Nurse plant effects on plant species richness in drylands: The role of grazing,rainfall and species specificity

The outcome of plant–plant interactions depends on environmental (e.g. grazing and climatic conditions) and species-specific attributes (e.g. life strategy and dispersal mode of the species involved). However, the joint effects of such factors on pairwise plant–plant interactions, and how they modulate the role of these interactions at the community level, have not been addressed before. We assessed how these species-specific (life strategy and dispersal) and environmental (grazing and rainfall) factors affected the co-occurrence of 681 plant species pairs on open woodlands in south-eastern Australia. Species-specific attributes affected the co-occurrence of most species pairs, with higher co-occurrence levels dominating for drought-intolerant species. The dispersal mechanism only affected drought-tolerant beneficiaries, with more positive co-occurrences for vertebrate-dispersed species. Conversely, the percentage of facilitated species at the community scale declined under higher rainfall availabilities. A significant grazing × rainfall interaction on the percentage of facilitated species suggests that grazing-mediated protection was important under low to moderate, but not high, rainfall availabilities. This study improves our ability to predict changes in plant–plant interactions along environmental gradients, and their effect on community species richness, by highlighting that: (1) species-specific factors were more important than environmental conditions as drivers of a large amount (～37%) of the pairwise co-occurrences evaluated; (2) grazing and rainfall interaction drive the co-occurrence among different species in the studied communities, and (3) the effect of nurse plants on plant species richness will depend on the relative dominance of particular dispersal mechanisms or life strategies prone to be facilitated.     

Disentangling the roles of chance,abiotic factors and biotic interactions among epiphytic bryophyte communities in a tropical rainforest (Yunnan,China)

• Epiphytes offer an appealing framework to disentangle the contributions of chance, biotic and abiotic drivers of species distributions. In the context of the stress-gradient theory, we test the hypotheses that (i) deterministic (i.e., non-random) factors play an increasing role in communities from young to old trees, (ii) negative biotic interactions increase on older trees and towards the tree base, and (iii) positive interactions show the reverse pattern.
• Bryophyte species distributions and abiotic conditions were recorded on a 1.1 ha tropical rainforest canopy crane site. We analysed co-occurrence patterns in a niche modelling framework to disentangle the roles of chance, abiotic factors and putative biotic interactions among species pairs.
• 76% of species pairs resulted from chance. Abiotic factors explained 78% of non-randomly associated species pairs, and co-occurrences prevailed over non-coincidences in the remaining species pairs. Positive and negative interactions mostly involved species pairs from the same versus different communities (mosses versus liverworts) and life forms, respectively. There was an increase in randomly associated pairs from large to small trees. No increase in negative interactions from young to old trees or from the canopy to the base was observed.
• Our results suggest that epiphytic bryophyte community composition is primarily driven by environmental filtering, whose importance increases with niche complexity and diversity. Biotic interactions play a secondary role, with a very marginal contribution of competitive exclusion. Biotic interactions vary among communities (mosses versus liverworts) and life forms, facilitation prevailing among species from the same community and life form, and competition among species from different communities and life forms.

     

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities

Species co-occurrence analysis is commonly used to assess how interspecific interactions dictate community assembly. Non-random co-occurrences, however, may also emerge from niche differences as well as environmental heterogeneity. The relationships between species co-occurrence patterns, environmental heterogeneity and species niches are not fully understood, due to complex interactions among them. To analyse the relationships among these patterns and processes, I developed synthetic community models and analysed a large dataset of tree species across the conterminous United States. Niche overlap and environmental heterogeneity had significant and contrasting effects on species co-occurrence patterns, in both modelled and real communities. Niche breadth, in turn, affected the effect sizes of both variables on species co-occurrence patterns. The effect of niche breadth on the relationship between co-occurrence and niche overlap was markedly consistent between modelled and real communities, while its effect on the relationship between co-occurrence and environmental heterogeneity was mostly consistent between real and modelled data. The results of this analysis highlight the complex and interactive effects of species niche overlap, niche breadth and environmental heterogeneity on species co-occurrence patterns. Therefore, inferring ecological processes from co-occurrence patterns without accounting for these fundamental characteristics of species and environments may lead to biased conclusions.     

A Continuum of Specialists and Generalists in Empirical Communities

Understanding the persistence of specialists and generalists within ecological communities is a topical research question, with far-reaching consequences for the maintenance of functional diversity. Although theoretical studies indicate that restricted conditions may be necessary to achieve co-occurrence of specialists and generalists, analyses of larger empirical (and species-rich) communities reveal the pervasiveness of coexistence. In this paper, we analyze 175 ecological bipartite networks of three interaction types (animal hosts–parasite, plant–herbivore and plant–pollinator), and measure the extent to which these communities are composed of species with different levels of specificity in their biotic interactions. We find a continuum from specialism to generalism. Furthermore, we demonstrate that diversity tends to be greatest in networks with intermediate connectance, and argue this is because of physical constraints in the filling of networks.     

Environmentally constrained null models: site suitability as occupancy criterion

Null models have proven to be an important quantitative tool in the search for ecological processes driving local diversity and species distribution. However, there remains an important concern that different processes, such as environmental conditions and biotic interactions may produce similar patterns in species distributions. In this paper we present an analytical protocol for incorporating habitat suitability as an occupancy criterion in null models. Our approach involves modeling species presence or absence as a function of environmental conditions, and using the estimated site-specific probabilities of occurrence as the likelihood of species occupancy of a site during the generation of "null communities". We validated this approach by showing that type I error is not affected by the use of probabilities as a site occupancy criterion and is robust against a variety of predictive performances of the species-environmental models. We describe the expected differences when contrasting classical and the environmentally constrained null models, and illustrate our approach with a data set of Dutch dune hunting spider assemblages. Together, an environmentally constrained approach to null models will provide a more robust evaluation of species associations by facilitating the distinction between mutually exclusive processes that may shape species distributions and community assembly.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

Evidence of species interactions within an ectomycorrhizal fungal community

Ectomycorrhizal fungal communities can be structured by abiotic and biotic factors. Here, we present evidence for community structuring by species interactions. We sampled ectomycorrhizas and forest floor seven times during a 13-month period. The presence of various ectomycorrhizal fungal species was determined for each sample, and species co-occurrence analyses were performed. For both ectomycorrhizas and forest floor samples there was significantly less co-occurrence among species within the community than expected by chance, mostly because of negative associations involving Cenococcum geophilum or Clavulina cinerea. For some species pairs, there was significantly more co-occurrence than expected by chance. Both nitrogen and tannin additions to the forest floor altered some interactions among species. The causes of these nonrandom distributions are currently unknown. Future investigations on competition, antibiosis, parasitism and facilitation among ectomycorrhizal fungal species appear to be warranted.     

Positive species interactions shape species' range limits

The relationship between niche and distribution, and especially the role of biotic interactions in shaping species' geographic distributions, has gained increasing interest in the last two decades. Most ecological research has focused on negative species interactions, especially competition, predation and parasitism. Yet the relevance of positive interactions – mutualisms and commensalisms – have been brought to the fore in recent years by an increasing number of empirical studies exploring their impact on range limits. Based on a review of 73 studies from a Web of Science search, we found strong evidence that positive interactions can influence the extent of species' geographic or ecological ranges through a diversity of mechanisms. More specifically, we found that while obligate interactions, and especially obligate mutualisms, tend to constrain the ranges of one or both partners, facultative positive interactions tend to widen ranges. Nonetheless, there was more variation in effects of facultative interactions on range limits, pointing to important context-dependencies. Therefore, we propose that conceptual development in this field will come from studying ecological interactions in the context of networks of many species across environmental gradients, since pairwise interactions alone might overlook the indirect and environmentally-contingent effects that species have on each other in communities of many interacting species. Finally, our study also revealed key data gaps that limit our current understanding of the pervasiveness of effects that positive interactions have on species' ranges, highlighting potential avenues for future theoretical and experimental work.     

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km² to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.     

Geographical variation in mutualistic networks: similarity,turnover and partner fidelity

Although species and their interactions in unison represent biodiversity and all the ecological and evolutionary processes associated with life, biotic interactions have, contrary to species, rarely been integrated into the concepts of spatial β-diversity. Here, we examine β-diversity of ecological networks by using pollination networks sampled across the Canary Islands. We show that adjacent and distant communities are more and less similar, respectively, in their composition of plants, pollinators and interactions than expected from random distributions. We further show that replacement of species is the major driver of interaction turnover and that this contribution increases with distance. Finally, we quantify that species-specific partner compositions (here called partner fidelity) deviate from random partner use, but vary as a result of ecological and geographical variables. In particular, breakdown of partner fidelity was facilitated by increasing geographical distance, changing abundances and changing linkage levels, but was not related to the geographical distribution of the species. This highlights the importance of space when comparing communities of interacting species and may stimulate a rethinking of the spatial interpretation of interaction networks. Moreover, geographical interaction dynamics and its causes are important in our efforts to anticipate effects of large-scale changes, such as anthropogenic disturbances.     

Directional changes of species spatial dispersion and realized environmental niches drive plant community assembly during early plant succession

Aims Probabilistic models of species co-occurrences predict aggregated intraspecific spatial distributions that might decrease the degree of joint species occurrences and increase community richness. Yet, little is known about the influence of intraspecific aggregation on the co-occurrence of species in natural, species-rich communities. Here, we focus on early plant succession and ask how changes in intraspecific aggregation of colonizing plant species influence the pattern of species co-existence, richness and turnover.     

Interspecific interactions and range limits: contrasts among interaction types

There is a great deal of interest in the effects of biotic interactions on geographic distributions. Nature contains many different types of biotic interactions (notably mutualism, commensalism, predation, amensalism, and competition), and it is difficult to compare the effects of multiple interaction types on species’ distributions. To resolve this problem, we analyze a general, flexible model of pairwise biotic interactions that can describe all interaction types. In the absence of strong positive feedback, a species’ ability to be present depends on its ability to increase in numbers when it is rare and the species it is interacting with is at equilibrium. This insight leads to counterintuitive conclusions. Notably, we often predict the same range limit when the focal species experiences competition, predation, or amensalism. Similarly, we often predict the same range margin or when the species experiences mutualism, commensalism, or benefits from prey. In the presence of strong positive density-dependent feedback, different species interactions produce different range limits in our model. In all cases, the abiotic environment can indirectly influence the impact of biotic interactions on range limits. We illustrate the implications of this observation by analyzing a stress gradient where biotic interactions are harmful in benign environments but beneficial in stressful environments. Our results emphasize the need to consider the effects of all biotic interactions on species’ range limits and provide a systematic comparison of when biotic interactions affect distributions.     

Modelling patterns of coexistence of three congeneric headwater fishes

1. Mechanisms driving patterns of occurrence and co-occurrence among North American freshwater fishes are poorly understood. In particular, the influence of biotic interactions on coexistence among stream reaches and their effects on regional species distribution patterns is not well understood for congeneric headwater fishes.
2. Occupancy models provide a useful framework for examining patterns of co-occurrence while also accounting for imperfect detection. Occupancy models may be extended to test for evidence that a dominant species influences the occurrence of a subordinate species and thus evaluate support for the hypothesis that species interactions drive patterns of coexistence.
3. We examined patterns of occurrence and co-occurrence at the stream-reach scale among three species of darters (Percidae: Etheostomatinae) that occupy headwater streams within a Gulf Coastal Plain drainage in the south-eastern U.S.A. We assessed species occurrences at 97 sites in first- to third-order streams on one occasion each and used data from four sub-reaches sampled with equal effort at each site to estimate species-specific detection probabilities. Following sampling, a suite of habitat variables was collected at three equidistant points along each of the three transects established within a sub-reach. Coarse (stream-segment, catchment, network) scale variables were also incorporated using geospatial data. Single-species and two-species occupancy models were used to examine patterns of occupancy and coexistence.
4. The occupancy of each species was influenced by distinct habitat variables. Goldstripe darters (Etheostoma parvipinne) were constrained by a stream size gradient, groundwater input appeared to influence the occurrence of Yazoo darters (Etheostoma raneyi), and local habitat heterogeneity (e.g. variation in depth and current velocity) appeared to influence the occupancy of redspot darters (Etheostoma artesiae).
5. We found no evidence that the presence of one species influenced the occurrence of another within a stream-reach based on two-species occupancy models. Rather, species co-occurrences were best explained as independent occurrences within a stream-reach according to species-specific habitat associations.
6. Occupancy modelling may provide a suitable framework for evaluating the influence of biotic interactions among congeneric stream fishes along species-specific habitat gradients at the stream reach scale. Our study offers insight into how habitat variation can influence coexistence of potential competitors across a large river system.

     

Species co-occurrences in ectoparasite infracommunities: Accounting for confounding factors associated with space,time, and host community composition

1. We explored patterns of co-occurrence of ectoparasite species on individual hosts from Central Europe (Slovakia) and South America (Argentina) within and between higher taxa while controlling for confounding factors associated with variation between host individuals and host species, as well as spatial and temporal variation. We used a recently developed statistical approach, the hierarchical modelling of species communities. 2. Although the probability of pairwise associations of the majority of species in both regions did not differ from random, all significant species associations in Slovakia were positive, whereas the only three significant species associations in Argentina were negative. On average, associations between ectoparasite species belonging to different higher taxa were positive in Slovakia and negative in Argentina. 3. At the host species level, both positive and negative associations between species were detected in all higher taxa. This was also true for ectoparasite co-occurrences in the same site, habitat, or year; although the number of co-occurring species pairs with high posterior probability was much greater in Slovakia than in Argentina. 4. We conclude that consideration of species co-occurrences across the entire multi-host assemblage and control for confounding spatial and temporal factors provided important insights into parasite community structure.     

Effects of habitat characteristics and interspecific interactions on co-occurrence patterns of saproxylic beetles breeding in tree boles after forest fire: null model analyses

It is often suggested that habitat attributes and interspecific interactions can cause non-random species co-occurrence patterns, but quantifying their contributions can be difficult. Null models that systematically exclude and include habitat effects can give information on the contribution of these factors to community assembly. In the boreal forest, saproxylic beetles are known to be attracted to recently burned forests where they breed in dead and dying trees. We examined whether species co-occurrences of saproxylic beetles that develop in, and emerge from, boles of recently burned trees show non-random patterns. We also estimated the extent to which both the post-fire habitat attributes and interspecific interactions among beetles contribute to such patterns. We sampled tree boles encompassing key attributes (tree species, tree size/dbh and burn severity) that are thought to characterize species–habitat associations of saproxylic beetles, a proposition that we tested using indicator species analysis. Two null models with no habitat constraints (“unconstrained”) indicated that a total of 29.4% of the species pairs tested had significant co-occurrence patterns. Habitat-constrained null models indicated that most of the detected species aggregations (72%) and segregations (59%) can be explained by shared and distinct species–habitat relationships, respectively. The assembly pattern was also driven by interspecific interactions, of which some were modulated by habitat; for example, predator and prey species tended to co-occur in large-sized trees (a proxy of available bark/wood food resource primarily for the prey). In addition, some species segregation suggesting antagonistic, competitive, or prey–predator interactions were evident after accounting for the species’ affinities for the same tree species. Overall, our results suggest that an intimate link between habitat and interspecific interactions can have important roles for community assembly of saproxylic assemblages even following disturbance by fire. We also show that a systematic application of null models can offer insight into the mechanisms behind the assembly of ecological communities.     

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases.     

Species assortment or habitat filtering: a case study of spider communities on lake islands

Competition theory predicts that species of similar ecological niches are less likely to coexist than species with different niches, a process called species assortment. In contrast, the concept of habitat filtering implies that species with similar ecological requirements should co-occur more often than expected by chance. Here we use environmental and ecological data to assess patterns of co-occurrence of regional communities of spiders distributed across two assemblies of lake islands in northern Poland. We found aggregated and random co-occurrences of species of the same genus and a significant tendency of species segregation across genera. We also found that species of the same genus react similarly to important environmental variables. A comparison of ecological traits of species of the local communities with those expected from a random sample from the regional Polish species pool corroborated partly the habitat filtering hypothesis. On the other hand, we did not find evidence for species assortment. Our results also imply that at least some observed species co-occurrences result from niche differentiation.     

The effect of competition on species' distributions depends on coexistence,rather than scale alone

One of the key problems in ecology is our need to anticipate the set of locations in which a species will be found (hereafter species' distributions). A major source of uncertainty in these models is the role of interactions among species (hereafter biotic interactions). Unfortunately, it is difficult to directly study this problem at large spatial scales and we lack a clear understanding of when biotic interactions shape species' distributions. We show a simple, direct link between the ease of species' coexistence and the importance of competition for shaping species' distributions. We show that increasing the ease of species' coexistence reduces the influence of biotic interactions. Changing the spatial scale of the analysis can reduce the influence of species interactions, but only when it promotes regional coexistence. Using these ideas, we analyze the conditions under which biotic interactions alter species' distributions in a Lotka–Volterra model of competition along an environmental gradient and argue that coexistence theory, rather than scale alone, provides a guide to the influence of species interactions. Our results provide a guide to the facets of biotic interactions that are necessary to anticipate their effects on species distributions. As such, we expect our work will help the development of more realistic distribution models.     

The effects of space and diversity of interaction types on the stability of complex ecological networks

The relationship between structure and stability in ecological networks and the effect of spatial dynamics on natural communities have both been major foci of ecological research for decades. Network research has traditionally focused on a single interaction type at a time (e.g. food webs, mutualistic networks). Networks comprising different types of interactions have recently started to be empirically characterized. Patterns observed in these networks and their implications for stability demand for further theoretical investigations. Here, we employed a spatially explicit model to disentangle the effects of mutualism/antagonism ratios in food web dynamics and stability. We found that increasing levels of plant-animal mutualistic interactions generally resulted in more stable communities. More importantly, increasing the proportion of mutualistic vs. antagonistic interactions at the base of the food web affects different aspects of ecological stability in different directions, although never negatively. Stability is either not influenced by increasing mutualism—for the cases of population stability and species’ spatial distributions—or is positively influenced by it—for spatial aggregation of species. Additionally, we observe that the relative increase of mutualistic relationships decreases the strength of biotic interactions in general within the ecological network. Our work highlights the importance of considering several dimensions of stability simultaneously to understand the dynamics of communities comprising multiple interaction types.