Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics.

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Microdiverse bacterial clades prevail across Antarctic wetlands.

Antarctica's extreme environmental conditions impose selection pressures on microbial communities. Indeed, a previous study revealed that bacterial assemblages at the Cierva Point Wetland Complex (CPWC) are shaped by strong homogeneous selection. Yet which bacterial phylogenetic clades are shaped by selection processes and their ecological strategies to thrive in such extreme conditions remain unknown. Here, we applied the phyloscore and feature-level ßNTI indexes coupled with phylofactorization to successfully detect bacterial monophyletic clades subjected to homogeneous (HoS) and heterogenous (HeS) selection. Remarkably, only the HoS clades showed high relative abundance across all samples and signs of putative microdiversity. The majority of the amplicon sequence variants (ASVs) within each HoS clade clustered into a unique 97% sequence similarity operational taxonomic unit (OTU) and inhabited a specific environment (lotic, lentic or terrestrial). Our findings suggest the existence of microdiversification leading to sub-taxa niche differentiation, with putative distinct ecotypes (consisting of groups of ASVs) adapted to a specific environment. We hypothesize that HoS clades thriving in the CPWC have phylogenetically conserved traits that accelerate their rate of evolution, enabling them to adapt to strong spatio-temporally variable selection pressures. Variable selection appears to operate within clades to cause very rapid microdiversification without losing key traits that lead to high abundance. Variable and homogeneous selection, therefore, operate simultaneously but on different aspects of organismal ecology. The result is an overall signal of homogeneous selection due to rapid within-clade microdiversification caused by variable selection. It is unknown whether other systems experience this dynamic, and we encourage future work evaluating the transferability of our results.

Deforestation strengthens environmental filtering and competitive exclusion in Neotropical streams and rivers.

Understanding how anthropization impacts the assembly of species onto communities is pivotal to go beyond the observation of biodiversity changes and reveal how disturbances affect the environmental and biotic processes shaping biodiversity. Here, we propose a simple framework to measure the assembly processes underpinning functional convergence/divergence patterns. We applied this framework to northern Amazonian fish communities inventoried using environmental DNA in 35 stream sites and 64 river sites. We found that the harsh and unstable environmental conditions characterizing streams conveyed communities towards functional convergence, by filtering traits related to food acquisition and, to a lower extent, dispersal. Such environmental filtering also strengthened competition by excluding species having less competitive food acquisition traits. Instead, random species assembly was more marked in river communities, which may be explained by the downstream position of rivers facilitating the dispersion of species. Although fish assembly rules differed between streams and river fish communities, anthropogenic disturbances reduced functional divergence in both ecosystems, with a reinforcement of both environmental filtering and weaker competitor exclusion. This may explain the substantial biodiversity alterations observed under slight deforestation levels in Neotropical freshwater ecosystems and underlines their vulnerability to anthropic disturbances that not only affect species persistence but also modify community assembly rules.

Distinct and Temporally Stable Assembly Mechanisms Shape Bacterial and Fungal Communities in Vineyard Soils.

Microbial communities in agricultural soils are fundamental for plant growth and in vineyard ecosystems contribute to defining regional wine quality. Managing soil microbes towards beneficial outcomes requires knowledge of how community assembly processes vary across taxonomic groups, spatial scales, and through time. However, our understanding of microbial assembly remains limited. To quantify the contributions of stochastic and deterministic processes to bacterial and fungal assembly across spatial scales and through time, we used 16 s rRNA gene and ITS sequencing in the soil of an emblematic wine-growing region of Italy.Combining null- and neutral-modelling, we found that assembly processes were consistent through time, but bacteria and fungi were governed by different processes. At the within-vineyard scale, deterministic selection and homogenising dispersal dominated bacterial assembly, while neither selection nor dispersal had clear influence over fungal assembly. At the among-vineyard scale, the influence of dispersal limitation increased for both taxonomic groups, but its contribution was much larger for fungal communities. These null-model-based inferences were supported by neutral modelling, which estimated a dispersal rate almost two orders-of-magnitude lower for fungi than bacteria.This indicates that while stochastic processes are important for fungal assembly, bacteria were more influenced by deterministic selection imposed by the biotic and/or abiotic environment. Managing microbes in vineyard soils could thus benefit from strategies that account for dispersal limitation of fungi and the importance of environmental conditions for bacteria. Our results are consistent with theoretical expectations whereby larger individual size and smaller populations can lead to higher levels of stochasticity.

Hyper-Null Models and Their Applications.

Null models are crucial tools for investigating network topological structures. However, research on null models for higher-order networks is still relatively scarce. In this study, we introduce an innovative method to construct null models for hypergraphs, namely the hyperedge swapping-based method. By preserving certain network properties while altering others, we generate six hyper-null models with various orders and analyze their interrelationships. To validate our approach, we first employ hypergraph entropy to assess the randomness of these null models across four datasets. Furthermore, we examine the differences in important statistical properties between the various null models and the original networks. Lastly, we investigate the impact of hypergraph randomness on network dynamics using the proposed hyper-null models, focusing on dismantling and epidemic contagion. The findings show that our proposed hyper-null models are applicable to various scenarios. By introducing a comprehensive framework for generating and analyzing hyper-null models, this research opens up avenues for further exploration of the intricacies of network structures and their real-world implications.

Calcium signaling in individual APP/PS1 mouse dentate gyrus astrocytes increases ex vivo with Aß pathology and age without affecting astrocyte network activity.

Astrocytes are critical for healthy brain function. In Alzheimer's disease, astrocytes become reactive, which affects their signaling properties. Here, we measured spontaneous calcium transients ex vivo in hippocampal astrocytes in brain slices containing the dentate gyrus of 6- (6M) and 9-month-old (9M) APPswe/PSEN1dE9 (APP/PS1) mice. We investigated the frequency and duration of calcium transients in relation to aging, amyloid-ß (Aß) pathology, and the proximity of the astrocyte to Aß plaques. The 6M APP/PS1 astrocytes showed no change in spontaneous calcium-transient properties compared to wild-type (WT) astrocytes. 9M APP/PS1 astrocytes, however, showed more hyperactivity compared to WT, characterized by increased spontaneous calcium transients that were longer in duration. Our data also revealed an effect of aging, as 9M astrocytes overall showed an increase in calcium activity compared to 6M astrocytes. Subsequent calcium-wave analysis showed an increase in sequential calcium transients (i.e., calcium waves) in 9M astrocytes, suggesting increased network activity ex vivo. Further analysis using null models revealed that this network effect is caused by chance, due to the increased number of spontaneous transients. Our findings show that alterations in calcium signaling in individual hippocampal astrocytes of APP/PS1 mice are subject to both aging and Aß pathology but these do not lead to a change in astrocyte network activity. These alterations in calcium dynamics of astrocytes may help to understand changes in neuronal physiology leading to cognitive decline and ultimately dementia.

Ecological network assembly: How the regional metaweb influences local food webs.

Local food webs result from a sequence of colonisations and extinctions by species from the regional pool or metaweb, that is, the assembly process. Assembly is theorised to be a selective process: whether or not certain species or network structures can persist is partly determined by local processes including habitat filtering and dynamical constraints. Consequently, local food web structure should reflect these processes. The goal of this study was to test evidence for these selective processes by comparing the structural properties of real food webs to the expected distribution given the metaweb. We were particularly interested in ecological dynamics; if the network properties commonly associated with dynamical stability are indeed the result of stability constraints, then they should deviate from expectation in the direction predicted by theory. To create a null expectation, we used the novel approach of randomly assembling model webs by drawing species and interactions from the empirical metaweb. The assembly model permitted colonisation and extinction, and required a consumer species to have at least one prey, but had no habitat type nor population dynamical constraints. Three datasets were used: (a) the marine Antarctic metaweb, with two local food webs; (b) the 50 lakes of the Adirondacks; and (c) the arthropod community from Florida Keys' classic defaunation experiment. Contrary to our expectations, we found that there were almost no differences between empirical webs and those resulting from the null assembly model. Few empirical food webs showed significant differences with network properties, motif representations and topological roles. Network properties associated with stability did not deviate from expectation in the direction predicted by theory. Our results suggest that-for the commonly used metrics we considered-local food web structure is not strongly influenced by dynamical nor habitat restrictions. Instead, the structure is inherited from the metaweb. This suggests that the network properties typically attributed as causes or consequences of ecological stability are instead a by-product of the assembly process (i.e. spandrels), and may potentially be too coarse to detect the true signal of dynamical constraint.

Las redes tróficas locales son el resultado de una secuencia de eventos de colonización y extinción de especies que provienen del conjunto regional de especies o metaweb, es decir, el proceso de ensamble. Se teoriza que el ensamble es un proceso selectivo: si ciertas especies o estructuras de red pueden persistir o no está determinado en parte por procesos locales, incluido el filtrado del hábitat y las limitaciones dinámicas. En consecuencia, la estructura de la red trófica local debe reflejar estos procesos. El objetivo de este estudio fue analizar la evidencia de estos procesos selectivos comparando las propiedades estructurales de redes tróficas empíricas (locales) con la distribución esperada dada la metaweb. Nuestro particular interés fue la dinámica ecológica: si las propiedades de la red comúnmente asociadas con la estabilidad dinámica son el resultado de restricciones de estabilidad, entonces deberían desviarse de las expectativas en la dirección predicha por la teoría. Para crear una expectativa nula utilizamos el enfoque novedoso de ensamblar redes utilizando un modelo estocástico o 'modelo de ensamble nulo' que extrae especies e interacciones de una metaweb empírica. El modelo de ensamble incluye colonización y extinción, y requiere que los consumidores tengan al menos una presa, pero no tiene restricciones acerca del tipo de hábitat ni de dinámica de poblaciones. Se utilizaron tres conjuntos de datos: (a) la metaweb antártica marina, con 2 redes tróficas locales; (b) los 50 lagos de Adirondacks; y (c) la comunidad de artrópodos del experimento clásico de defaunación de los Cayos de la Florida. Contrariamente a lo esperado, encontramos que casi no hubo diferencias entre las redes empíricas (locales) y las resultantes del modelo de ensamble nulo. Pocas redes tróficas empíricas mostraron diferencias significativas con las propiedades de la red, los motivos y los roles topológicos. Las propiedades de la red asociadas con la estabilidad no se desviaron de las expectativas en la dirección predicha por la teoría. Nuestros resultados sugieren que-para las métricas de uso común que consideramos-la estructura de la red trófica local no está fuertemente influenciada por restricciones dinámicas o de hábitat. En cambio, la estructura se hereda de la metaweb. Esto sugiere que las propiedades de la red típicamente atribuidas como causas o consecuencias de la estabilidad ecológica son, en cambio, un subproducto del proceso de ensamble y podrían no tener la suficiente potencia para detectar la verdadera señal de restricción dinámica.

Comparing spatial null models for brain maps.

Technological and data sharing advances have led to a proliferation of high-resolution structural and functional maps of the brain. Modern neuroimaging research increasingly depends on identifying correspondences between the topographies of these maps; however, most standard methods for statistical inference fail to account for their spatial properties. Recently, multiple methods have been developed to generate null distributions that preserve the spatial autocorrelation of brain maps and yield more accurate statistical estimates. Here, we comprehensively assess the performance of ten published null frameworks in statistical analyses of neuroimaging data. To test the efficacy of these frameworks in situations with a known ground truth, we first apply them to a series of controlled simulations and examine the impact of data resolution and spatial autocorrelation on their family-wise error rates. Next, we use each framework with two empirical neuroimaging datasets, investigating their performance when testing (1) the correspondence between brain maps (e.g., correlating two activation maps) and (2) the spatial distribution of a feature within a partition (e.g., quantifying the specificity of an activation map within an intrinsic functional network). Finally, we investigate how differences in the implementation of these null models may impact their performance. In agreement with previous reports, we find that naive null models that do not preserve spatial autocorrelation consistently yield elevated false positive rates and unrealistically liberal statistical estimates. While spatially-constrained null models yielded more realistic, conservative estimates, even these frameworks suffer from inflated false positive rates and variable performance across analyses. Throughout our results, we observe minimal impact of parcellation and resolution on null model performance. Altogether, our findings highlight the need for continued development of statistically-rigorous methods for comparing brain maps. The present report provides a harmonised framework for benchmarking and comparing future advancements.

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis.

Null models are useful for assessing whether a dataset exhibits a non-trivial property of interest. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fMRI) time series. Interpretation of null-model testing in this context may not be straightforward because (i) null hypotheses associated to different null models are sometimes unclear and (ii) fMRI metrics might be 'trivial', i.e. preserved under the null hypothesis, and still be useful in neuroimaging applications. In this commentary, we review several commonly used null models of fMRI time series and discuss the interpretation of the corresponding tests. We argue that, while null-model testing allows for a better characterization of the statistical properties of fMRI time series and associated metrics, it should not be considered as a mandatory validation step to assess their relevance in representing brain functional dynamics.

Minimal models provide maximally parsimonious explanations.

We are delighted that Diniz-Filho et al. agree with the main premise of our paper, and we welcome their critique, as constructive debate will help foster a better understanding of size evolution on islands. Our perspective on each of their criticisms is discussed in greater detail below.

Ecophylogenetics redux.

Species' evolutionary histories shape their present-day ecologies, but the integration of phylogenetic approaches in ecology has had a contentious history. The field of ecophylogenetics promised to reveal the process of community assembly from simple indices of phylogenetic pairwise distances - communities shaped by environmental filtering were composed of closely related species, whereas communities shaped by competition were composed of less closely related species. However, the mapping of ecology onto phylogeny proved to be not so straightforward, and the field remains mired in controversy. Nonetheless, ecophylogenetic methods provided important advances across ecology. For example the phylogenetic distances between species is a strong predictor of pest and pathogen sharing, and can thus inform models of species invasion, coexistence and the disease dilution/amplification effect of biodiversity. The phylogenetic structure of communities may also provide information on niche space occupancy, helping interpret patterns of facilitation, succession and ecosystem functioning - with relevance for conservation and restoration - and the dynamics among species within foodwebs and metacommunities. I suggest leveraging advances in our understanding of the process of evolution on phylogenetic trees would allow the field to progress further, while maintaining the essence of the original vision that proved so seductive.

Too simple models may predict the island rule for the wrong reasons.

Biddick & Burns (2021) proposed a null/neutral model that reproduces the island rule as a product of random drift. We agree that it is unnecessary to assume adaptive processes driving island dwarfing or gigantism, but several flaws make their approach unrealistic and thus unsuitable as a stochastic model for evolutionary size changes.

Bacterial dispersal and drift drive microbiome diversity patterns within a population of feral hindgut fermenters.

Studies of microbiome variation in wildlife often emphasize host physiology and diet as proximate selective pressures acting on host-associated microbiota. In contrast, microbial dispersal and ecological drift are more rarely considered. Using amplicon sequencing, we characterized the bacterial microbiome of adult female (n = 86) Sable Island horses (Nova Scotia, Canada) as part of a detailed individual-based study of this feral population. Using data on sampling date, horse location, age, parental status, and local habitat variables, we contrasted the ability of spatiotemporal, life history, and environmental factors to explain microbiome diversity among Sable Island horses. We extended inferences made from these analyses with both phylogeny-informed and phylogeny-independent null modelling approaches to identify deviations from stochastic expectations. Phylogeny-informed diversity measures were correlated with spatial and local habitat variables, but null modelling results suggested that heterogeneity in ecological drift, rather than differential selective pressures acting on the microbiome, was responsible for these correlations. Conversely, phylogeny-independent diversity measures were best explained by host spatial and social structure, suggesting that taxonomic composition of the microbiome was shaped most strongly by bacterial dispersal. Parental status was important but correlated with measures of ß-dispersion rather than ß-diversity (mares without foals had lower alpha diversity and more variable microbiomes than mares with foals). Our results suggest that between host microbiome variation within the Sable Island horse population is driven more strongly by bacterial dispersal and ecological drift than by differential selective pressures. These results emphasize the need to consider alternative ecological processes in the study of microbiomes.

Scale-resolved analysis of brain functional connectivity networks with spectral entropy.

Functional connectivity is derived from inter-regional correlations in spontaneous fluctuations of brain activity, and can be represented in terms of complete graphs with continuous (real-valued) edges. The structure of functional connectivity networks is strongly affected by signal processing procedures to remove the effects of motion, physiological noise and other sources of experimental error. However, in the absence of an established ground truth, it is difficult to determine the optimal procedure, and no consensus has been reached on the most effective approach to remove nuisance signals without unduly affecting the network intrinsic structural features. Here, we use a novel information-theoretic approach, based on von Neumann entropy, which provides a measure of information encoded in the networks at different scales. We also define a measure of distance between networks, based on information divergence, and optimal null models appropriate for the description of functional connectivity networks, to test for the presence of nontrivial structural patterns that are not the result of simple local constraints. This formalism enables a scale-resolved analysis of the distance between a functional connectivity network and its maximally random counterpart, thus providing a means to assess the effects of noise and image processing on network structure. We apply this novel approach to address a few open questions in the analysis of brain functional connectivity networks. Specifically, we demonstrate a strongly beneficial effect of network sparsification by removal of the weakest links, and the existence of an optimal threshold that maximizes the ability to extract information on large-scale network structures. Additionally, we investigate the effects of different degrees of motion at different scales, and compare the most popular processing pipelines designed to mitigate its deleterious effect on functional connectivity networks. We show that network sparsification, in combination with motion correction algorithms, dramatically improves detection of large scale network structure.

Rare species of wood-inhabiting fungi are not local.

Wood-inhabiting fungal communities are a diverse and ecologically critical part of forest ecosystems, yet the spatial structure of fungal biodiversity in these ecosystems is largely unknown. Legislation allowed harvesting of deadwood from temperate rainforests on conservation lands in New Zealand following Cyclone Ita in 2014. Harvesting guidelines specified widely spread harvesting, on the assumption that rare fungal species may be highly spatially restricted, but were not based on quantitative assessment. We sampled fungi in and on logs of Dacrydium cupressinum (Podocarpaceae) a long-lived, common, canopy tree in lowland New Zealand forests. DNA was extracted from 81 logs varying in decay state across a 40 km long region of West Coast (South Island) forests, and sequenced using general fungal primers for metabarcoding to identify OTUs (operational taxonomic units). We examined three axes of rarity: occupancy, dominance when present, and niche breadth (as spatial extent and decay state specialization). Low-occupancy fungi were common, including a group of infrequently occurring but dominant when present fungi, the majority of which were Ascomycota. Despite this, there was an overall positive relationship between occupancy and dominance. Widespread, dominant fungi were most commonly Basidiomycota. Testing all fungal OTUs, there were no more fungi with maximum range sizes < 4 km than would be expected at random. Of the 351 low-occupancy OTUs found two to four times, only 12 had maximum range sizes < 900 m, and there was no more spatial restriction at scales < 900 m than would be expected by random chance, although there was some evidence of niche breadth restriction based on decay state similarity. The results show that fungal communities in deadwood are highly diverse, and include many rare taxa. Nonetheless, the lack of fungal OTUs with spatial restriction at scales < 900 m suggests that spatially dispersed timber harvesting will not mitigate risks of harvesting to rare fungal biodiversity.

Population asynchrony alone does not explain stability in species-rich soil animal assemblages: The stabilizing role of forest age on oribatid mite communities.

The importance of microbial and plant communities in the control of the diversity and structure of soil animal communities has been clarified over the last decade. Previous research focused on abiotic factors, niche separation and spatial patterns. Significant gaps still exist in our knowledge of the factors that control the stability of these communities over time. We analysed a 9-year dataset from the national Long-term Ecological Research Network of Latvia. We focused on 117 oribatid species from three Scots pine forests of different age (<40, 65 and >150 years) and structure. For each forest type, 100 samples were collected each year, providing very high replication and long time series for a soil community. We assessed different aspects of stability: we used a dynamic null model, parameterized on observed growth rates, to test the hypothesis that asynchrony in species populations stabilizes total community size; we also analysed alpha and beta diversity over time to test the hypothesis that temporal variation in species composition and relative abundances is controlled by forest attributes. Real communities can be more stable than their stochastic counterparts if species are asynchronous, confirming for the first time the role of asynchrony in stabilizing soil communities. Yet, while some real communities were more stable and had higher abundance and growth rates than others, they were not necessarily more asynchronous than the less stable communities. Species composition and relative abundances were also less variable in the more stable communities. Species asynchrony generally stabilizes species-rich communities but is not sufficient to explain the different levels of stability between forests. Forest age is a key factor explaining the different levels of overyielding and so stability. Data suggest that both asynchrony and high diversity of microhabitat structure of Scots pine forests promote the stability of soil animal communities.

Effect of ecological factors on fine-scale patterns of social structure in African lions.

Environmental variations can influence the extent to which individuals interact with other individuals by changing the value of grouping. It is well known that many species can form and disband groups, often in response to the distribution and abundance of resources. While previous studies showed that resources influence the broad-scale structure of animal groups, knowledge gaps remain on whether they affect fine-scale patterns of association among individuals within groups. We quantify association patterns in African lions while simultaneously monitoring the abundance and distribution of prey. We test how social and ecological factors, including individual trait (age, sex, reproductive state) similarity and prey availability (prey abundance, dispersion, herd size and body size) affect within-pride social structure in African lions. We found that individual decisions about associates depended on resource availability with individuals associating equally across all members of the pride when prey herds were scarce, aggregated or large bodied, and associating more exclusively (in subgroups of preferred associates) when prey herds were abundant, dispersed or small bodied. Individuals within lion prides seemed to be buffering against changes in prey availability by modulating their strength and density of connections with conspecifics when prides split into subgroups. The strength and density of connections among individuals within subgroups was greater when prey herds were large and lower when prey herds were dispersed or are large bodied. Our findings suggest that individual lions are making social decisions at both the subgroup level and the pride level, with decisions representing putatively fitness-enhancing strategies. Individuals were typically shifting between having few strong connections and having many weaker connections depending on prevailing ecological conditions, with prey abundance, dispersion and body size having the greatest impact on decisions about splitting into subgroups. The maintenance of connections within prides and subgroups in the face of ecological change suggests that the fission-fusion nature of lion prides might be essential for the long-term maintenance of social connections even when short-term conditions do not allow them. More broadly, our study reveals how fission-fusion dynamics and ecological factors can simultaneously have an effect on animals across multiple levels of sociality.

Increasing importance of niche versus neutral processes in the assembly of plant-herbivore networks during succession.

Recent studies suggest that the assembly of trophic interaction networks is the result of both niche (deterministic and selective) and neutral (stochastic) processes, but we know little about their relative importance. Succession following disturbance offers a good opportunity to address this question. Studies of single-trophic guilds suggest that, shortly after a disturbance, such as a fire, neutral assembly processes (e.g. colonisation events) dominate; whereas, niche processes (selection) become more and more important as succession proceeds. Building on these observations, we predict similar changes in interaction networks during succession, with a shift from stochastic toward selective interactions. To test this, we studied succession of plant-herbivorous insect networks in South Africa after a fire. We sampled a total of 385 herbivorous arthropod species and 92 plant species. For different successional stages and spatial grain sizes, we used network descriptors to estimate plant-herbivore specificity and partner fidelity of plant and herbivore species across networks (i.e. localities). We compared the observed network descriptors to neutral models, and then differentiated selective species (associated with similar partner species in different networks) from neutral species (associated at random with their partners). Our results suggest that specialisation, partner fidelity and the proportion of selective species of plants and herbivores increased with succession, which is consistent with the hypothesis that niche-based processes prevail over neutral processes as succession proceeds. However, in all the successional stages, the majority of species were neutral species, which pinpoints the importance of opportunistic interactions in the assembly of trophic networks.

A Global-Scale Mid-Domain Effect Cannot Explain the Latitudinal Gradient in Species Richness.

The latitudinal gradient in species richness is perhaps the most fundamental pattern of biodiversity, yet a satisfactory explanation for its existence remains elusive. A geometric "mid-domain effect" is often cited as having potential to help explain the latitudinal gradient in species richness, but the logic underpinning this hypothesis is apparently built on two incorrect assumptions: (1) that a given great circle-usually the Equator-can constitute the geometric "mid-domain" of the Earth's surface, and (2) that geophysical or bioclimatic boundaries are of geometric relevance in the context of a global-scale mid-domain effect. This article gives a brief overview of the relevant literature and history of thought on the subject, and describes in clear and simple terms why a global-scale mid-domain effect cannot arise, and thus cannot possibly represent a mechanistic basis for the latitudinal gradient in species richness. Explicit acknowledgement of this fact is of great importance, as it allows us to dispense with a commonly cited hypothesis for the latitudinal gradient in species richness.

Specialization and niche overlap across spatial scales: Revealing ecological factors shaping species richness and coexistence in Australian songbirds.

Ecological specialization enables the partitioning of resources and thus can facilitate the coexistence of species and promote higher species richness. Specialization and niche partitioning are expected to exert a decisive influence on local spatial scales, while species richness at regional scales should be shaped mostly by historical factors and abiotic conditions. Moreover, specialization is expected to be particularly important in communities that are exceptionally species rich for their environmental conditions. Concurrently, niche overlap in these communities should be minimized to enable species coexistence. We tested these hypotheses by studying specialization-richness relationship and niche overlap in assemblages of 298 species of songbirds (Passeriformes) across Australia. We used local (2-6 ha) to regional (bioregions) spatial scales and detailed data on habitat, diet and foraging behaviour (method, substrate and stratum). We expected the richness-specialization relationship to be particularly strong (a) on local spatial scales and (b) in communities exceptionally species rich for given environmental conditions (approximated by moisture and vegetation complexity). We also expected (c) low niche overlap in assemblages with specialized species. Only the third prediction was partly supported. First, while the specialization and species richness were often positively related, the strength and the direction of the relationship changed between traits and across spatial scales. The strength of the specialization-richness relationship was consistently positive only in foraging stratum, and it increased towards smaller spatial scales only in case of habitat and diet. Simultaneously, species in local communities demonstrated high overlap in habitat and diet. Second, we did not find particularly strong specialization-richness relationships in exceptionally species-rich communities. Third, we found the expected negative relationship between specialization and overlap in foraging stratum and substrate (in local communities), suggesting that species partition ecological space locally in terms of where they find food. Our expectations were only weakly supported. Specialization on foraging stratum was probably important in facilitating species coexistence. Conversely, although species were often specialized on habitat and diet, high overlap in these traits did not preclude their local coexistence. Overall, specialization and overlap in foraging traits were more important for species coexistence than habitat or diet.