Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

Species distribution models for Peruvian plantcutter improve with consideration of biotic interactions

Biotic interactions have been controversial in distributional ecology, mainly in regards to whether they have effects over broad extents, with the negative view known as the Eltonian noise hypothesis (ENH). In this study, we evaluated the ENH for Phytotoma raimondii, a restricted‐range Peruvian endemic bird species: we developed models based on 1) only abiotic conditions, 2) only host plant distributions, and 3) both abiotic conditions and host plant distributions; models were evaluated with partial receiver operating characteristic test and Akaike information criteria metrics. We rejected the ENH for this case: biotic interactions improved the model. The frequency with which exceptions to the ENH are detected has important implications for distributional ecology and methods for estimating distributions of species.     

Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions

Predicting changes in potential habitat for endangered species as a result of global warming requires considering more than future climate conditions; it is also necessary to evaluate biotic associations. Most distribution models predicting species responses to climate change include climate variables and occasionally topographic and edaphic parameters, rarely are biotic interactions included. Here, we incorporate biotic interactions into niche models to predict suitable habitat for species under altered climates. We constructed and evaluated niche models for an endangered butterfly and a threatened bird species, both are habitat specialists restricted to semiarid shrublands of southern California. To incorporate their dependency on shrubs, we first developed climate‐based niche models for shrubland vegetation and individual shrub species. We also developed models for the butterfly's larval host plants. Outputs from these models were included in the environmental variable dataset used to create butterfly and bird niche models. For both animal species, abiotic–biotic models outperformed the climate‐only model, with climate‐only models over‐predicting suitable habitat under current climate conditions. We used the climate‐only and abiotic–biotic models to calculate amounts of suitable habitat under altered climates and to evaluate species' sensitivities to climate change. We varied temperature (+0.6, +1.7, and +2.8 °C) and precipitation (50%, 90%, 100%, 110%, and 150%) relative to current climate averages and within ranges predicted by global climate change models. Suitable habitat for each species was reduced at all levels of temperature increase. Both species were sensitive to precipitation changes, particularly increases. Under altered climates, including biotic variables reduced habitat by 68–100% relative to the climate‐only model. To design reserve systems conserving sensitive species under global warming, it is important to consider biotic interactions, particularly for habitat specialists and species with strong dependencies on other species.     

Context‐dependent biotic interactions control plant abundance across altitudinal environmental gradients

Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context‐dependent across abiotic gradients. For example, plant–plant interactions can grade from competition to facilitation over temperature gradients. We used a hierarchical Bayesian framework to predict the abundances of 12 plant species across a mountain landscape and test hypotheses on the context‐dependency of biotic interactions over abiotic gradients. We combined field‐based estimates of six biotic interactions (foliar herbivory and pathogen damage, fungal root colonization, fossorial mammal disturbance, plant cover and plant diversity) with abiotic data on climate and soil depth, nutrients and moisture. All biotic interactions were significantly context‐dependent along temperature gradients. Results supported the stress gradient hypothesis: as abiotic stress increased, the strength or direction of the relationship between biotic variables and plant abundance generally switched from negative (suggesting suppressed plant abundance) to positive (suggesting facilitation/mutualism). For half of the species, plant cover was the best predictor of abundance, suggesting that the prior focus on plant–plant interactions is well‐justified. Explicitly incorporating the context‐dependency of biotic interactions generated novel hypotheses about drivers of plant abundance across abiotic gradients and may improve the accuracy of niche models.     

No species is an island: testing the effects of biotic interactions on models of avian niche occupation

Traditionally, the niche of a species is described as a hypothetical 3D space, constituted by well‐known biotic interactions (e.g. predation, competition, trophic relationships, resource–consumer interactions, etc.) and various abiotic environmental factors. Species distribution models (SDMs), also called “niche models” and often used to predict wildlife distribution at landscape scale, are typically constructed using abiotic factors with biotic interactions generally been ignored. Here, we compared the goodness of fit of SDMs for red‐backed shrike Lanius collurio in farmlands of Western Poland, using both the classical approach (modeled only on environmental variables) and the approach which included also other potentially associated bird species. The potential associations among species were derived from the relevant ecological literature and by a correlation matrix of occurrences. Our findings highlight the importance of including heterospecific interactions in improving our understanding of niche occupation for bird species. We suggest that suite of measures currently used to quantify realized species niches could be improved by also considering the occurrence of certain associated species. Then, an hypothetical “species 1” can use the occurrence of a successfully established individual of “species 2” as indicator or “trace” of the location of available suitable habitat to breed. We hypothesize this kind of biotic interaction as the “heterospecific trace effect” (HTE): an interaction based on the availability and use of “public information” provided by individuals from different species. Finally, we discuss about the incomes of biotic interactions for enhancing the predictive capacities on species distribution models.     

Positive and negative biotic interactions and invasive Triadica sebifera tolerance to salinity: a cross‐continent comparative study

Exotic plant species may exhibit abiotic niche expansions that enable them to persist in a greater variety of habitat types in their introduced ranges than in their native ranges. This may reflect variation in limitation by different abiotic niche dimensions (realized niche shift) or phenotypic effects of biotic interactions that vary among ranges (realized niche expansion). Novel abiotic and biotic environments in the introduced range may also lead to genetic changes in exotic plant traits that enhance their abiotic stress tolerance (fundamental niche expansion). Here, we investigated how biotic interactions (aboveground herbivory and soil organisms) affect plant salinity tolerance using the invasive species Triadica sebifera from China (native range) and US (introduced range) populations grown in common gardens in both ranges. Simulated herbivory significantly reduced survival in saline treatments with reductions especially large at low salinity. Soil sterilization had a negative effect on survival at low salinity in China but had a positive effect on survival at low salinity in the US. Triadica survival and biomass were higher for US populations than for China populations, particularly in China but salinity tolerance did not depend on population origin. On average, arbuscular mycorrhizal (AM) colonization was higher for US populations, US soils and low salinity. These factors had a significant, positive, non‐additive interaction so that clipped seedlings from US populations in low saline US soils had high levels of AM colonization. Overall, our results show that phenotypic biotic interactions shape Triadica's salinity tolerance. Positive and negative biotic interactions together affected plant performance at intermediate stress levels. However, only aboveground damage consistently affected salinity tolerance, suggesting an important role for enemy release in expanding stress tolerance.     

Mutualist‐mediated effects on species' range limits across large geographic scales

Understanding the processes determining species range limits is central to predicting species distributions under climate change. Projected future ranges are extrapolated from distribution models based on climate layers, and few models incorporate the effects of biotic interactions on species' distributions. Here, we show that a positive species interaction ameliorates abiotic stress, and has a profound effect on a species' range limits. Combining field surveys of 92 populations, 10 common garden experiments throughout the range, species distribution models and greenhouse experiments, we show that mutualistic fungal endophytes ameliorate drought stress and broaden the geographic range of their native grass host Bromus laevipes by thousands of square kilometres (~ 20% larger) into drier habitats. Range differentiation between fungal‐associated and fungal‐free grasses was comparable to species‐level range divergence of congeners, indicating large impacts on range limits. Positive biotic interactions may be underappreciated in determining species' ranges and species' responses to future climates across large geographic scales.     

Division within the North American boreal forest: Ecological niche divergence between the Bicknell's Thrush (Catharus bicknelli) and Gray‐cheeked Thrush (C. minimus)

Sister species that diverged in allopatry in similar environments are expected to exhibit niche conservatism. Using ecological niche modeling and a multivariate analysis of climate and habitat data, I test the hypothesis that the Bicknell's Thrush (Catharus bicknelli) and Gray‐cheeked Thrush (C. mimimus), sister species that breed in the North American boreal forest, show niche conservatism. Three tree species that are important components of breeding territories of both thrush species were combined with climatic variables to create niche models consisting of abiotic and biotic components. Abiotic‐only, abiotic+biotic, and biotic‐only models were evaluated using the area under the curve (AUC) criterion. Abiotic+biotic models had higher AUC scores and did not over‐project thrush distributions compared to abiotic‐only or biotic‐only models. From the abiotic+biotic models, I tested for niche conservatism or divergence by accounting for the differences in the availability of niche components by calculating (1) niche overlap from ecological niche models and (2) mean niche differences of environmental values at occurrence points. Niche background similarity tests revealed significant niche divergence in 10 of 12 comparisons, and multivariate tests revealed niche divergence along 2 of 3 niche axes. The Bicknell's Thrush breeds in warmer and wetter regions with a high abundance of balsam fir (Abies balsamea), whereas Gray‐cheeked Thrush often co‐occurs with black spruce (Picea mariana). Niche divergence, rather than conservatism, was the predominant pattern for these species, suggesting that ecological divergence has played a role in the speciation of the Bicknell's Thrush and Gray‐cheeked Thrush. Furthermore, because niche models were improved by the incorporation of biotic variables, this study validates the inclusion of relevant biotic factors in ecological niche modeling to increase model accuracy.     

Microhabitat selection in the common lizard: implications of biotic interactions,age, sex,local processes,and model transferability among populations

Modeling species' habitat requirements are crucial to assess impacts of global change, for conservation efforts and to test mechanisms driving species presence. While the influence of abiotic factors has been widely examined, the importance of biotic factors and biotic interactions, and the potential implications of local processes are not well understood. Testing their importance requires additional knowledge and analyses at local habitat scale. Here, we recorded the locations of species presence at the microhabitat scale and measured abiotic and biotic parameters in three different common lizard (Zootoca vivipara) populations using a standardized sampling protocol. Thereafter, space use models and cross‐evaluations among populations were run to infer local processes and estimate the importance of biotic parameters, biotic interactions, sex, and age. Biotic parameters explained more variation than abiotic parameters, and intraspecific interactions significantly predicted the spatial distribution. Significant differences among populations in the relationship between abiotic parameters and lizard distribution, and the greater model transferability within populations than between populations are in line with effects predicted by local adaptation and/or phenotypic plasticity. These results underline the importance of including biotic parameters and biotic interactions in space use models at the population level. There were significant differences in space use between sexes, and between adults and yearlings, the latter showing no association with the measured parameters. Consequently, predictive habitat models at the population level taking into account different sexes and age classes are required to understand a specie's ecological requirements and to allow for precise conservation strategies. Our study therefore stresses that future predictive habitat models at the population level and their transferability should take these parameters into account.     

The role of abiotic and biotic factors in determining coexistence of multiple pollinators in the yucca–yucca moth mutualism

The determinants of a species' geographic distribution are a combination of both abiotic and biotic factors. Environmental niche modeling of climatic factors has been instrumental in documenting the role of abiotic factors in a species' niche. Integrating this approach with data from species interactions provides a means to assess the relative roles of abiotic and biotic components. Here, we examine whether the high host specificity typically exhibited in the active pollination mutualism between yuccas and yucca moths is the result of differences in climatic niche requirements that limit yucca moth distributions or the result of competition among mutualistic moths that would co‐occur on the same yucca species. We compared the species distribution models of two Tegeticula pollinator moths that use the geographically widespread plant Yucca filamentosa. Tegeticula yuccasella occurs throughout eastern North America whereas T. cassandra is restricted to the southeastern portion of the range, primarily occurring in Florida. Species distribution models demonstrate that T. cassandra is restricted climatically to the southeastern United States and T. yuccasella is predicted to be able to live across all of eastern North America. Data on moth abundances in Florida demonstrate that both moth species are present on Y. filamentosa; however, T. cassandra is numerically dominant. Taken together, the results suggest that moth geographic distributions are heavily influenced by climate, but competition among pollinating congeners will act to restrict populations of moth species that co‐occur.     

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.     

Invasion biology in non‐free‐living species: interactions between abiotic (climatic) and biotic (host availability) factors in geographical space in crayfish commensals (Ostracoda,Entocytheridae)

In invasion processes, both abiotic and biotic factors are considered essential, but the latter are usually disregarded when modeling the potential spread of exotic species. In the framework of set theory, interactions between biotic (B), abiotic (A), and movement‐related (M) factors in the geographical space can be hypothesized with BAM diagrams and tested using ecological niche models (ENMs) to estimate A and B areas. The main aim of our survey was to evaluate the interactions between abiotic (climatic) and biotic (host availability) factors in geographical space for exotic symbionts (i.e., non‐free‐living species), using ENM techniques combined with a BAM framework and using exotic Entocytheridae (Ostracoda) found in Europe as model organisms. We carried out an extensive survey to evaluate the distribution of entocytherids hosted by crayfish in Europe by checking 94 European localities and 12 crayfish species. Both exotic entocytherid species found, Ankylocythere sinuosa and Uncinocythere occidentalis, were widely distributed in W Europe living on the exotic crayfish species Procambarus clarkii and Pacifastacus leniusculus, respectively. No entocytherids were observed in the remaining crayfish species. The suitable area for A. sinuosa was mainly restricted by its own limitations to minimum temperatures in W and N Europe and precipitation seasonality in circum‐Mediterranean areas. Uncinocythere occidentalis was mostly restricted by host availability in circum‐Mediterranean regions due to limitations of P. leniusculus to higher precipitation seasonality and maximum temperatures. The combination of ENMs with set theory allows studying the invasive biology of symbionts and provides clues about biogeographic barriers due to abiotic or biotic factors limiting the expansion of the symbiont in different regions of the invasive range. The relative importance of abiotic and biotic factors on geographical space can then be assessed and applied in conservation plans. This approach can also be implemented in other systems where the target species is closely interacting with other taxa.     

Spatio‐temporal variation of biotic factors underpins contemporary range dynamics of congeners

Species’ ranges are complex often exhibiting multidirectional shifts over space and time. Despite the strong fingerprint of recent historical climate change on species’ distributions, biotic factors such as loss of vegetative habitat and the presence of potential competitors constitute important yet often overlooked drivers of range dynamics. Furthermore, short‐term changes in environmental conditions can influence the underlying processes of local extinction and local colonization that drive range shifts, yet are rarely considered at broad scales. We used dynamic state‐space occupancy models to test multiple hypotheses of the relative importance of major drivers of range shifts of Golden‐winged Warblers (Vermivora chrysoptera) and Blue‐winged Warblers (V. cyanoptera) between 1983 and 2012 across North America: warming temperatures; habitat changes; and occurrence of congeneric species, used here as proxy for biotic interactions. Dynamic occupancies for both species were most influenced by spatial relative to temporal variation in temperature and habitat. However, temporal variation in temperature anomalies and biotic interactions remained important. The two biotic factors considered, habitat change and biotic interactions, had the largest relative effect on estimated extinction rates followed by abiotic temperature anomalies. For the Golden‐winged Warbler, the predicted presence of the Blue‐winged Warbler, a hypothesized competitor, most influenced extinction probabilities, contributing to evidence supporting its role in site‐level species replacement. Given the overall importance of biotic factors on range‐wide dynamic occupancies, their consideration alongside abiotic factors should not be overlooked. Our results suggest that warming compounds the negative effect of habitat loss emphasizing species’ need for habitat to adapt to a changing climate. Notably, even closely related species exhibited individual responses to abiotic and biotic factors considered.     

Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication

Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian‐based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co‐occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes’ distribution under eutrophication stress.     

Integrating demography,dispersal and interspecific interactions into bird distribution models

Species’ ranges are primarily limited by the physiological (abiotic) tolerance of the species, described by their fundamental niche. Additionally, demographic processes, dispersal, and interspecific interactions with other species are shaping species distributions, resulting in the realised niche. Understanding the complex interplay between these drivers is vital for making robust biodiversity predictions to novel environments. Correlative species distribution models have been widely used to predict biodiversity response but also remain criticised, as they are not able to properly disentangle the abiotic and biotic drivers shaping species’ niches. Recent developments have thus focussed on 1) integrating demography and dispersal into species distribution models, and on 2) integrating interspecific interactions. Here, I review recent demographic and multi‐species modelling approaches and discuss critical aspects of these models that remain underexplored in general and in respect to birds, for example, the complex life histories of birds and other animals as well as the scale dependence of interspecific interactions. I conclude by formulating modelling guidelines for integrating the abiotic and biotic processes that limit species’ ranges, which will help to disentangle the complex roles of demography, dispersal and interspecific interactions in shaping species niches. Throughout, I pinpoint complexities of avian life cycles that are critical for consideration in the models and identify data requirements for operationalizing the different modelling steps.     

Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species,Lasiocampidae) using different representations of modelled host tree distributions

Biotic interactions influence species niches and may thus shape distributions. Nevertheless, species distribution modelling has traditionally relied exclusively on environmental factors to predict species distributions, while biotic interactions have only seldom been incorporated into models. This study tested the ability of incorporating biotic interactions, in the form of host plant distributions, to increase model performance for two host‐dependent lepidopterans of economic interest, namely the African silk moth species, Gonometa postica and Gonometa rufobrunnea (Lasiocampidae). Both species are dependent on a small number of host tree species for the completion of their life cycle. We thus expected the host plant distribution to be an important predictor of Gonometa distributions. Model performance of a species distribution model trained only on abiotic predictors was compared to four species distribution models that additionally incorporated biotic interactions in the form of four different representations of host plant distributions as predictors. We found that incorporating the moth–host plant interactions improved G. rufobrunnea model performance for all representations of host plant distribution, while for G. postica model performance only improved for one representation of host plant distribution. The best performing representation of host plant distribution differed for the two Gonometa species. While these results suggest that incorporating biotic interactions into species distribution models can improve model performance, there is inconsistency in which representation of the host tree distribution best improves predictions. Therefore, the ability of biotic interactions to improve species distribution models may be context‐specific, even for species which have obligatory interactions with other organisms.     

Characterising functional trait diversity and trait–environment relationships in fish assemblages of boreal lakes

1. Characterisation of biodiversity is typically based on taxonomic approaches, while much less is known about other related aspects. Functional trait diversity is one such component of biodiversity that has not been addressed rigorously in ecological research until recently. We tested the congruence between taxonomic‐ and trait‐based approaches, and examined how spatial configuration, local abiotic environmental factors and biotic effects interact to influence taxonomic‐ and trait‐based characterisation of freshwater fish assemblages. 2. Fish assemblage data were compiled for 124 lakes in southern Finland. Variance partitioning in both linear regression analyses and redundancy analysis was used to quantify the relative contribution of spatial and environmental variables to taxonomic and functional trait diversity and structure. Additionally, a null model analysis was used to test for the potential effects of interspecific segregation and biotic interactions on the co‐occurrence of species. 3. The species pool was relatively poor. However, trait‐based classification of species indicated that most species belonged to unique functional entities, which suggested low redundancy in species composition. Correlation analysis indicated a very strong relationship between species richness (SR) and the number of unique trait combinations (UTC). Ecoregion‐level heterogeneity in SR and UTC were well represented in a relatively small group of randomly selected lakes (c. 30 lakes). Multiple regressions indicated moderate roles for abiotic environmental variables (i.e. lake surface area, depth, total phosphorous, colour and pH) in determining SR, UTC and the distribution of single trait categories, whereas geographical location was not generally influential. 4. Redundancy analysis revealed similar patterns to those of diversity analyses for taxonomic and associated trait‐based structure, emphasising the effect of abiotic environmental variables and the negligible effect of geographical position. 5. Co‐occurrence analysis indicated significant checkerboard distribution at the whole assemblage level, but interspecific segregation proved to be of relatively minor importance in the constrained analyses, where species pair combinations within trait category groups were evaluated. 6. Our results suggest that taxonomic‐ and trait‐based patterns of boreal lake fish assemblages are strongly interrelated. Environmental filtering through the effects of local abiotic variables seems to have the most prominent role in determining trait‐based assemblage patterns among lakes, which may also be secondarily shaped by biotic interactions. 7. From the applied perspective, it may not necessarily matter whether traditional taxonomic or more novel trait‐based approaches are used in characterising spatial patterns in boreal fish assemblages. However, trait‐based approaches may provide complementary information which cannot be directly revealed by taxonomic data.     

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.

     

Multiple environmental stressors increase the realised niche breadth of a forest‐dwelling fish

Understanding the determinants of species' niche breadth is important due to the negative relationship between niche breadth and extinction probability. Species tolerant to extremely harsh abiotic conditions (e.g. low pH or hypoxia) often have relatively small realised niches due to a trade‐off between abiotic and biotic stress tolerance, and are therefore particularly vulnerable to extinction. We hypothesised that tolerance to multiple extreme conditions (e.g. low pH, hypoxia and drought) in brown mudfish Neochanna apoda, would increase their realised niche breadth because each extreme would provide additive refuge against a dominant species, the banded kokopu Galaxias fasciatus. Fish distributions were surveyed in 65 peat‐swamp‐forest streams and pools in New Zealand, which varied in dissolved oxygen, acidity and hydroperiod. Mudfish distribution was extremely patchy, and almost completely allopatric with kokopu. Allopatry was driven mainly by pool hydroperiod; mudfish occupied 88 percent of temporary pools due to their tolerance of habitat drying, whereas kokopu were absent from temporary pools. Within permanent pools, mudfish occurrence was negatively related to pool oxygen and pH, whereas kokopu occurrence was positively related to these conditions. Pool conditions were independently distributed in the landscape, suggesting that each abiotic stressor offered additive refuge for mudfish from kokopu predation/competition. Consequently, the mudfish realised niche breadth depended on the number of abiotic factors driving their allopatry with kokopu. Given the widespread negative relationships between niche breadth and species extinction probabilities, our results indicate that tolerance to multiple stressors may play an important role in insuring species persistence against the multiple drivers of global environmental change.     

Improving species distribution models using biotic interactions: a case study of parasites,pollinators and plants

Biotic interactions have been considered as an important factor to be included in species distribution modelling, but little is known about how different types of interaction or different strategies for modelling affect model performance. This study compares different methods for including interspecific interactions in distribution models for bees, their brood parasites, and the plants they pollinate. Host–parasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant–pollinator interactions between Centris bees and Krameria flowers were used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. For Bombus, the inclusion of interacting species distributions generally increased model predictive accuracy. The improvement was better when the interacting species was included with its raw distribution rather than with its modeled suitability. However, incorporating the distributions of non‐interacting species sometimes resulted in similarly increased model accuracy despite their being no significance of any interaction for the distribution. For the Centris‐Krameria system the best strategy for modelling biotic interactions was to include the interacting species model‐predicted values. However, the results were less consistent than those for Bombus species, and most models including biotic interactions showed no significant improvement over abiotic models. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales. However, correlations between species distributions are not necessarily indicative of interactions. Therefore, choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models and forecast distribution change.