Neighbours and relatives: accounting for spatial distribution when testing causal hypotheses in cultural evolution

Many important and interesting hypotheses about cultural evolution are evaluated using cross-cultural correlations: if knowing one particular feature of a culture (e.g. environmental conditions such as temperature, humidity or parasite load) allows you to predict other features (e.g. language features, religious beliefs, cuisine), it is often interpreted as indicating a causal link between the two (e.g. hotter climates carry greater disease risk, which encourages belief in supernatural forces and favours the use of antimicrobial ingredients in food preparation; dry climates make the production of distinct tones more difficult). However, testing such hypotheses from cross-cultural comparisons requires us to take proximity of cultures into account: nearby cultures share many aspects of their environment and are more likely to be similar in many culturally inherited traits. This can generate indirect associations between environment and culture which could be misinterpreted as signals of a direct causal link. Evaluating examples of cross-cultural correlations from the literature, we show that significant correlations interpreted as causal relationships can often be explained as a result of similarity between neighbouring cultures. We discuss some strategies for sorting the explanatory wheat from the co-varying chaff, distinguishing incidental correlations from causal relationships.

Diversity and extinction risk are inversely related at a global scale

Increases in biodiversity often lead to greater, and less variable, levels of ecosystem functioning. However, whether species are less likely to go extinct in more diverse ecosystems is unclear. We use comprehensive estimates of avian taxonomic, phylogenetic and functional diversity to characterise the global relationship between multiple dimensions of diversity and extinction risk in birds, focusing on contemporary threat status and latent extinction risk. We find that more diverse assemblages have lower mean IUCN threat status despite being composed of species with attributes that make them more vulnerable to extinction, such as large body size or small range size. Indeed, the reduction in current threat status associated with greater diversity far outweighs the increased risk associated with the accumulation of extinction‐prone species in more diverse assemblages. Our results suggest that high diversity reduces extinction risk, and that species conservation targets may therefore best be achieved by maintaining high levels of overall biodiversity in natural ecosystems.

Chemical properties of key metabolites determine the global distribution of lichens

In lichen symbioses, fungal secondary metabolites provide UV protection on which lichen algae such as trebouxiophycean green algae-the most prominent group of photobionts in lichen symbioses-sensitively depend. These metabolites differ in their UV absorbance capability and solvability, and thus vary in their propensity of being leached from the lichen body in humid and warm environments, with still unknown implications for the global distribution of lichens. In this study covering more than 10,000 lichenised fungal species, we show that the occurrence of fungal-derived metabolites in combination with their UV absorbance capability and their probability of being leached in warm and humid environments are important eco-evolutionary drivers of global lichen distribution. Fungal-derived UV protection seems to represent an indirect environmental adaptation in which the lichen fungus invests to protect the trebouxiophycean photobiont from high UV radiation in warm and humid climates and, by doing this, secures its carbon source.

Heterogeneity in African savanna elephant distributions and their impacts on trees in Kruger National Park, South Africa

Though elephants are a major cause of savanna tree mortality and threaten vulnerable tree species, managing their impact remains difficult, in part because relatively little is known about how elephant impacts are distributed throughout space.This is exacerbated by uncertainty about what determines the distribution of elephants themselves, as well as whether the distribution of elephants is even informative for understanding the distribution of their impacts.To better understand the factors that underlie elephant impacts, we modeled elephant distributions and their damage to trees with respect to soil properties, water availability, and vegetation in Kruger National Park, South Africa, using structural equation modeling.We found that bull elephants and mixed herds differed markedly in their distributions, with bull elephants concentrating in sparsely treed basaltic sites close to artificial waterholes and mixed herds aggregating around permanent rivers, particularly in areas with little grass.Surprisingly, we also found that the distribution of elephant impacts, while highly heterogeneous, was largely unrelated to the distribution of elephants themselves, with damage concentrated instead in densely treed areas and particularly on basaltic soils.Results underscore the importance of surface water for elephants but suggest that elephant water dependence operates together with other landscape factors, particularly vegetation community composition and historical management interventions, to influence elephant distributions.

A test of the Niche Variation Hypothesis in a ruminant herbivore

Despite the shared prediction that the width of a population's dietary niche expands as food becomes limiting, the Niche Variation Hypothesis (NVH) and Optimal Foraging Theory (OFT) offer contrasting views about how individuals alter diet selection when food is limited. Classical OFT predicts that dietary preferences do not change as food becomes limiting, so individuals expand their diets as they compensate for a lack of preferred foods. In contrast, the NVH predicts that among-individual variation in cognition, physiology or morphology create functional trade-offs in foraging efficiency, thereby causing individuals to specialize on different subsets of food as food becomes limiting. To evaluate (a) the predictions of the NVH and OFT and (b) evidence for physiological and cognitive-based functional trade-offs, we used DNA microsatellites and metabarcoding to quantify the diet, microbiome and genetic relatedness (a proxy for social learning) of 218 moose Alces alces across six populations that varied in their degree of food limitation. Consistent with both the NVH and OFT, dietary niche breadth increased with food limitation. Increased diet breadth of individuals-rather than increased diet specialization-was strongly correlated with both food limitation and dietary niche breadth of populations, indicating that moose foraged in accordance with OFT. Diets were not constrained by inheritance of the microbiome or inheritance of diet selection, offering support for the little-tested hypothesis that functional trade-offs in food use (or lack thereof) determine whether populations adhere to the predictions of the NVH or OFT. Our results indicate that both the absence of strong functional trade-offs and the digestive physiology of ruminants provide contexts under which populations should forage in accordance with OFT rather than the NVH. Also, because dietary niche width increased with increased food limitation, OFT and the NVH provide theoretical support for the notion that plant-herbivore interaction networks are plastic rather than static, which has important implications for understanding interspecific niche partitioning. Lastly, because population-level dietary niche breadth and calf recruitment are correlated, and because calf recruitment can be a proxy for food limitation, our work demonstrates how diet data can be employed to understand a populations' proximity to carrying capacity.

Introducing the Adverse Ecosystem Service Pathway as a Tool in Ecological Risk Assessment

Soils provide numerous ecosystem services (ESs) such as food production and water purification. These ESs result from soil organism interactions and activities, which are supported by the soil physicochemical properties. Risk assessment for this complex system requires understanding the relationships among its components, both in the presence and absence of stressors. To better understand the soil ecosystem and how exposure to potentially toxic elements impact ESs, we developed a quantitative technique, the adverse ecosystem service pathway (AESP) model. We sampled 47 soils across Canada and analyzed them for properties that included pH and cation exchange capacity. We spiked the soils with a metal mixture and measured 15 soil processes representing five ESs. Using a Pearson correlation, we confirmed that proxies of ESs are linked to soil properties. t test results showed that, apart from soil enzyme activities (p > 0.05), the processes underlying ES proxies are significantly reduced in metal-impacted soils. Using soil properties as predictors of ES proxies, we developed AESP models: one for spiked and another for control soils. These models showed adverse effects on ESs in spiked soils, depicted as changes in partial correlation coefficients. The AESP model, therefore, can be an important tool to understand complex ecosystems and improve risk assessment.

A survey of invasive plants on grassland soil microbial communities and ecosystem services

Invasive plants can cause changes in the structure and function of the ecosystem being invaded. Any changes in ecosystem diversity and community composition will likely alter ecosystem services provided by that ecosystem. However, how these ecosystem services may change is poorly understood. To elucidate how these ecosystem services will change with invasion, we sampled 561 plots undergoing invasion by smooth brome (Bromus inermis) and four other invasive species at a native Rough Fescue prairie located near Saskatoon, Saskatchewan, Canada. Soil and plant surveys were undertaken weekly for 26 weeks between May of 2014 and November of 2014, or the growing season. We measured a suite of ecosystem services, including greenhouse gasses, extracellular enzyme function, forage production, glyphosate degradation and decomposition. Furthermore, soil physical and chemical properties were measured, and soil bacterial and fungal communities were sequenced. This is a large and multifaceted dataset with complex temporal and spatial attributes which can be used to answer numerous questions regarding the functioning of prairie ecosystems and how invasive species will impact that functioning.

Measurement(s)	invasive species • native species • ecosystem decay • greenhouse gas • DNA
Technology Type(s)	Survey • monitoring device • DNA sequencing
Factor Type(s)	geographic location • sampling date
Sample Characteristic - Environment	prairie • soil
Sample Characteristic - Location	Saskatoon

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11898213

Functional and phylogenetic diversity determine woody productivity in a temperate forest

Understanding the relationships between biodiversity and ecosystem productivity has become a central issue in ecology and conservation biology studies, particularly when these relationships are connected with global climate change and species extinction. However, which facets of biodiversity (i.e. taxonomic, functional, and phylogenetic diversity) account most for variations in productivity are still not understood very well. This is especially true with regard to temperate forest ecosystems. In this study, we used a dataset from a stem-mapped permanent forest plot in northeastern China exploring the relationships between biodiversity and productivity at different spatial scales (20 × 20 m; 40 × 40 m; and 60 × 60 m). The influence of specific environmental conditions (topographic conditions) and stand maturity (expressed by initial stand volume and biomass) were taken into account using the multivariate approach known as structural equation models. The variable "Biodiversity" includes taxonomic (Shannon), functional (FDis), and phylogenetic diversity (PD). Biodiversity-productivity relationships varied with the spatial scales. At the scale of 20 × 20 m, PD and FDis significantly affected forest biomass productivity, while Shannon had only indirect effects. At the 40 × 40 m and 60 × 60 m scales, biodiversity and productivity were weakly correlated. The initial stand volume and biomass were the most important drivers of forest productivity. The local environmental conditions significantly influenced the stand volume, biomass, biodiversity, and productivity. The results highlight the scale dependency of the relationships between forest biodiversity and productivity. The positive role of biodiversity in facilitating forest productivity was confirmed at the smaller scales. Our findings emphasize the fundamental role of environmental conditions in determining forest ecosystem performances. The results of this study provide a better understanding of the underlying ecological processes that influence specific forest biodiversity and productivity relationships.

The contribution of socioeconomic factors to PM2.5 pollution in urban China

PM_2.5 pollution poses severe health risks to urban residents in low and middle-income countries. Existing studies have shown that the problem is affected by multiple socioeconomic factors. However, the relative contribution of these factors is not well understood, which sometimes leads to controversial controlling measures. In this study, we quantified the relative contribution of different socioeconomic factors, including the city size, industrial activities, and residents' activities, to PM_2.5 pollution in urban China between 2014 and 2015 by using structural equation model (SEM). Our results showed that industrial activities contributed more to PM_2.5 pollution than other factors. The city size and residents' activities also had significant impacts on PM_2.5 pollution. The combined influence of all socioeconomic factors could explain between 44% and 48% of variation in PM_2.5 pollution, which indicated the existence of influences from other factors such as weather conditions and outside sources of pollutants. Findings from our study can contribute to a more comprehensive understanding of the socioeconomic causes of PM_2.5 pollution.

Gauging policy-driven large-scale vegetation restoration programmes under a changing environment: Their effectiveness and socio-economic relationships

Large-scale ecological restoration has been widely accepted globally as an effective strategy for combating environmental crises and to facilitate sustainability. Assessing the effectiveness of ecological restoration is vital for researchers, practitioners, and policy-makers. However, few practical tools are available to perform such tasks, particularly for large-scale restoration programmes in complex socio-ecological systems. By taking a "before and after" design, this paper formulates a composite index (E_j) based on comparing the trends of vegetation cover and vegetation productivity to assess ecological restoration effectiveness. The index reveals the dynamic and spatially heterogenic process of vegetation restoration across different time periods, which can be informative for ecological restoration management at regional scales. Effectiveness together with its relationship to socio-economic factors is explored via structural equation modeling for three time periods. The results indicate that the temporal scale is a crucial factor in representing restoration effectiveness, and that the effects of socio-economic factors can also vary with time providing insight for improving restoration effectiveness. A dual-track strategy, which promotes the development of tertiary industry in absorbing the rural labor force together with improvements in agricultural practices, is proposed as a promising strategy for enhancing restoration effectiveness. In this process, timely and long-term ecological restoration monitoring is advocated, so that the success and sustainability of such programmes is ensured, together with more informative decision making where socio-ecological interactions at differing temporal scales are key concerns.

Soils and fire jointly determine vegetation structure in an African savanna

Savanna vegetation is variable, and predicting how water, nutrients, and chronic disturbances interact to determine vegetation structure in savannas represents a challenge. Here, we examined in situ interactions among rainfall, soils, grasses, fire, and elephants that determine tree layer responses to resource gradients in Kruger National Park in South Africa, using 363 long-term monitoring sites throughout the park. Grass biomass increased with rainfall and on nutrient-rich clay soils. Fire frequency, too, increased with rainfall. Conversely, tree density was greater on sandier soils, where water infiltrates more readily, and in areas where the maximum interval between fires was longer, irrespective of average fire frequency. Elephant density responded positively to tree density, but did not contribute significantly to decreasing tree density. Savanna vegetation structure was reasonably predictable, via a combination of rainfall (favoring grasses), soil (sandy soils favoring trees), and fire (limiting trees until a longer interval between fires allows them to establish). Explicit consideration of bottom-up and top-down interactions may thus contribute to a predictive understanding of savanna vegetation heterogeneity.

Macroecological scale effects of biodiversity on ecosystem functions under environmental change

Conserving different spatial and temporal dimensions of biological diversity is considered necessary for maintaining ecosystem functions under predicted global change scenarios. Recent work has shifted the focus from spatially local (α-diversity) to macroecological scales (β- and γ-diversity), emphasizing links between macroecological biodiversity and ecosystem functions (MB-EF relationships). However, before the outcomes of MB-EF analyses can be useful to real-world decisions, empirical modeling needs to be developed for natural ecosystems, incorporating a broader range of data inputs, environmental change scenarios, underlying mechanisms, and predictions. We outline the key conceptual and technical challenges currently faced in developing such models and in testing and calibrating the relationships assumed in these models using data from real ecosystems. These challenges are explored in relation to two potential MB-EF mechanisms: "macroecological complementarity" and "spatiotemporal compensation." Several regions have been sufficiently well studied over space and time to robustly test these mechanisms by combining cutting-edge spatiotemporal methods with remotely sensed data, including plant community data sets in Australia, Europe, and North America. Assessing empirical MB-EF relationships at broad spatiotemporal scales will be crucial in ensuring these macroecological processes can be adequately considered in the management of biodiversity and ecosystem functions under global change.

Ant predation on herbivores through a multitrophic lens: how effects of ants on plant herbivore defense and natural enemies vary along temperature gradients

Ants are keystone predators in terrestrial trophic cascades. Addressing ants' roles in multitrophic interactions across regional gradients is important for understanding mechanisms behind range limits of species. We present four hypotheses of trophic dynamics occurring when ants are rare: first, there is a shift in predator communities; second, plants decrease investments in ant attraction and increase production of secondary metabolites; third, lower herbivory at high elevations allows plants to tolerate herbivory; and fourth, distribution of ant-plants can be limited based on ant abundance. Conducting experiments on multitrophic effects of ants across elevational gradients, and incorporating these results to ecological niche modeling (ENM) will improve our knowledge of the impacts of global change on ants, trophic interactions, and biodiversity.

Direct and indirect causal effects of heterozygosity on fitness-related traits in Alpine ibex

Heterozygosity-fitness correlations (HFCs) are a useful tool to investigate the effects of inbreeding in wild populations, but are not informative in distinguishing between direct and indirect effects of heterozygosity on fitness-related traits. We tested HFCs in male Alpine ibex (Capra ibex) in a free-ranging population (which suffered a severe bottleneck at the end of the eighteenth century) and used confirmatory path analysis to disentangle the causal relationships between heterozygosity and fitness-related traits. We tested HFCs in 149 male individuals born between 1985 and 2009. We found that standardized multi-locus heterozygosity (MLH), calculated from 37 microsatellite loci, was related to body mass and horn growth, which are known to be important fitness-related traits, and to faecal egg counts (FECs) of nematode eggs, a proxy of parasite resistance. Then, using confirmatory path analysis, we were able to show that the effect of MLH on horn growth was not direct but mediated by body mass and FEC. HFCs do not necessarily imply direct genetic effects on fitness-related traits, which instead can be mediated by other traits in complex and unexpected ways.

Validating the scalability of soft X-ray spectromicroscopy for quantitative soil ecology and biogeochemistry research

Synchrotron-based soft-X-ray scanning transmission X-ray microscopy (STXM) has the potential to provide nanoscale resolution of the associations among biological and geological materials. However, standard methods for how samples should be prepared, measured, and analyzed to allow the results from these nanoscale imaging and spectroscopic tools to be scaled to field scale biogeochemical results are not well established. We utilized a simple sample preparation technique that allows one to assess detailed mineral, metal, and microbe spectroscopic information at the nano- and microscale in soil colloids. We then evaluated three common approaches to collect and process nano- and micronscale information by STXM and the correspondence of these approaches to millimeter scale soil measurements. Finally, we assessed the reproducibility and spatial autocorrelation of nano- and micronscale protein, Fe(II) and Fe(III) densities in a soil sample. We demonstrate that linear combination fitting of entire spectra provides slightly different Fe(II) mineral densities compared to image resonance difference mapping but that difference mapping results are highly reproducible between among sample replicates. Further, STXM results scale to the mm scale in complex systems with an approximate geospatial range of 3 μm in these samples.