Soil microbial subcommunity assembly mechanisms are highly variable and intimately linked to their ecological and functional traits.

Revealing the mechanisms underlying soil microbial community assembly is a fundamental objective in molecular ecology. However, despite increasing body of research on overall microbial community assembly mechanisms, our understanding of subcommunity assembly mechanisms for different prokaryotic and fungal taxa remains limited. Here, soils were collected from more than 100 sites across southwestern China. Based on amplicon high-throughput sequencing and iCAMP analysis, we determined the subcommunity assembly mechanisms for various microbial taxa. The results showed that dispersal limitation and homogenous selection were the primary drivers of soil microbial community assembly in this region. However, the subcommunity assembly mechanisms of different soil microbial taxa were highly variable. For instance, the contribution of homogenous selection to Crenarchaeota subcommunity assembly was 70%, but it was only around 10% for the subcommunity assembly of Actinomycetes, Gemmatimonadetes and Planctomycetes. The assembly of subcommunities including microbial taxa with higher occurrence frequencies, average relative abundance and network degrees, as well as wider niches tended to be more influenced by homogenizing dispersal and drift, but less affected by heterogeneous selection and dispersal limitation. The subcommunity assembly mechanisms also varied substantially among different functional guilds. Notably, the subcommunity assembly of diazotrophs, nitrifiers, saprotrophs and some pathogens were predominantly controlled by homogenous selection, while that of denitrifiers and fungal pathogens were mainly affected by stochastic processes such as drift. These findings provide novel insights into understanding soil microbial diversity maintenance mechanisms, and the analysis pipeline holds significant value for future research.

Exploring the environmental influences and community assembly processes of bacterioplankton in a subtropical coastal system: Insights from the Beibu Gulf in China.

Due to rapid urbanization, the Beibu Gulf, a semi-closed gulf in the northwestern South China Sea, faces escalating ecological and environmental threats. Understanding the assembly mechanisms and driving factors of bacterioplankton in the Beibu Gulf is crucial for preserving its ecological functions and services. In the present study, we investigated the spatiotemporal dynamics of bacterioplankton communities and their assembly mechanisms in the Beibu Gulf based on the high-throughput sequencing of the bacterial 16 S rRNA gene. Results showed significantly higher bacterioplankton diversity during the wet season compared to the dry season. Additionally, distinct seasonal variations in bacterioplankton composition were observed, characterized by an increase in Cyanobacteria and Thermoplasmatota and a decrease in Proteobacteria and Bacteroidota during the wet season. Null model analysis revealed that stochastic processes governed bacterioplankton community assembly in the Beibu Gulf, with drift and homogenizing dispersal dominating during the dry and wet seasons, respectively. Enhanced deterministic assembly of bacterioplankton was also observed during the wet season. Redundancy and random forest model analyses identified the physical properties (e.g., temperature) and nutrient content (e.g., nitrate) of water as primary environmental drivers influencing bacterioplankton dynamics. Moreover, variation partitioning and distance-decay of similarity revealed that environmental filtering played a significant role in shaping bacterioplankton variations in this rapidly developed coastal ecosystem. These findings advance our understanding of bacterioplankton assembly in coastal ecosystems and establish a theoretical basis for effective ecological health management amidst ongoing global changes.

Use of trophic ecology of omnivorous fish and abiotic factors as supporting tools for assessing environmental impacts in a neotropical river.

The study of diet is one of the mechanisms by which competition for resources between species that cohabit in the same ecosystem can be inferred. Therefore, the relationships of the indices that measure specialization in the diet of fish species are necessary to characterize the nutritional quality of these populations and the ecosystem's environmental health. Three species of catfish were selected: one invasive (Clarias gariepinus) and two natives (Trachelyopterus striatulus and Rhamdia quelen), with similar distribution along the Guapi-Macacu River, in the Guapimirim Protection Area (Rio de Janeiro). Fifty-nine catfish of the three species were collected in total, along 32 collection points in the Guapi-Macacu River in two periods (dry and rainy) in 2018. Non-parametric statistics showed the partition of resources between species and the influence of abiotic factors (temperature, pH, transparency, and dissolved oxygen) contributing to the selection of available resources in the environment. Diet-related indices-repletion index (RI), condition factor (K), niche width, and trophic position (TP) of the specimens collected-contributed to measuring the nutritional status of each of these catfish species, showing that R. quelen has a relationship between RI and K, tending to absorb and metabolize nutrients faster than other species. In addition, the invasive species occupies a wide range of TPs compared to native species, confirming its feeding plasticity. On the contrary, T. striatulus needs large amounts of terrestrial insects to maintain its poor condition factor. Also, the RI showed direct influences of abiotic variables, with the temperature being the most prominent. Our results suggest that the invasive species can benefit from this environment that shows signs of environmental degradation.

The siren song of so-called evidence: Why the evidence for social ecology models is not as strong as we think.

Ecological competition models from biology have been adopted for the study of a wide variety of social entities, including workplace organizations and voluntary associations.Despite their popularity, a number of fundamental challenges to these models have not been sufficiently recognized or addressed. As a result, it's possible that some apparently supportive evidence for ecological competition is in fact the outcome of chance or other processes. We propose a permutation test to compare observed evidence for ecological competition against an appropriate counterfactual population. To demonstrate our approach and validate our concern about the quality of evidence for ecological competition models, we apply the permutation test to one specific case. The results indicate that K-correlation values that have been taken as evidence for a well-established model, the Ecology of Affiliation, are quite common even in the absence of ecological competition. We conclude that the existing evidence for social ecology models may not be as reliable as commonly believed due to the disconnect between theory and empirical testing.

Diversity and ecological assembly process of aerobic anoxygenic phototrophic bacteria in a low irradiation area, Three Gorges Reservoir.

Aerobic anoxygenic phototrophic bacteria (AAPB) are significant bacterial groups in aquatic ecosystems, known for their rapid growth and photoheterotrophic characteristics. However, the distribution and ecological assembly process of AAPB in low irradiation freshwater basins remain unclear, warranting further investigation. In this study, we present the diversity, abundance, spatial variations, ecological process, and community interaction of AAPB in sediment of Three Gorges Reservoir (TGR) under low irradiation. Our findings demonstrate the dominant genera of AAPB community that exist in the TGR area also are appeared in different waters, with some regional preference. Moreover, the concentration of pufM gene, an indicator for AAPB, maintains a consistently high numerical level ranging from (2.21 ± 0.44) × 104 to (9.98 ± 0.30) × 107 gene copies/g. Although solar irradiation is suggested as the major factor affecting AAPB, it remains unclear whether and how AAPB differ between regions due to varying solar irradiation levels. Our results show spatial differences between total bacteria and AAPB communities, with significant differences observed only in AAPB. Geographical and environmental factor contributed less than 10% to the spatial difference of community, with sediment type and environmental factors being the key factors influencing microbial community structure. The stochastic process plays a dominant role in the aggregation and replacement of AAPB communities, among which the most contribution is dispersal limitation. For AAPB network, Yoonia and Gemmobacter are the hubs for modules. Those results valuable insights into the AAPB communities in TGR with low irradiation.

Relaxed Selection and the Rapid Evolution of Reproductive Genes.

Evolutionary genomic studies find that reproductive protein genes, those directly involved in reproductive processes, diversify more rapidly than most other gene categories. Strong postcopulatory sexual selection acting within species is the predominant hypothesis proposed to account for the observed pattern. Recently, relaxed selection due to sex-specific gene expression has also been put forward to explain the relatively rapid diversification. We contend that relaxed selection due to sex-limited gene expression is the correct null model for tests of molecular evolution of reproductive genes and argue that it may play a more significant role in the evolutionary diversification of reproductive genes than previously recognized. We advocate for a re-evaluation of adaptive explanations for the rapid diversification of reproductive genes.

Changes in plant community assembly from patchy degradation of grasslands and grazing by different-sized herbivores.

Grassland degradation caused by increases in livestock grazing threatens a variety of ecosystem services. Understanding changes in plant community assembly during the process of grassland degradation in the presence of grazing is important to help restore degraded grasslands worldwide but has received little attention thus far. The grassland degradation process is typified by heterogeneous degradation, that is, gradual formation of degraded patches (hereafter "patchy degradation"). Here, we experimentally examined the effects of herbivore grazing and patchy degradation on plant community assembly using nine pairs of non-degraded (intact) and patch-degraded (fragmented) grasslands subject to grazing by different-sized herbivores (i.e., NG, no grazing; SG, sheep grazing; CG, cattle grazing) over 4 years. Using a null-model approach, we estimated the relative magnitude of deterministic processes of community assembly by comparing the observed and expected ß-diversity. We found that in the absence of herbivore grazing, deterministic processes played a greater role in community assembly, regardless of whether patchy degradation had occurred. However, the deterministic processes resulted in plant communities being more spatially similar in non-degraded grasslands while being more dissimilar in patchy degraded grasslands. Compared with non-degraded grasslands, species with strong competitive abilities (i.e., Leymus chinensis) were less dominant in patchy degraded grasslands, indicating relaxed competition and a reduced role of species interactions over plant communities. Instead, patchy degradation added the role of environmental variables over plant communities. SG consistently promoted more stochastic plant community assembly in both non-degraded and patch-degraded grasslands, while CG promoted more stochastic plant community assembly only in the non-degraded state, having no effect in the patch-degraded state. Our study offers important insights into changes in plant community assembly during ongoing patch-degradation of grasslands, indicating the role of increased environmental filtering of soil and reduced species interactions in driving plant community dynamics with increasing grassland patchy degradation. We also uncovered an herbivore species-specific effect on plant community assembly during the process of grassland degradation, which will better inform and improve future grassland restoration planning efforts.

Factors at multiple scales drive parasite community structure.

Understanding how ecological communities are assembled remains a key goal of ecosystem ecology. Because communities are hierarchical, factors acting at multiple scales can contribute to patterns of community structure. Parasites provide a natural system to explore this idea, as they exist as discrete communities within host individuals, which are themselves part of a community and metacommunity. We aimed to understand the relative contribution of multi-scale drivers in parasite community assembly and assess how patterns at one level may mask those occurring at another. Specifically, we wanted to disentangle patterns caused by passive sampling from those determined by ecological drivers, and how these vary with scale. We applied a Markov Random Fields model and assessed measures of ß-diversity and nestedness for 420 replicate parasite infracommunities (parasite assemblages in host individuals) across two freshwater mussel host species, three sites and two time periods, comparing our results to simulations from four different ecologically relevant null models. We showed that ß-diversity between sites (explaining 25% of variation in parasite distribution) and host species (41%) is greater than expected, and ß-diversity between individual hosts is smaller than expected, even after accounting for parasite prevalence and characteristics of host individuals. Furthermore, parasite communities were significantly less nested than expected once parasite prevalence and host characteristics were both accounted for, but more nested than expected otherwise, suggesting a degree of modularity at the within-host level that is masked if underlying host and parasite characteristics are not taken into account. The Markov Random Fields model provided evidence for possible competitive within-host parasite interactions, providing a mechanism for the observed infracommunity modularity. An integrative approach that examines factors at multiple scales is necessary to understand the composition of ecological communities. Furthermore, patterns at one level can alter the interpretation of ecologically important drivers at another if variation at higher scales is not accounted for.

Inferring microbial community assembly in an urban river basin through geo-multi-omics and phylogenetic bin-based null-model analysis of surface water.

Understanding the community assembly process is a central issue in microbial ecology. In this study, we analyzed the community assembly of particle-associated (PA) and free-living (FL) surface water microbiomes in 54 sites from the headstream to the river mouth of an urban river in Japan, the river basin of which has the highest human population density in the country. Analyses were conducted from two perspectives: (1) analysis of deterministic processes considering only environmental factors using a geo-multi-omics dataset and (2) analysis of deterministic and stochastic processes to estimate the contributions of heterogeneous selection (HeS), homogeneous selection (HoS), dispersal limitation (DL), homogenizing dispersal (HD), and drift (DR) as community assembly processes using a phylogenetic bin-based null model. The variation in microbiomes was successfully explained from a deterministic perspective by environmental factors, such as organic matter-related, nitrogen metabolism, and salinity-related parameters, using multivariate statistical analysis, network analysis, and habitat prediction. In addition, we demonstrated the dominance of stochastic processes (DL, HD, and DR) over deterministic processes (HeS and HoS) in community assembly from both deterministic and stochastic perspectives. Our analysis revealed that as the distance between two sites increased, the effect of HoS sharply decreased while the effect of HeS increased, particularly between upstream and estuary sites, indicating that the salinity gradient could potentially enhance the contribution of HeS to community assembly. Our study highlights the importance of both stochastic and deterministic processes in community assembly of PA and FL surface water microbiomes in urban riverine ecosystems.

Local stressors mask the effects of warming in freshwater ecosystems.

Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.

Statistical testing in transcriptomic-neuroimaging studies: A how-to and evaluation of methods assessing spatial and gene specificity.

Multiscale integration of gene transcriptomic and neuroimaging data is becoming a widely used approach for exploring the molecular underpinnings of large-scale brain organization in health and disease. Proper statistical evaluation of determined associations between imaging-based phenotypic and transcriptomic data is key in these explorations, in particular to establish whether observed associations exceed "chance level" of random, nonspecific effects. Recent approaches have shown the importance of statistical models that can correct for spatial autocorrelation effects in the data to avoid inflation of reported statistics. Here, we discuss the need for examination of a second category of statistical models in transcriptomic-neuroimaging analyses, namely those that can provide "gene specificity." By means of a couple of simple examples of commonly performed transcriptomic-neuroimaging analyses, we illustrate some of the potentials and challenges of transcriptomic-imaging analyses, showing that providing gene specificity on observed transcriptomic-neuroimaging effects is of high importance to avoid reports of nonspecific effects. Through means of simulations we show that the rate of reported nonspecific effects (i.e., effects that cannot be specifically linked to a specific gene or gene-set) can run as high as 60%, with only less than 5% of transcriptomic-neuroimaging associations observed through ordinary linear regression analyses showing both spatial and gene specificity. We provide a discussion, a tutorial, and an easy-to-use toolbox for the different options of null models in transcriptomic-neuroimaging analyses.

Increased adoption of best practices in ecological forecasting enables comparisons of forecastability.

Near-term iterative forecasting is a powerful tool for ecological decision support and has the potential to transform our understanding of ecological predictability. However, to this point, there has been no cross-ecosystem analysis of near-term ecological forecasts, making it difficult to synthesize diverse research efforts and prioritize future developments for this emerging field. In this study, we analyzed 178 near-term (≤10-yr forecast horizon) ecological forecasting papers to understand the development and current state of near-term ecological forecasting literature and to compare forecast accuracy across scales and variables. Our results indicated that near-term ecological forecasting is widespread and growing: forecasts have been produced for sites on all seven continents and the rate of forecast publication is increasing over time. As forecast production has accelerated, some best practices have been proposed and application of these best practices is increasing. In particular, data publication, forecast archiving, and workflow automation have all increased significantly over time. However, adoption of proposed best practices remains low overall: for example, despite the fact that uncertainty is often cited as an essential component of an ecological forecast, only 45% of papers included uncertainty in their forecast outputs. As the use of these proposed best practices increases, near-term ecological forecasting has the potential to make significant contributions to our understanding of forecastability across scales and variables. In this study, we found that forecastability (defined here as realized forecast accuracy) decreased in predictable patterns over 1-7 d forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in forecastability, while more distantly related variables (i.e., pollen and evapotranspiration) exhibited significantly different patterns. Increasing use of proposed best practices in ecological forecasting will allow us to examine the forecastability of additional variables and timescales in the future, providing a robust analysis of the fundamental predictability of ecological variables.

Random placement models explain species richness and dissimilarity of frog assemblages within Atlantic Forest fragments.

Understanding the effects of random versus niche-based processes on biodiversity patterns is a central theme in ecology, and an important tool for predicting effects of habitat loss and fragmentation on biodiversity. We investigated the predictive power of random processes to explain species richness and species dissimilarity of amphibian assemblages in a fragmented tropical landscape of the Atlantic Forest of South America. We analyzed a large database of amphibian abundance and occupancy, sampled in 21 forest fragments ranging in size from 1.9 to 619 ha. We compared observed species richness and species dissimilarity with the outcomes of two null (random placement) models: 1- the traditional Coleman's area-based model and 2- an abundance-based model (based on the number of individuals observed in each fragment). We applied these models for all species combined, and separately for forest-dependent and habitat-generalist species. The abundance-based model fitted the observed species richness data better than the area-based model for all species, forest-dependent species, and generalist species. The area-based and the abundance-based models were also able to significantly explain species dissimilarity for all species and for generalists, but not for forest dependent species. The traditional area-based model assigned too many individuals to large fragments, thus failing to accurately explain species richness within patches across the landscape. Although niche-based processes may be important to structuring the regional pool of species in fragmented landscapes, our results suggest that part of the variation in species richness and species dissimilarity can be successfully explained by random placement models, especially for generalist species. Evaluating which factors cause variation in the number of individuals among patches should be a focus in future studies aiming to understand biodiversity patterns in fragmented landscapes.

Compreender os efeitos de processos aleatórios versus processos baseados em nicho nos padrões de biodiversidade é um tema central em ecologia e uma ferramenta importante para prever os efeitos da perda e fragmentação de habitat na biodiversidade. Nós investigamos o poder preditivo de processos aleatórios para explicar a riqueza e a dissimilaridade de espécies de assembleias de anfíbios em uma paisagem fragmentada tropical da Mata Atlântica da América do Sul. Analisamos um grande conjunto de dados de abundância e ocupação de anfíbios, amostrados em 21 fragmentos florestais com tamanhos de 1.9 a 619 ha. Comparamos a riqueza e a dissimilaridade de espécies observadas com os resultados de dois modelos nulos (posicionamento aleatório): 1- o modelo tradicional baseado em área de Coleman e 2 - um modelo baseado em abundância (com base no número de indivíduos observados em cada fragmento). Aplicamos esses modelos para todas as espécies combinadas e separadamente para espécies dependentes de floresta e espécies generalistas de habitat. O modelo baseado em abundância ajustou-se melhor aos dados observados de riqueza de espécies do que o modelo baseado em área para todas as espécies, espécies dependentes de floresta e espécies generalistas. Os modelos baseados em área e em abundância também foram capazes de explicar significativamente a dissimilaridade de espécies para todas as espécies e para generalistas, mas não para espécies dependentes de floresta. O modelo tradicional baseado em área atribuiu muitos indivíduos a grandes fragmentos, falhando assim em explicar com precisão a riqueza de espécies dentro de manchas na paisagem. Embora processos baseados em nicho possam ser importantes para estruturar o conjunto regional de espécies em paisagens fragmentadas, nossos resultados sugerem que parte da variação na riqueza e dissimilaridade de espécies pode ser explicada com sucesso por modelos de posicionamento aleatório, especialmente para espécies generalistas. Avaliar quais fatores causam variação no número de indivíduos entre manchas deve ser um foco em estudos futuros que visem compreender os padrões de biodiversidade em paisagens fragmentadas.

Are Cenozoic relict species also climatic relicts? Insights from the macroecological evolution of the giant sedges of Carex sect. Rhynchocystis (Cyperaceae).

PREMISE: Most of the Paleotropical flora widely distributed in the Western Palearctic became extinct during the Mio-Pliocene as a result of global geoclimatic changes. A few elements from this Cenozoic flora are believed to remain as relicts in Macaronesia, forming part of the laurel forests. Although the origins of the present species assembly are known to be heterogeneous, it is unclear whether some species should be considered climatic relicts with conserved niches. An ideal group for studying such relict characteristics is a Miocene lineage of Carex sect. Rhynchocystis (Cyperaceae), which comprises four species distributed in mainland Palearctic and Macaronesia. METHODS: We reconstructed the current and past environmental spaces for extant mainland and Macaronesian species, as well as for Pliocene fossils. We also studied the bioclimatic niche evolution. Species distribution modeling and ensemble small modeling were performed to assess the potential distribution over time. RESULTS: Climatic niche analyses and distribution modeling revealed that the ecological requirements of Macaronesian species did not overlap with those of either mainland species or with the Pliocene fossils. Conversely, the niches of mainland species displayed significant similarity and equivalence. CONCLUSIONS: Macaronesian species are not climatic relicts from the Paleotropical flora, but instead seem to have changed the ecological niche of their ancestors. By contrast, despite their ancient divergence (Late Miocene), mainland C. pendula and C. agastachys show conserved niches, with competitive exclusion likely shaping their mostly allopatric ranges.

Rare Bacteria Assembly in Soils Is Mainly Driven by Deterministic Processes.

Rare species are crucial components of the highly diverse soil microbial pool and over-proportionally contribute to the soil functions. However, much remains unknown about their assembling rules. The biogeographic patterns and species aggregations of the rare bacterial biosphere were assessed using 140 soil samples from a gradient of 2000 km across the main tea-producing areas in China. About 96% OTUs with ~40% sequences were classified as rare taxa. The rare bacterial communities were significantly affected by geographical regions and showed distance-decay effects, indicating that the rare bacteria are not cosmopolitan, they displayed a pattern of limited dispersal and were restricted to certain sites. Variation partitioning analysis (VPA) revealed that environmental variation and spatial factors explained 12.5% and 6.4%, respectively, of the variance in rare bacterial community. The Mantel and partial Mantel tests also showed that the environmental factors had stronger (~3 times) impacts than spatial factors. The null model showed that deterministic processes contributed more than stochastic processes in rare bacterial assembly (75% vs. 25%). There is likely an enrichment in ecological functions within the rare biosphere, considering this high contribution of deterministic processes in the assembly. In addition, the assembly of rare taxa was found to be mainly driven by soil pH. Overall, this study revealed that rare bacteria were not cosmopolitan, and their assembly was more driven by deterministic processes. These findings provided a new comprehensive understanding of rare bacterial biogeographic patterns and assembly rules.

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.

Limiting similarity shapes the functional and phylogenetic structure of root neighborhoods in a subtropical forest.

Environmental filtering and limiting similarity mechanisms can simultaneously structure community assemblages. However, how they shape the functional and phylogenetic structure of root neighborhoods remains unclear, hindering the understanding of belowground community assembly processes and diversity maintenance. In a 50-ha plot in a subtropical forest, China, we randomly sampled > 2700 root clusters from 625 soil samples. Focusing on 10 root functional traits measured on 76 woody species, we examined the functional and phylogenetic structure of root neighborhoods and linked their distributions with environmental cues. Functional overdispersion was pervasive among individual root traits (50% of the traits) and accentuated when different traits were combined. Functional clustering (20% of the traits) seemed to be associated with a soil nutrient gradient with thick roots dominating fertile areas whereas thin roots dominated infertile soils. Nevertheless, such traits also were sorted along other environmental cues, showing multidimensional adaptive trait syndromes. Species relatedness also was an important factor defining root neighborhoods, resulting in significant phylogenetic overdispersion. These results suggest that limiting similarity may drive niche differentiation of coexisting species to reduce competition, and that alternative root strategies could be crucial in promoting root neighborhood resource use and species coexistence.

Selective extinctions resulting from random habitat destruction lead to under-estimates of local and regional biodiversity loss in a manipulative field experiment.

Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species-area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.

Discriminating climate, land-cover and random effects on species range dynamics.

Species are reportedly shifting their distributions poleward and upward in several parts of the world in response to climate change. The extent to which other factors might play a role driving these changes is still unclear. Land-cover change is a major cause of distributional changes, but it cannot be discarded that distributional dynamics might be at times caused by other mechanisms (e.g. dispersal, ecological drift). Using observed changes in the distribution of 82 breeding birds in Great Britain between three time periods 1968-72 (t1 ), 1988-91 (t2 ) and 2007-2011 (t3 ), we examine whether observed bird range shifts between t1 -t2 and t1 -t3 are best explained by climate change or land-cover change, or whether they are not distinguishable from what would be expected by chance. We found that range shifts across the rear edge of northerly distributed species in Great Britain are best explained by climate change, while shifts across the leading edge of southerly distributed species are best explained by changes in land-cover. In contrast, at the northern and southern edges of Great Britain, range dynamics could not be distinguished from that expected by chance. The latter observation could be a consequence of boundary effects limiting the direction and magnitude of range changes, stochastic demographic mechanisms neither associated with climate nor land-cover change or with complex interactions among factors. Our results reinforce the view that comprehensive assessments of climate change effects on species range shifts need to examine alternative drivers of change on equal footing and that null models can help assess whether observed patterns could have arisen by chance alone.

Precedent and the Rule of Law.

Courts may reason using precedents in various ways, but not all of them satisfy the rule of law. This article provides two ways that are compatible with this ideal and one which is not. In doing so, the article aims to explain the practice of following precedent in law and to offer criteria for evaluating its value. Two claims are defended. First, courts always have a reason to decide precedent-governed disputes by following precedent. This reason is a minimum requirement of the rule of law, and in some cases this reason may be reinforced in the form of an obligation. Secondly, depending on whether courts have a reason or an obligation to follow precedent, two modes of precedential reasoning may be identified. The article explains them in detail. The modes, together with the considerations that are reasons in favour of them or against them, provide a valuable philosophical foundation of precedent-following in law.