Statistical challenges in null model analysis

Community connectivity and local heterogeneity explain animal species co-occurrences within pond communities

Metacommunity processes have the potential to determine most features of the community structure. However, species diversity has been the dominant focus of studies. Nestedness, modularity and checkerboard distribution of species occurrences are main components of biodiversity organisation. Within communities, these patterns emerge from the interaction between functional diversity, spatial heterogeneity and resource availability. Additionally, the connectivity determines the pool of species for community assembly and, eventually, the pattern of species co-occurrence within communities. Despite the recognised theoretical expectations, the change in occurrence patterns within communities along ecological gradients has seldom been considered. Here, we analyse the spatial occurrence of animal species along sampling units within 18 temporary ponds and its relationship with pond environments and geographic isolation. Isolated ponds presented a nested organisation of species with low spatial segregation-modularity and checkerboard-and the opposite was found for communities with high connectivity. A pattern putatively explained by high functional diversity in ponds with large connectivity and heterogeneity, which determines that species composition tracks changes in microhabitats. On the contrary, nestedness is promoted in dispersal-limited communities with low functional diversity, where microhabitat filters mainly affect richness without spatial replacement between functional groups. Vegetation biomass promotes nestedness, probably due to the observed increase in spatial variance in biomass with the mean biomass. Similarly, the richness of vegetation reduced the spatial segregation of animals within communities. This result may be due to the high plant diversity of the pond that is observed similarly along all sampling units, which promotes the spatial co-occurrence of species at this scale. In the study system, the spatial arrangement of species within communities is related to local drivers as heterogeneity and metacommunity processes by means of dispersal between communities. Patterns of species co-occurrence are interrelated with community biodiversity and species interactions, and consequently with most functional and structural properties of communities. These results indicate that understanding the interplay between metacommunity processes and co-occurrence patterns is probably more important than previously thought to understand biodiversity assembly and functioning.

Forest structure, plants, arthropods, scale, or birds' functional groups: What key factor are forest birds responding to?

Forest birds respond to a diverse set of environmental factors, including those altered by forest management intensity, such as resource and habitat availability in the form of food or nesting sites. Although resource/habitat availability and bird traits likely mediate responses of bird diversity to global change drivers, no study has assessed the direct and indirect effects of changes in forest management and traits on bird assemblages jointly at large spatial scales. In this context the questions remain whether (1) the birds' response to forest management changes through alterations in structural properties and/or food availability, or (2) if birds' eco-morphological traits act as environmental filters in response to environmental factors. We audio-visually recorded birds at 150 forest plots in three regions of Germany and assessed the forest structure (LiDAR) as well as the diversity of the herbaceous layer and diversity and biomass of arthropods. We further assessed eco-morphological traits of the birds and tested if effects on bird assemblages are mediated by changes in eco-morphological traits' composition. We found that abundance and species numbers of birds are explained best by models including the major environmental factors, forest structure, plants, and arthropods. Eco-morphological traits only increased model fit for indirect effects on abundance of birds. We found minor differences between the three regions in Germany, indicating spatial congruency of the processes at the local and regional scale. Our results suggest that most birds are not specialized on a particular food type, but that the size, diversity and species composition of arthropods are important. Our findings question the general view that bird traits adapt to the resources available.

Microbial community assembly in engineered bioreactors

Microbial community assembly (MCA) processes that shape microbial communities in environments are being used to analyze engineered bioreactors such as activated sludge systems and anaerobic digesters. The goal of studying MCA is to be able to understand and predict the effect of design and operation procedures on bioreactor microbial composition and function. Ultimately, this can lead to bioreactors that are more efficient, resilient, or resistant to perturbations. This review summarizes the ecological theories underpinning MCA, evaluates MCA analysis methods, analyzes how these MCA-based methods are applied to engineered bioreactors, and extracts lessons from case studies. Furthermore, we suggest future directions in MCA research in engineered bioreactor systems. The review aims to provide insights and guidance to the growing number of environmental engineers who wish to design and understand bioreactors through the lens of MCA.

Investigating macroecological patterns in coarse-grained microbial communities using the stochastic logistic model of growth

The structure and diversity of microbial communities are intrinsically hierarchical due to the shared evolutionary history of their constituents. This history is typically captured through taxonomic assignment and phylogenetic reconstruction, sources of information that are frequently used to group microbes into higher levels of organization in experimental and natural communities. Connecting community diversity to the joint ecological dynamics of the abundances of these groups is a central problem of community ecology. However, how microbial diversity depends on the scale of observation at which groups are defined has never been systematically examined. Here, we used a macroecological approach to quantitatively characterize the structure and diversity of microbial communities among disparate environments across taxonomic and phylogenetic scales. We found that measures of biodiversity at a given scale can be consistently predicted using a minimal model of ecology, the Stochastic Logistic Model of growth (SLM). This result suggests that the SLM is a more appropriate null-model for microbial biodiversity than alternatives such as the Unified Neutral Theory of Biodiversity. Extending these within-scale results, we examined the relationship between measures of biodiversity calculated at different scales (e.g. genus vs. family), an empirical pattern previously evaluated in the context of the Diversity Begets Diversity (DBD) hypothesis (Madi et al., 2020). We found that the relationship between richness estimates at different scales can be quantitatively predicted assuming independence among community members, demonstrating that the DBD can be sufficiently explained using the SLM as a null model of ecology. Contrastingly, only by including correlations between the abundances of community members (e.g. as the consequence of interactions) can we predict the relationship between estimates of diversity at different scales. The results of this study characterize novel microbial patterns across scales of organization and establish a sharp demarcation between recently proposed macroecological patterns that are not and are affected by ecological interactions.

Niche and Range Shifts of Aedes aegypti and Ae. albopictus Suggest That the Latecomer Shows a Greater Invasiveness

The yellow fever (Aedes aegypti) and Asian tiger (Ae. albopictus) mosquitos are major vectors of global mosquito-borne pathogens. However, their niche and range shifts, the underlying mechanisms, and related relative invasion rates remain scarcely known. We examined the niche and range shifts between the native and invasive Ae. aegypti and Ae. albopictus populations through dynamic niche and range models and the largest occurrence record datasets to date. We detected substantial niche and range expansions in both species, probably because the introduced populations have more opportunities to acclimate to diverse environmental conditions than their native counterparts. Mitigating climate change could effectively control their future invasions, given that future climate changes could promote their invasiveness. Additionally, compared to the introduced Ae. aegypti, the more recent invader Ae. albopictus had greater niche and range expansion over its shorter invasion history. In terms of the range shifts, Ae. albopictus had an invasion rate approximately 13.3 times faster than that of Ae. aegypti, making it a more invasive vector of global mosquito-borne pathogens. Therefore, considering its higher invasion rate, much more attention should be paid to Ae. albopictus in devising our strategies against prevailing global mosquito-borne pathogens than Ae. aegypti. Since small niche shifts could result in their large range shifts, niche shifts might be a more important indicator for biological invasion assessments.

Climatic niche and range shifts of grey squirrels (Sciurus carolinensis Gmelin) in Europe: An invasive pest displacing native squirrels

BACKGROUND

As an invasive pest from North America, grey squirrels (GSs; Sciurus carolinensis Gmelin) are displacing native squirrels in Europe. However, the climatic niche and range dynamics of GSs in Europe remain largely unknown. Through niche and range dynamic models, we investigated climatic niche and range shifts between introduced GSs in Europe and native GSs in North America.

RESULTS

GSs in North America can survive in more variable climatic conditions and have much wider climatic niche breadth than do GSs in Europe. Based on climate, the potential range of GSs in Europe included primarily Britain, Ireland, and Italy, whereas the potential range of GSs in North America included vast regions of western and southern Europe. If GSs in Europe could occupy the same climatic niche space and potential range as GSs in North America, they would occupy an area ca. 2.45 times the size of their current range. The unfilling ranges of GSs in Europe relative to those of GSs in North America were primarily in France, Italy, Spain, Croatia, and Portugal.

CONCLUSION

Our observations implied that GSs in Europe have significant invasion potential, and that range projections based on their occurrence records in Europe may underestimate their invasion risk. Given that small niche shifts between GSs in Europe and in North America could lead to large range shifts, niche shifts could be a sensitive indicator in invasion risk assessment. The identified unfilling ranges of the GS in Europe should be prioritized in combating GS invasions in the future. © 2023 Society of Chemical Industry.

Metal bioavailable contamination engages richness decline, species turnover but unchanged functional diversity of stream macroinvertebrates at the scale of a French region

Freshwater ecosystems are the main source of water for sustaining life on earth, and the biodiversity they support is the main source of valuable goods and services for human populations. Despite growing recognition of the impairment of freshwater ecosystems by micropollutant contamination, different conceptual and methodological considerations can newly be addressed to improve our understanding of the ecological impact into these ecosystems. Here, we originally combined in situ ecotoxicology and community ecology concepts to unveil the mechanisms structuring macroinvertebrate communities along a regional contamination gradient. The novelty of our study lies in the use of an innovative biomonitoring approach (measurement of metal contents in caged crustaceans) allowing to quantify and compare on a regional scale the levels of bioavailable metal contamination to which stream communities are exposed. We were hence able to identify 23 streams presenting a significant gradient of bioavailable metal contamination within the same catchment area in the South West of France, from which we also obtained data on the composition of resident macroinvertebrate communities. Analyses of structural and functional integrity of communities revealed an unexpected decoupling between taxonomic and functional diversity of communities in response to bioavailable metal contamination. We show that despite the negative impact of bioavailable metal contamination exposure on taxonomic diversity (with an average species loss of 17% in contaminated streams), functional diversity is maintained through a process of non-random species replacement by functional redundant species at the regional scale. Such unanticipated findings call for a deeper characterization of metal-tolerant communities' ability to cope with environmental variability in multi-stressed ecosystems.

Assessment of the stream invertebrate β -diversity along an elevation gradient using a bidimensional null model analysis

β -Diversity, commonly defined as the compositional variation among localities that links local diversity (α-diversity) and regional diversity (γ-diversity), can arise from two different ecological phenomena, namely the spatial species turnover (i.e., species replacement) and the nestedness of assemblages (i.e., species loss). However, any assessment that does not account for stochasticity in community assembly could be biased and misinform conservation management. In this study, we aimed to provide a better understanding of the overall ecological phenomena underlying streamβ -diversity along elevation gradients and to contribute to the rich debate on null model approaches to identify nonrandom patterns in the distribution of taxa. Based on presence-absence data of 78 stream invertebrate families from 309 sites located in the Swiss Alpine region, we analyzed the effect size of nonrandom spatial distribution of stream invertebrates on theβ -diversity and its two components (i.e., turnover and nestedness). We used a modeling framework that allows exploring the complete range of existing algorithms used in null model analysis and assessing how distribution patterns vary according to an array of possible ecological assumptions. Overall, the turnover of stream invertebrates and the nestedness of assemblages were significantly lower and higher, respectively, than the ones expected by chance. This pattern increased with elevation, and the consistent trend observed along the altitudinal gradient, even in the most conservative analysis, strengthened our findings. Our study suggests that deterministic distribution of stream invertebrates in the Swiss Alpine region is significantly driven by differential dispersal capacity and environmental stress gradients. As long as the ecological assumptions for constructing the null models and their implications are acknowledged, we believe that they still represent useful tools to measure the effect size of nonrandom spatial distribution of taxa onβ -diversity.

Feeding Patterns of Three Widespread Carnivores—The Wolf, Snow Leopard, and Red Fox—in the Trans-Himalayan Landscape of India

The Trans-Himalayan landscape is an extreme cold desert with limited diversity and a low density of wild prey. The landscape has three widespread carnivores—the wolf Canis lupus chanco, snow leopard Panthera uncia, and red fox Vulpes vulpes—competing for similar prey. We studied predation patterns, dietary competition, and niche segregation of three sympatric carnivores in the Indian Trans-Himalayas. The Himalayan or wooly wolf is one of the oldest lineages and has adapted to extreme cold. We further studied the prey selection of the wolf in the high-altitude environment. We collected 1,600 carnivore scats (wolf = 542, snow leopard = 31, and red fox = 1,027), and additional data on 573 snow leopard scats from literature was used in the analyses. We found that livestock was a major contributor to the wolf (56.46%) and snow leopard diet (30.01%). The wolf consumed blue sheep (8.26%) and ibex (3.13%), whereas the snow leopard subsisted on blue sheep (30.79%) and ibex (17.15%), relatively more frequently. The red fox preyed upon small species like pika and marmots (18.85 %); however, livestock carrions (16.49%), fruits and seeds (15.05%), and human-derived material (11.89%) were also consumed frequently. The dietary niche of three carnivore species highly overlapped (Pianka's index = 0.503, simulated mean = 0.419, p = 0.15) due to livestock. The carnivores segregated their diet in prey items originating from the wild. We tested a relationship between carnivore diet variations and prey/predator functional traits using RLQ ordination. Predator morphology traits like body size, weight, and habitat preference significantly affected the prey selection (p < 0.05). The wolf and snow leopard avoided the competition through habitat selection, while the red fox coexisted by exploiting a broader niche. The wolf showed site-specific variation in prey preferences albeit no prey selection at the landscape level (G2 = 6.79, df = 12, p = 0.87). The wolf preferred wild prey over domestic species at the wild prey rich site. The carnivores in this pastoralist landscape have adapted to exploit livestock resources despite facing persecution. Therefore, managing livestock and simultaneously restoring wild prey is crucial for the conservation of the carnivore guild in the Trans-Himalayan ecosystem.

A needle in the haystack? Applying species co-occurrence frameworks with fish assemblage data to identify species associations and sharpen ecological hypotheses

Different species can associate or interact in many ways, and methods exist for inferring associations and underlying mechanisms from incidence data (e.g., co-occurrence frameworks). These methods have received criticism despite their recent resurgence in the literature. However, co-occurrence frameworks for identifying nonrandomly associated species pairs (e.g., aggregated or segregated pairs) have value as heuristic tools for sharpening hypotheses concerning fish ecology. This paper provides a case study examining species co-occurrence across 33 stream fish assemblages in southeastern Oklahoma, USA, which were sampled twice (1974 and 2014). This study sought to determine (a) which species were nonrandomly associated, (b) what processes might have driven these associations and (c) how consistent patterns were across time. Associations among most pairs of species (24 species, 276 unique pairs) were not significantly different from random (>80%). Among all significant, nonrandomly associated species pairs (54 unique pairs), 78% (42 pairs) were aggregated and 22% (12 pairs) segregated. Most of these (28 pairs, 52%) were hypothesized to be driven by nonbiotic mechanisms: habitat filtering (20 pairs, 37%), dispersal limitation (two pairs, 0.4%) or both (six pairs, 11%). The remaining 26 nonrandomly associated pairs (48%) had no detectable signal of spatial or environmental factors involved with the association, therefore the potential for biotic interaction was not refuted. Only five species pairs were consistently associated across both sampling periods: stonerollers Campostoma spp. and orangebelly darter Etheostoma radiosum; red shiner Cyprinella lutrensis and bullhead minnow Pimephales vigilax; bluegill sunfish Lepomis macrochirus and redear sunfish Lepomis microlophus; redfin shiner Lythrurus umbratilis and bluntnose minnow Pimephales notatus; and bigeye shiner Notropis boops and golden shiner Notemigonus crysoleucas. Frameworks for identifying nonrandomly associated species pairs can provide insight into broader mechanisms of species assembly and point to potentially interesting species interactions (out of many possible pairs). However, this approach is best applied as a tool for sharpening hypotheses to be investigated further. Rather than a weakness, the heuristic nature is the strength of such methods, and can help guide biologists toward better questions by employing relatively cheap diversity survey data, which are often already in hand, to reduce complex interaction networks down to their nonstochastic parts which warrant further investigation.

A better index for analysis of co-occurrence and similarity

Scientists often need to know whether pairs of entities tend to occur together or independently. Standard approaches to this issue use co-occurrence indices such as Jaccard, Sørensen-Dice, and Simpson. We show that these indices are sensitive to the prevalences of the entities they describe and that this invalidates their interpretability. We propose an index, α, that is insensitive to prevalences. Published datasets reanalyzed with both α and Jaccard's index (J) yield profoundly different biological inferences. For example, a published analysis using J contradicted predictions of the island biogeography theory finding that community stability increased with increasing physical isolation. Reanalysis of the same dataset with the estimator [Formula: see text] reversed that result and supported theoretical predictions. We found similarly marked effects in reanalyses of antibiotic cross-resistance and human disease biomarkers. Our index α is not merely an improvement; its use changes data interpretation in fundamental ways.

A niche for null models in adaptive resource management

As global systems rapidly change, our collective ability to predict future ecological dynamics will become increasingly important for successful natural resource management. By merging stakeholder objectives with system uncertainty, and by adapting actions to changing systems and knowledge, adaptive resource management (ARM) provides a rigorous platform for making sound decisions in a changing world. Critically, however, applications of ARM could be improved by employing benchmarks (i.e., points of reference) for determining when learning is occurring through the cycle of monitoring, modeling, and decision-making steps in ARM. Many applications of ARM use multiple model-based hypotheses to identify and reduce systematic uncertainty over time, but generally lack benchmarks for gauging discovery of scientific evidence and learning. This creates the danger of thinking that directional changes in model weights or rankings are indicative of evidence for hypotheses, when possibly all competing models are inadequate. There is thus a somewhat obvious, but yet to be filled niche for including benchmarks for learning in ARM. We contend that carefully designed "ecological null models," which are structured to produce an expected ecological pattern in the absence of a hypothesized mechanism, can serve as suitable benchmarks. Using a classic case study of mallard harvest management that is often used to demonstrate the successes of ARM for learning about ecological mechanisms, we show that simple ecological null models, such as population persistence (Nt +1 = Nt ), provide more robust near-term forecasts of population abundance than the currently used mechanistic models. More broadly, ecological null models can be used as benchmarks for learning in ARM that trigger the need for discarding model parameterizations and developing new ones when prevailing models underperform the ecological null model. Identifying mechanistic models that surpass these benchmarks will improve learning through ARM and help decision-makers keep pace with a rapidly changing world.

Using Model Analysis to Unveil Hidden Patterns in Tropical Forest Structures

When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient from poorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes.

Climate change effects on desert ecosystems: A case study on the keystone species of the Namib Desert Welwitschia mirabilis

Deserts have been predicted to be one of the most responsive ecosystems to global climate change. In this study, we examine the spatial and demographic response of a keystone endemic plant of the Namib Desert (Welwitschia mirabilis), for which displacement and reduction of suitable climate has been foreseen under future conditions. The main aim is to assess the association between ongoing climate change and geographical patterns of welwitschia health, reproductive status, and size. We collected data on welwitschia distribution, health condition, reproductive status, and plant size in northern Namibia. We used ecological niche models to predict the expected geographic shift of suitability under climate change scenarios. For each variable, we compared our field measurements with the expected ongoing change in climate suitability. Finally, we tested the presence of simple geographical gradients in the observed patterns. The historically realized thermal niche of welwitschia will be almost completely unavailable in the next 30 years in northern Namibia. Expected reductions of climatic suitability in our study sites were strongly associated with indicators of negative population conditions, namely lower plant health, reduced recruitment and increased adult mortality. Population condition does not follow simple latitudinal or altitudinal gradients. The observed pattern of population traits is consistent with climate change trends and projections. This makes welwitschia a suitable bioindicator (i.e. a 'sentinel') for climate change effect in the Namib Desert ecosystems. Our spatially explicit approach, combining suitability modeling with geographic combinations of population conditions measured in the field, could be extensively adopted to identify sentinel species, and detect population responses to climate change in other regions and ecosystems.

Congruent trophic pathways underpin global coral reef food webs

Ecological interactions uphold ecosystem structure and functioning. However, as species richness increases, the number of possible interactions rises exponentially. More than 6,000 species of coral reef fishes exist across the world's tropical oceans, resulting in an almost innumerable array of possible trophic interactions. Distilling general patterns in these interactions across different bioregions stands to improve our understanding of the processes that govern coral reef functioning. Here, we show that across bioregions, tropical coral reef food webs exhibit a remarkable congruence in their trophic interactions. Specifically, by compiling and investigating the structure of six coral reef food webs across distinct bioregions, we show that when accounting for consumer size and resource availability, these food webs share more trophic interactions than expected by chance. In addition, coral reef food webs are dominated by dietary specialists, which makes trophic pathways vulnerable to biodiversity loss. Prey partitioning among these specialists is geographically consistent, and this pattern intensifies when weak interactions are disregarded. Our results suggest that energy flows through coral reef communities along broadly comparable trophic pathways. Yet, these critical pathways are maintained by species with narrow, specialized diets, which threatens the existence of coral reef functioning in the face of biodiversity loss.

Freshwater Releases Into Estuarine Wetlands Change the Determinants of Benthic Invertebrate Metacommunity Structure

In recent years, the relative importance of the processes driving metacommunity composition has aroused extensive attention and become a powerful approach to identify community patterns and their regulatory mechanisms. We investigated variations in the composition of benthic community in restored wetlands and natural wetlands in the Yellow River Delta (Shandong Province, China). First, spatial structures within each wetland were modeled with Moran eigenvector maps. Next, the variation in community structure among local environmental and spatial variables was partitioned using constrained ordination, and the “elements of metacommunity structure” analysis was used to determine the patterns of best fit for species distributions within metacommunities. Finally, the null model was used to analyze non-random patterns of species co-occurrence. The community structure of benthic invertebrates in restored wetlands and natural wetlands differed significantly. The benthic invertebrate metacommunity structure showed a nested distribution in restored wetlands and a quasi-Clementsian structure in natural wetlands. Pure environmental fractions and pure spatial fractions were critical in regulating benthic invertebrate metacommunities of restored wetlands. In natural wetlands, pure spatial fractions and the interaction between environmental and spatial factors (shared fractions) played a major role in the metacommunity. A species co-occurrence analysis showed that species co-occurred more frequently than expected by chance, demonstrating that biotic interactions were not the main driver of metacommunity structures in both wetland types. Accordingly, the benthic invertebrate metacommunity in estuarine wetlands following freshwater releases was mostly determined by environmental and spatial effects, which resulted in a metacommunity with nested distribution. These results are important for biodiversity protection and ecosystem management of estuarine wetlands in the Yellow River Delta.

Intertidal estimates of sea urchin abundance reveal congruence in spatial structure for a guild of consumers

We hypothesized congruence in the spatial structure of abundance data sampled across multiple scales for an ecological guild of consumers that exploit similar nutritional and habitat resources. We tested this hypothesis on the spatial organization of abundance of an herbivorous guild of sea urchins. We also examined whether the amount of local along-shore rocky habitat can explain the observed spatial patterns of abundance. Standardized estimates of abundance of four intertidal sea urchins-Diadema cf. savignyi, Echinometra mathaei, Parechinus angulosus, and Stomopneustes variolaris-were determined by six observers at 105 sites across 2,850 km of coast of South Africa. For each species and observer, wavelet analysis was used on abundance estimates, after controlling for potential biases, to examine their spatial structure. The relationship between local sea urchin abundance and the amount of upstream and downstream rocky habitat, as defined by the prevailing ocean current, was also investigated. All species exhibited robust structure at scales of 75-220 km, despite variability among observers. Less robust structure in the abundances of three species was detected at larger scales of 430-898 km. Abundance estimates of sympatric populations of two species (D. cf. savignyi and E. mathaei) were positively correlated with the amount of rocky habitat upstream of the site, suggesting that upstream populations act as larval sources across a wide range of scales. No relationship between abundance and habitat size was found for P. angulosus or S. variolaris. Within the range of scales examined, we found robust congruence in spatial structure in abundance at the lower, but not the larger, range of scales for all four species. The relationship between abundance and upstream habitat availability in two species suggests that larval supply from upstream populations was probably the mechanism linking habitat size and abundance.

Anything for a cheerio: Brown capuchins (Sapajus [Cebus] apella) consistently coordinate in an Assurance Game for unequal payoffs

Unequal outcomes disrupt cooperation in some situations, but this has not been tested in the context of coordination in economic games. To explore this, we tested brown capuchins (Sapajus [Cebus] apella) on a manual version of the Stag Hunt (or Assurance) Game, in which individuals sequentially chose between two options, Stag or Hare, and were rewarded according to their choices and that of their partner. Typically, coordination on Stag results in an equal highest payout, whereas coordinating on Hare results in a guaranteed equal but lower payoff and uncoordinated play results in the lowest payoff when playing Stag. We varied this structure such that one capuchin received double the rewards for the coordinated Stag outcome; thus, it was still both animals' best option, but no longer equally rewarding. Despite the inequality, capuchins coordinated on Stag in 78% of trials, and neither payoff structure nor their partner's choice impacted their decision. Additionally, there was no relationship between self-scratching, a measure of stress in capuchins, and choices. After completing the study, we discovered our reward, cheerios, was sufficiently valuable that in another study, capuchins never refused it, so post hoc we repeated the study using a lower value reward, banana flavored pellets. Capuchins completed only 26% of the pellet trials (compared to 98% with cheerios), constraining our ability to interpret the results, but nonetheless the monkeys showed a decrease in preference for Stag, particularly when they received fewer rewards for the coordinated Stag outcome. These results reinforce capuchins' ability to find coordinated outcomes in the Stag Hunt game, but more work is needed to determine whether the monkeys did not mind the inequality or were unwilling to sacrifice a highly preferred food to rectify it. In either case, researchers should carefully consider the impact of their chosen rewards on subjects' choices.

Detecting turnover among complex communities using null models: a case study with sky-island haemosporidian parasites

Turnover in species composition between sites, or beta diversity, is a critical component of species diversity that is typically influenced by geography, environment, and biotic interactions. Quantifying turnover is particularly challenging, however, in multi-host, multi-parasite assemblages where undersampling is unavoidable, resulting in inflated estimates of turnover and uncertainty about its spatial scale. We developed and implemented a framework using null models to test for community turnover in avian haemosporidian communities of three sky islands in the southwestern United States. We screened 776 birds for haemosporidian parasites from three genera (Parahaemoproteus, Plasmodium, and Leucocytozoon) by amplifying and sequencing a mitochondrial DNA barcode. We detected infections in 280 birds (36.1%), sequenced 357 infections, and found a total of 99 parasite haplotypes. When compared to communities simulated from a regional pool, we observed more unique, single-mountain haplotypes and fewer haplotypes shared among three mountain ranges than expected, indicating that haemosporidian communities differ to some degree among adjacent mountain ranges. These results were robust even after pruning datasets to include only identical sets of host species, and they were consistent for two of the three haemosporidian genera. The two more distant mountain ranges were more similar to each other than the one located centrally, suggesting that the differences we detected were due to stochastic colonization-extirpation dynamics. These results demonstrate that avian haemosporidian communities of temperate-zone forests differ on relatively fine spatial scales between adjacent sky islands. Null models are essential tools for testing the spatial scale of turnover in complex, undersampled, and poorly known systems.

Experimental and computational approaches to unravel microbial community assembly

Microbial communities have a preponderant role in the life support processes of our common home planet Earth. These extremely diverse communities drive global biogeochemical cycles, and develop intimate relationships with most multicellular organisms, with a significant impact on their fitness. Our understanding of their composition and function has enjoyed a significant thrust during the last decade thanks to the rise of high-throughput sequencing technologies. Intriguingly, the diversity patterns observed in nature point to the possible existence of fundamental community assembly rules. Unfortunately, these rules are still poorly understood, despite the fact that their knowledge could spur a scientific, technological, and economic revolution, impacting, for instance, agricultural, environmental, and health-related practices. In this minireview, I recapitulate the most important wet lab techniques and computational approaches currently employed in the study of microbial community assembly, and briefly discuss various experimental designs. Most of these approaches and considerations are also relevant to the study of microbial microevolution, as it has been shown that it can occur in ecological relevant timescales. Moreover, I provide a succinct review of various recent studies, chosen based on the diversity of ecological concepts addressed, experimental designs, and choice of wet lab and computational techniques. This piece aims to serve as a primer to those new to the field, as well as a source of new ideas to the more experienced researchers.

The ambiguity of nestedness under soft and hard constraints

Many real networks feature the property of nestedness, i.e. the neighbours of nodes with a few connections are hierarchically nested within the neighbours of nodes with more connections. Despite the abstract simplicity of this notion, various mathematical definitions of nestedness have been proposed, sometimes giving contrasting results. Moreover, there is an ongoing debate on the statistical significance of nestedness, since random networks where the number of connections (degree) of each node is fixed to its empirical value are typically as nested as real ones. By using only ergodic and unbiased null models, we propose a clarification that exploits the recent finding that random networks where the degrees are enforced as hard constraints (microcanonical ensembles) are thermodynamically different from random networks where the degrees are enforced as soft constraints (canonical ensembles). Indeed, alternative definitions of nestedness can be negatively correlated in the microcanonical one, while being positively correlated in the canonical one. This result disentangles distinct notions of nestedness captured by different metrics and highlights the importance of making a principled choice between hard and soft constraints in null models of ecological networks.

Environmental and Microbial Interactions Shape Methane-Oxidizing Bacterial Communities in a Stratified Lake

In stratified lakes, methane-oxidizing bacteria (MOB) are strongly mitigating methane fluxes to the atmosphere by consuming methane entering the water column from the sediments. MOB communities in lakes are diverse and vertically structured, but their spatio-temporal dynamics along the water column as well as physico-chemical parameters and interactions with other bacterial species that drive the community assembly have so far not been explored in depth. Here, we present a detailed investigation of the MOB and bacterial community composition and a large set of physico-chemical parameters in a shallow, seasonally stratified, and sub-alpine lake. Four highly resolved vertical profiles were sampled in three different years and during various stages of development of the stratified water column. Non-randomly assembled MOB communities were detected in all compartments. We could identify methane and oxygen gradients and physico-chemical parameters like pH, light, available copper and iron, and total dissolved nitrogen as important drivers of the MOB community structure. In addition, MOB were well-integrated into a bacterial-environmental network. Partial redundancy analysis of the relevance network of physico-chemical variables and bacteria explained up to 84% of the MOB abundances. Spatio-temporal MOB community changes were 51% congruent with shifts in the total bacterial community and 22% of variance in MOB abundances could be explained exclusively by the bacterial community composition. Our results show that microbial interactions may play an important role in structuring the MOB community along the depth gradient of stratified lakes.

Hill-based dissimilarity indices and null models for analysis of microbial community assembly

BACKGROUND

High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases, and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.

RESULTS

Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.

CONCLUSIONS

Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package ( https://github.com/omvatten/qdiv ). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines. Video Abstract.

Good times, bad times: Resource pulses influence mammal diversity in meridional Brazilian highlands

Understanding spatiotemporal patterns of species distributions and their determinants is paramount in ecology. Here, we explore the relationship between the diversity of surviving mammals and two of the main alimentary resources (araucaria seeds and feijoa fruits) across the Araucaria Forest (FOM) in South America. First, we investigated the influence of landscape and environment on the species distribution and pulse of forest productivity. Then, we evaluated how these spatiotemporal pulses in resource availability influence the mammalian diversity. We analyzed the data via diversity descriptors, Morisita index and multiple regressions. Our findings highlighted that climate, tree density, and other environmental variables explained the pulses of productivity. Mammalian diversity of first-order consumers mammals-all those immediately feeding on seeds and fruits-was partially related to resource pulses. Our results revealed that the pulses of forest resources can influence mammal diversity over the years, including delayed responses and asynchronous oscillations. The integrity of vegetal elements of the FOM is key to maintain several mammal-mediated ecological processes. Maintaining the viability of tree populations, encouraging the sustainable use of non-timber resources, and promoting the conservation of the mammalian fauna, which is undergoing an unprecedented diversity crisis worldwide, can help to preserve the remaining ecological processes.

Press Disturbance Alters Community Structure and Assembly Mechanisms of Bacterial Taxa and Functional Genes in Mesocosm-Scale Bioreactors

Press disturbances are of interest in microbial ecology, as they can drive microbial communities to alternative stable states. However, the effect of press disturbances in community assembly mechanisms, particularly with regard to taxa and functional genes at different levels of abundance (i.e., common and rare), remains largely unknown. Here, we tested the effect of a continuous alteration in substrate feeding scheme on the structure, function, and assembly of bacterial communities. Two sets of replicate 5-liter sequencing batch reactors were operated at two different organic carbon loads for a period of 74 days, following 53 days of acclimation after inoculation with sludge from a full-scale treatment plant. Temporal dynamics of community taxonomic and functional gene structure were derived from metagenomics and 16S rRNA gene metabarcoding data. Disturbed reactors exhibited different community function, structure, and assembly compared to undisturbed reactors. Bacterial taxa and functional genes showed dissimilar α-diversity and community assembly patterns. Deterministic assembly mechanisms were generally stronger in disturbed reactors and in common fractions compared to rare ones. Function quickly recovered after the disturbance was removed, but community structure did not. Our results highlight that functional gene data from metagenomics can indicate patterns of community assembly that differ from those obtained from taxon data. This study reveals how a joint evaluation of assembly mechanisms and community structure of bacterial taxa and functional genes as well as ecosystem function can unravel the response of complex microbial systems to a press disturbance.IMPORTANCE Ecosystem management must be viewed in the context of increasing frequencies and magnitudes of various disturbances that occur at different scales. This work provides a glimpse of the changes in assembly mechanisms found in microbial communities exposed to sustained changes in their environment. These mechanisms, deterministic or stochastic, can cause communities to reach a similar or variable composition and function. For a comprehensive view, we use a joint evaluation of temporal dynamics in assembly mechanisms and community structure for both bacterial taxa and their functional genes at different abundance levels, in both disturbed and undisturbed states. We further reverted the disturbance state to contrast recovery of function with community structure. Our findings are relevant, as very few studies have employed such an approach, while there is a need to assess the relative importance of assembly mechanisms for microbial communities across different spatial and temporal scales, environmental gradients, and types of disturbance.

Historic changes in species composition for a globally unique bird community

Significant uncertainties remain of how global change impacts on species richness, relative abundance and species composition. Recently, a discussion emerged on the importance of detecting and understanding long-term fluctuations in species composition and relative abundance and whether deterministic or non-deterministic factors can explain any temporal change. However, currently, one of the main impediments to providing answers to these questions is the relatively short time series of species diversity datasets. Many datasets are limited to 2 years and it is rare for a few decades of data to be available. In addition, long-term data typically has standardization issues from the past and/or the methods are not comparable. We address several of these uncertainties by investigating bird diversity in a globally important mountain ecosystem of the Hkakabo Razi Landscape in northern Myanmar. The study compares bird communities in two periods (pre-1940: 1900–1939 vs. post-2000: 2001–2006). Land-cover classes have been included to provide understanding of their potential role as drivers. While species richness did not change, species composition and relative abundance differed, indicating a significant species turn over and hence temporal change. Only 19.2% of bird species occurred during both periods. Land-cover model predictors explained part of the species richness variability but not relative abundance nor species composition changes. The temporal change is likely caused by minimal methodological differences and partially by land-cover.

Mutual Information as a General Measure of Structure in Interaction Networks

Entropy-based indices are long-established measures of biological diversity, nowadays used to gauge partitioning of diversity at different spatial scales. Here, we tackle the measurement of diversity of interactions among two sets of organisms, such as plants and their pollinators. Actual interactions in ecological communities are depicted as bipartite networks or interaction matrices. Recent studies concentrate on distinctive structural patterns, such as nestedness or modularity, found in different modes of interaction. By contrast, we investigate mutual information as a general measure of structure in interactive networks. Mutual information (MI) measures the degree of reciprocal matching or specialization between interacting organisms. To ascertain its usefulness as a general measure, we explore (a) analytical solutions for different models; (b) the response of MI to network parameters, especially size and occupancy; (c) MI in nested, modular, and compound topologies. MI varies with fundamental matrix parameters: dimension and occupancy, for which it can be adjusted or normalized. Apparent differences among topologies are contingent on dimensions and occupancy, rather than on topological patterns themselves. As a general measure of interaction structure, MI is applicable to conceptually and empirically fruitful analyses, such as comparing similar ecological networks along geographical gradients or among interaction modalities in mutualistic or antagonistic networks.

Predicting the structure of turtle assemblages along a megatransect in West Africa

Understanding large- and small-scale patterns and the determinants of species richness is central for the study of evolutionary mechanisms. The extent to which species richness in local communities is related to larger-scale processes is a pre-eminent topic in ecological and evolutionary research. To investigate how local and regional species richness are related, we sampled freshwater turtle assemblages in seven localities to represent the variation in ecological conditions along a 90 km south–north megatransect in Benin, West Africa. In each locality, all turtles captured were identified and measured, and the microhabitat in which individual turtles were observed was classified. Based on these data, we used community diversity metrics to compare turtle assemblages. Spatial autocorrelation did not affect our data. For all localities pooled, two species (Pelusios castaneus and Pelomedusa olivacea) were the most common and one species (Trionyx triunguis) was the rarest. Analyses of the commonest and more numerous species showed that the abundance of Pelusios castaneus declined with an increase in latitude and longitude, but the opposite was true for Pelomedusa olivacea. We showed that various characteristics of the microhabitat were significantly correlated with the abundance of the two common species. We found significant but variable south–north gradients in microhabitat use for different turtle species. Our results highlight the importance of studying interactions between local environments, the ecological requirements of each species and their synecological relationships.

Difficulties in benchmarking ecological null models: an assessment of current methods

Identifying species interactions and detecting when ecological communities are structured by them is an important problem in ecology and biogeography. Ecologists have developed specialized statistical hypothesis tests to detect patterns indicative of community-wide processes in their field data. In this respect, null model approaches have proved particularly popular. The freedom allowed in choosing the null model and statistic to construct a hypothesis test leads to a proliferation of possible hypothesis tests from which ecologists can choose to detect these processes. Here, we point out some serious shortcomings of a popular approach to choosing the best hypothesis for the ecological problem at hand that involves benchmarking different hypothesis tests by assessing their performance on artificially constructed data sets. Terminological errors concerning the use of Type I and Type II errors that underlie these approaches are discussed. We argue that the key benchmarking methods proposed in the literature are not a sound guide for selecting null hypothesis tests, and further, that there is no simple way to benchmark null hypothesis tests. Surprisingly, the basic problems identified here do not appear to have been addressed previously, and these methods are still being used to develop and test new null models and summary statistics, from quantifying community structure (e.g., nestedness and modularity) to analyzing ecological networks.

Integrating the underlying structure of stochasticity into community ecology

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

Coinfections by noninteracting pathogens are not independent and require new tests of interaction

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models.

If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts can be obtained by simply multiplying the individual prevalences. However, even simple epidemiological models show this to be untrue. This study develops new tests for interaction between pathogens that account for this surprising lack of statistical independence.

Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations

Patterns of species associations have been commonly used to infer interactions among species. If species positively co-occur, they may form predominantly neutral assemblages, and such patterns suggest a relatively weak role for compensatory dynamics. The main objective of this study was to test this prediction on temporal samples of bird assemblages (n = 19, 10-57 years) by the presence/absence and quantitative null models on assemblage and guild levels. These null model outcomes were further analyzed to evaluate the effects of various data set characteristics on the outcomes of the null models. The analysis of two binary null models in combination with three association indices revealed 20% with significant aggregations, 61% with random associations, and only 19% with significant segregations (n = 95 simulations). The results of the quantitative null model simulations detected more none-random associations: 61% aggregations, 6% random associations, and 33% segregations (n = 114 simulations). Similarly, quantitative analyses on guild levels showed 58% aggregations, 20% segregations, and 22% random associations (n = 450 simulations). Bayesian GLMs detected that the outcomes of the binary and quantitative null models applied to the assemblage analyses were significantly related to census plot size, whereas the outcomes of the quantitative analyses were also related to the mean population densities of species in the data matrices. In guild-level analyses, only 9% of the GLMs showed a significant influence of matrix properties (plot size, matrix size, species richness, and mean species population densities) on the null model outcomes. The results did not show the prevalence of negative associations that would have supported compensatory dynamics. Instead, we assume that a similar response of the majority of species to climate-driven and stochastic factors may be responsible for the revealed predominance of positive associations.

Ecological drift and competitive interactions predict unique patterns in temporal fluctuations of population size

Recent studies have highlighted the importance of higher-order competitive interactions in stabilizing population dynamics in multi-species communities. But how does the structure of competitive hierarchies affect population dynamics and extinction processes? We tackled this important question by using spatially explicit simulations of ecological drift (10 species in a homogeneous landscape of 64 patches) in which birth rates were influenced by interspecific competition. Specifically, we examined how transitive (linear pecking orders) and intransitive (pecking orders with loops) competitive hierarchies affected extinction rates and population dynamics in simulated communities through time. In comparison to a pure neutral model, an ecological drift model including transitive competition increased extinction rates, caused synchronous density-dependent population fluctuations, and generated a white-noise distribution of population sizes. In contrast, the drift model with intransitive competitive interactions decreased extinctions rates, caused asynchronous (compensatory) density-dependent population fluctuations, and generated a brown noise distribution of population sizes. We also explored the effect on community stability of more complex patterns of competitive interactions in which pairwise competitive relationships were assigned probabilistically. These probabilistic competition models also generated density-dependent trajectories and a brown noise distribution of population sizes. However, extinction rates and the degree of population synchrony were comparable to those observed in purely neutral communities. Collectively, our results confirm that intransitive competition has a strong and stabilizing effect on local populations in species-poor communities. This effect wanes with increasing species richness. Empirical assemblages characterized by brown spectral noise, density-dependent regulation, and asynchronous (compensatory) population fluctuations may indicate a signature of intransitive competitive interactions.

Nematodes in a polar desert reveal the relative role of biotic interactions in the coexistence of soil animals

Abiotic factors are major determinants of soil animal distributions and their dominant role is pronounced in extreme ecosystems, with biotic interactions seemingly playing a minor role. We modelled co-occurrence and distribution of the three nematode species that dominate the soil food web of the McMurdo Dry Valleys (Antarctica). Abiotic factors, other biotic groups, and autocorrelation all contributed to structuring nematode species distributions. However, after removing their effects, we found that the presence of the most abundant nematode species greatly, and negatively, affected the probability of detecting one of the other two species. We observed similar patterns in relative abundances for two out of three pairs of species. Harsh abiotic conditions alone are insufficient to explain contemporary nematode distributions whereas the role of negative biotic interactions has been largely underestimated in soil. The future challenge is to understand how the effects of global change on biotic interactions will alter species coexistence.

Tancredi Caruso et al. analyze biodiversity survey data from the McMurdo Dry Valleys, an extreme desert ecosystem in Antarctica in which abiotic factors are thought to determine species distributions. Focusing on three nematode species, they find that abiotic factors alone cannot explain the data and interaction between species have been historically underestimated.

On the Statistical Distribution of the Nonzero Spatial Autocorrelation Parameter in a Simultaneous Autoregressive Model

This paper focuses on the spatial autocorrelation parameter ρ of the simultaneous autoregressive model, and furnishes its sampling distribution for nonzero values, for two regular square (rook and queen) tessellations as well as a hexagonal case with rook connectivity, using Monte Carlo simulation experiments with a large sample size. The regular square lattice directly relates to increasingly used, remotely sensed images, whereas the regular hexagonal configuration is frequently used in sampling and aggregation situations. Results suggest an asymptotic normal distribution for estimated ρ. More specifically, this paper posits functions between ρ and its variance for three adjacency structures, which makes hypothesis testing implementable and furnishes an easily-computed version of the asymptotic variance for ρ at zero for each configuration. In addition, it also presents three examples, where the first employed a simulated dataset for a zero spatial autocorrelation case, and the other two used two empirical datasets—of these, one is a census block dataset for Wuhan (with a Moran coefficient of 0.53, allowing a null hypothesis of, e.g., ρ=0.7) to illustrate a moderate spatial autocorrelation case, and the other is a remotely sensed image of the Yellow Mountain region, China (with a Moran coefficient of 0.91, allowing a null hypothesis of, e.g., ρ=0.95) to illustrate a high spatial autocorrelation case.

Drivers of Phylogenetic Assemblage Structure of the Furnariides, a Widespread Clade of Lowland Neotropical Birds

Species co-occurrence in local assemblages is shaped by distinct processes at different spatial and temporal scales. Here we focus on historical explanations and examine the phylogenetic structure of local assemblages of the Furnariides clade (Aves: Passeriformes), assessing the influence of diversification rates on the assembly and species co-occurrence within those assemblages. Using 120 local assemblages across Bolivia and Argentina and a nearly complete phylogeny for the clade, we analyzed assemblage phylogenetic structure, applying a recently developed model (DAMOCLES, or dynamic assembly model of colonization, local extinction, and speciation) accounting for the historical processes of speciation, colonization, and local extinction. We also evaluated how diversification rates determine species co-occurrence. We found that the assembly of Furnariides assemblages can be explained largely by speciation, colonization, and local extinction without invoking current local species interactions. Phylogenetic structure of open habitat assemblages mainly showed clustering, characterized by faster rates of colonization and local extinction than in forest habitats, whereas forest habitat assemblages were congruent with the model's equal rates expectation, thus highlighting the influence of habitat preferences on assembly and co-occurrence patterns. Our results suggest that historical processes are sufficient to explain local assemblage phylogenetic structure, while there is little evidence for species ecological interactions in avian assemblage diversity and composition.

Unraveling Saproxylic Insect Interactions in Tree Hollows from Iberian Mediterranean Forest

Tree hollows are complex microhabitats in which a variety of abiotic and biotic factors shape the community assembly of saproxylic insects. Detecting non-random species co-occurrence patterns is a fundamental goal in ecology in order to understand the assembly mechanisms of communities. We study association patterns of species of Coleoptera and Diptera (Syrphidae), belonging to different trophic guilds, on 72 tree hollows at a local and regional scale in three protected areas in Mediterranean forests using a fixed-fixed null model. Our matrix-level analysis shows a tendency for segregation in species association (species exclusion) at the regional and site levels. However, the high complexity of tree-hollow habitats, offering different resources for a more or less specialized fauna, makes it difficult to prove competition interactions. Indeed, pairwise analysis shows a dominance of non-random aggregation patterns (species coexistence) at the local and regional levels. Both aggregation and segregation of non-random patterns were more common among species from different trophic guilds than within the same guilds, with predators being a common denominator for a high percentage of the inter-guild pairs. Our results suggest that predation and facilitation interactions, together with habitat segregation, are the main factors shaping tree-hollow assemblages, while competition seems to be less important. We conclude that species interactions take an important part of the process of assemblage structuration and special attention should be paid to 'ecosystem engineers' and threatened species in the conservation of tree hollow assemblages.

Nestedness patterns and the role of morphodynamics and spatial distance on sandy beach fauna: ecological hypotheses and conservation strategies

Sandy beach fauna is hypothesized to be mainly structured by environmental variables. As such, it is expected that morphodynamic characteristics are limiting factors, and the species pool inhabiting harsher reflective beaches would be a subset of (i.e., nested in) the fauna of nearby dissipative beaches. We investigated the existence of a nestedness pattern in sandy beach assemblages, as well as the contribution of environmental and spatial variables (i.e., factors that potentially affect an assemblage regardless of environmental conditions - typically related to distance between sites and dispersal of organisms) on sandy beach macrobenthic fauna. Dissipative beaches had higher species richness than reflective beaches but we found no nestedness pattern. Furthermore, almost every beach showed exclusive species. Spatial variables exerted stronger influence on macrobenthic assemblages than local environmental variables. Our results therefore suggest that local and small-scale recruitment is the predominant process structuring macrobenthic assemblages. These results bring important implications for sandy beach conservation: given that spatial distance is an important factor structuring macrobenthic fauna and different sandy beaches harbor different pools of species, conservation programs need to focus on sandy beaches across large spatial scales and with varied morphodynamic characteristics in order to preserve coastal biodiversity.

Which climate change path are we following? Bad news from Scots pine

Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.