All three species were observed within urban areas, but European hares and rabbits appear to be more successful urban colonizers compared to mountain hares. Overall, our findings suggested that urban occurrence by all three lagomorphs was related to suitable conditions within the distribution of each species (e.g., climate and elevation), rather than by the presence of other lagomorph species or specific land cover types within urban areas. On a finer spatial scale, European hares and rabbits generally selected for green urban areas and mountain hares for residential gardens, which likely constitute suitable foraging sites. Moreover, overlap in activity times between European hares and rabbits was mediated by land cover type and sympatry. Our findings contribute to the understanding of urban ecology and provide insights for management measures of the three lagomorphs in urban areas of Sweden.

Macrosystem community change in lake phytoplankton and its implications for diversity and function.

We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints. Finland. 1977-2017. Phytoplankton. We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a "region of common profile" approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development. We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities. Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novelcommunity types, but only a minor part of this reshuffling could be linked to temporal environmental change.

Coexistence of Native and Invasive Freshwater Turtles: The Llobregat Delta (NE Iberian Peninsula) as a Case Study

The global degradation of wetlands is increasing their susceptibility to invasions, which is greatly determined by a niche overlap between native and invasive species. We analyze its role in regulating the coexistence of the native Mediterranean stripe-necked terrapin Mauremys leprosa and the invasive Red-eared Slider Trachemys scripta elegans in a coastal wetland. We analyzed both water chemistry and landscape attributes, using variance-partitioning analysis to isolate the variance explained by each set of variables. Then, the influence of environmental variables on species co-occurrence patterns was assessed by using latent variable models (LVM), which account for correlation between species that may be attributable to biotic interactions or missing environmental covariates. The species showed a very low niche overlap, with clear differences in their response to environmental and landscape filters. The distribution of T. s. elegans was largely explained by landscape variables, preferring uniform landscapes within the daily movement buffer, whereas at larger scales, it was associated with a high diversity of habitats of small and uniform relative sizes. A high percentage of the distribution of M. leprosa was unexplained by the measured variables and may be related to the competitive exclusion processes with T. s. elegans. The species was positively related with large patches with high perimeter values or ecotone area at medium spatial scales, and it was benefited from a marked heterogeneity in the patches’ size at larger scale. According to latent variable models, both species had wide eutrophication and salinity tolerance ranges, but they showed different environmental preferences. T. s. elegans was related to eutrophic freshwater environments, whereas M. leprosa was related to more saline and less eutrophic waters. Our results suggest that M. leprosa modifies its habitat use in order to avoid interaction with the T. s. elegans. Thus, management actions aimed at removing the invasive species from the territory and promoting habitat heterogeneity might be needed to protect M. leprosa and avoid local extinctions.

Polymicrobial Foot Infection Patterns Are Common and Associated With Treatment Failure.

That foot infections are predominately polymicrobial has long been recognized, but it is not clear if the various species co-occur randomly or in patterns. We sought nonrandom species co-occurrence patterns that might help better predict prognosis or guide antimicrobial selection. We analyzed tissue (bone, skin, and other soft tissue), fluid, and swab specimens collected from initial foot infection episodes during a 10-year period using a hospital registry. Nonrandom co-occurrence of microbial species was identified using simple pairwise co-occurrence rates adjusted for multiple comparisons, Markov and conditional random fields, and factor analysis. A historical cohort was used to validate pattern occurrence and identify clinical significance. In total, 156 unique species were identified among the 727 specimens obtained from initial foot infection episodes in 694 patients. Multiple analyses suggested that Staphylococcus aureus is negatively associated with other staphylococci. Another pattern noted was the co-occurrence of alpha-hemolytic Streptococcus, Enterococcus fecalis, Klebsiella, Proteus, Enterobacter, or Escherichia coli, and absence of both Bacteroides and Corynebacterium. Patients in a historical cohort with this latter pattern had significantly higher risk-adjusted rates of treatment failure. Several nonrandom microbial co-occurrence patterns are frequently seen in foot infection specimens. One particular pattern with many Proteobacteria species may denote a higher risk for treatment failure. Staphylococcus aureus rarely co-occurs with other staphylococci.

Monthly variations in species co-occurrence patterns of fishes in a temperate estuary

Co-occurrence patterns of species in spatial and temporal scale can provide insight into how fish species distributions and community structure are determined. Identifying temporal shifts of co-occurrence patterns and the influencing factors is important for biodiversity conservation of fish species. However, the species co-occurrence patterns of fishes in estuary are poorly understood in terms of temporal dynamics, especially monthly changes. The co-occurrence patterns of fish communities and the significant species pairs underlying the patterns observed in different months were examined using null model analysis in the Yellow River estuary. Fish communities displayed nonrandom coexistence patterns and were structured in most months in the estuary. A few significantly aggregated or segregated species pairs were found in different months, even though there was no significant overall pattern. Fish species co-occurrence patterns are variable over months and migratory fish species can contribute obviously to forming significant species pairs and structured patterns in the temperate estuary.