Ecology and Evolution

Plant‐soil feedbacks (PSFs) have been shown to strongly affect plant performance under controlled conditions, and PSFs are thought to have far reaching consequences for plant population dynamics and the structuring of plant communities. However, thus far the relationship between PSF and plant species abundance in the field is not consistent. Here, we synthesize PSF experiments from tropical forests to semiarid grasslands, and test for a positive relationship between plant abundance in the field and PSFs estimated from controlled bioassays. We meta‐analyzed results from 22 PSF experiments and found an overall positive correlation (0.12 ≤  ≤ 0.32) between plant abundance in the field and PSFs across plant functional types (herbaceous and woody plants) but also variation by plant functional type. Thus, our analysis provides quantitative support that plant abundance has a general albeit weak positive relationship with PSFs across ecosystems. Overall, our results suggest that harmful soil biota tend to accumulate around and disproportionately impact species that are rare. However, data for the herbaceous species, which are most common in the literature, had no significant abundance‐PSFs relationship. Therefore, we conclude that further work is needed within and across biomes, succession stages and plant types, both under controlled and field conditions, while separating PSF effects from other drivers (e.g., herbivory, competition, disturbance) of plant abundance to tease apart the role of soil biota in causing patterns of plant rarity versus commonness.

Root traits vary enormously among plant species but we have little understanding of how this variation affects their functioning. Of central interest is how root traits are related to plant resource acquisition strategies from soil. We examined root traits of 33 woody species from northeastern US forests that form two of the most common types of mutualisms with fungi, arbuscular mycorrhizas (AM) and ectomycorrhizas (EM). We examined root trait distribution with respect to plant phylogeny, quantifying the phylogenetic signal (K statistic) in fine root morphology and architecture, and used phylogenetically independent contrasts (PICs) to test whether taxa forming different mycorrhizal associations had different root traits. We found a pattern of species forming roots with thinner diameters as species diversified across time. Given moderate phylogenetic signals (K = 0.44–0.68), we used PICs to examine traits variation among taxa forming AM or EM, revealing that hosts of AM were associated with lower branching intensity (r_PIC = −0.77) and thicker root diameter (r_PIC = −0.41). Because EM evolved relatively more recently and intermittently across plant phylogenies, significant differences in root traits and colonization between plants forming AM and EM imply linkages between the evolution of these biotic interactions and root traits and suggest a history of selection pressures, with trade‐offs for supporting different types of associations. Finally, across plant hosts of both EM and AM, species with thinner root diameters and longer specific root length (SRL) had less colonization (r_PIC = 0.85, −0.87), suggesting constraints on colonization linked to the evolution of root morphology.

Presence‐only data present challenges for selecting thresholds to transform species distribution modeling results into binary outputs. In this article, we compare two recently published threshold selection methods (maxSSS and maxF_pb) and examine the effectiveness of the threshold‐based prevalence estimation approach. Six virtual species with varying prevalence were simulated within a real landscape in southeastern Australia. Presence‐only models were built with DOMAIN, generalized linear model, Maxent, and Random Forest. Thresholds were selected with two methods maxSSS and maxF_pb with four presence‐only datasets with different ratios of the number of known presences to the number of random points (KP–RP_ratio). Sensitivity, specificity, true skill statistic, and F measure were used to evaluate the performance of the results. Species prevalence was estimated as the ratio of the number of predicted presences to the total number of points in the evaluation dataset. Thresholds selected with maxF_pb varied as the KP–RP_ratio of the threshold selection datasets changed. Datasets with the KP–RP_ratio around 1 generally produced better results than scores distant from 1. Results produced by We conclude that maxF_pb had specificity too low for very common species using Random Forest and Maxent models. In contrast, maxSSS produced consistent results whichever dataset was used. The estimation of prevalence was almost always biased, and the bias was very large for DOMAIN and Random Forest predictions. We conclude that maxF_pb is affected by the KP–RP_ratio of the threshold selection datasets, but maxSSS is almost unaffected by this ratio. Unbiased estimations of prevalence are difficult to be determined using the threshold‐based approach.

Bamboo, a member of subfamily Bambusoideae in the grass family (Poaceae), is one of the most important nontimber forest resources and a potential alternative to wood and wood products. Ethiopian lowland bamboo (Oxytenanthera abyssinica) is an economically and ecologically important species which accounts about 85% of total bamboo coverage in the country. This species is experiencing population decline due to a number of anthropogenic factors. As a foundation step, genetic diversity, population structure, and gene flow analysis of various O. abyssinica populations found in Ethiopia are studied using inter‐simple sequence repeat markers. One hundred and thirty isolates of bamboo belonging to 13 geographically diverse populations were collected for DNA extraction and analysis. Heterozygosity, level of polymorphism, marker efficiency, Nei's gene diversity (H), and Shannon's information index (I) analysis, analysis of molecular variance (AMOVA), analysis for cluster, principal coordinates (PCoA), and admixture analyses were performed based on the markers banding pattern. The results indicated high genetic variation (84.48%) at species level. The H, I, observed and effective number of alleles at the species level were 0.2702, 0.4061, 1.8448, and 1.4744, respectively, suggesting a relatively high level of genetic diversity. However, genetic differentiation at the population level was relatively low. Using grouped populations, AMOVA revealed that most (61.05%) of the diversity was distributed within the populations with F_ST = 0.38949, F_SC = 0.10486, and F_CT = 0.31797. Cluster analysis grouped the populations into markedly distinct clusters, suggesting confined propagation in distinct geographic regions. STRUCTURE analyses showed K = 2 for all populations and K = 11 excluding Gambella population. Using these markers, we found strong evidence that the genetic diversity of the lowland bamboo is associated with distinct geographic regions and that isolates of Gambella Region, with their unique genetic origin, are quite different from other bamboos found in the country.

Rising temperatures are predicted to melt all perennial ice cover in the Arctic by the end of this century, thus opening up suitable habitat for temperate and subarctic species. Canopy‐forming seaweeds provide an ideal system to predict the potential impact of climate‐change on rocky‐shore ecosystems, given their direct dependence on temperature and their key role in the ecological system. Our primary objective was to predict the climate‐change induced range‐shift of Fucus distichus, the dominant canopy‐forming macroalga in the Arctic and subarctic rocky intertidal. More specifically, we asked: which Arctic/subarctic and cold‐temperate shores of the northern hemisphere will display the greatest distributional change of F. distichus and how will this affect niche overlap with seaweeds from temperate regions? We used the program MAXENT to develop correlative ecological niche models with dominant range‐limiting factors and 169 occurrence records. Using three climate‐change scenarios, we projected habitat suitability of F. distichus – and its niche overlap with three dominant temperate macroalgae – until year 2200. Maximum sea surface temperature was identified as the most important factor in limiting the fundamental niche of F. distichus. Rising temperatures were predicted to have low impact on the species' southern distribution limits, but to shift its northern distribution limits poleward into the high Arctic. In cold‐temperate to subarctic regions, new areas of niche overlap were predicted between F. distichus and intertidal macroalgae immigrating from the south. While climate‐change threatens intertidal seaweeds in warm‐temperate regions, seaweed meadows will likely flourish in the Arctic intertidal. Although this enriches biodiversity and opens up new seaweed‐harvesting grounds, it will also trigger unpredictable changes in the structure and functioning of the Arctic intertidal ecosystem.

In mosaic marine habitats, such as intertidal zones, ocean acidification (OA) is exacerbated by high variability of pH, temperature, and biological CO₂ production. The nonlinear interactions among these drivers can be context‐specific and their effect on organisms in these habitats remains largely unknown, warranting further investigation.

Probability of detection and accuracy of distance estimates in aural avian surveys may be affected by the presence of anthropogenic noise, and this may lead to inaccurate evaluations of the effects of noisy infrastructure on wildlife. We used arrays of speakers broadcasting recordings of grassland bird songs and pure tones to assess the probability of detection, and localization accuracy, by observers at sites with and without noisy oil and gas infrastructure in south‐central Alberta from 2012 to 2014. Probability of detection varied with species and with speaker distance from transect line, but there were few effects of noisy infrastructure. Accuracy of distance estimates for songs and tones decreased as distance to observer increased, and distance estimation error was higher for tones at sites with infrastructure noise. Our results suggest that quiet to moderately loud anthropogenic noise may not mask detection of bird songs; however, errors in distance estimates during aural surveys may lead to inaccurate estimates of avian densities calculated using distance sampling. We recommend caution when applying distance sampling if most birds are unseen, and where ambient noise varies among treatments.

Edges are ecologically important environmental features and have been well researched in agricultural and urban landscapes. However, little work has been conducted in flammable ecosystems where spatially and temporally dynamic fire edges are expected to influence important processes such as recolonization of burnt areas and landscape connectivity. We review the literature on fire, fauna, and edge effects to summarize current knowledge of faunal responses to fire edges and identify knowledge gaps. We then develop a conceptual model to predict faunal responses to fire edges and present an agenda for future research. Faunal abundance at fire edges changes over time, but patterns depend on species traits and resource availability. Responses are also influenced by edge architecture (e.g., size and shape), site and landscape context, and spatial scale. However, data are limited and the influence of fire edges on both local abundance and regional distributions of fauna is largely unknown. In our conceptual model, biophysical properties interact with the fire regime (e.g., patchiness, frequency) to influence edge architecture. Edge architecture and species traits influence edge permeability, which is linked to important processes such as movement, resource selection, and species interactions. Predicting the effect of fire edges on fauna is challenging, but important for biodiversity conservation in flammable landscapes. Our conceptual model combines several drivers of faunal fire responses (biophysical properties, regime attributes, species traits) and will therefore lead to improved predictions. Future research is needed to understand fire as an agent of edge creation; the spatio‐temporal flux of fire edges across landscapes; and the effect of fire edges on faunal movement, resource selection, and biotic interactions. To aid the incorporation of new data into our predictive framework, our model has been designed as a Bayesian Network, a statistical tool capable of analyzing complex environmental relationships, dealing with data gaps, and generating testable hypotheses.

Invasive animals can facilitate the success of invasive plant populations through disturbance. We examined the relationship between the repeated foraging disturbance of an invasive animal and the population maintenance of an invasive plant in a coastal dune ecosystem. We hypothesized that feral wild hog (Sus scrofa) populations repeatedly utilized tubers of the clonal perennial, yellow nutsedge (Cyperus esculentus) as a food source and evaluated whether hog activity promoted the long‐term maintenance of yellow nutsedge populations on St. Catherine's Island, Georgia, United States. Using generalized linear mixed models, we tested the effect of wild hog disturbance on permanent sites for yellow nutsedge culm density, tuber density, and percent cover of native plant species over a 12‐year period. We found that disturbance plots had a higher number of culms and tubers and a lower percentage of native live plant cover than undisturbed control plots. Wild hogs redisturbed the disturbed plots approximately every 5 years. Our research provides demographic evidence that repeated foraging disturbances by an invasive animal promote the long‐term population maintenance of an invasive clonal plant. Opportunistic facultative interactions such as we demonstrate in this study are likely to become more commonplace as greater numbers of introduced species are integrated into ecological communities around the world.

Point data obtained from real‐time location systems (RTLSs) can be processed into animal contact networks, describing instances of interaction between tracked individuals. Proximity‐based definitions of interanimal “contact,” however, may be inadequate for describing epidemiologically and sociologically relevant interactions involving body parts or other physical spaces relatively far from tracking devices. This weakness can be overcome by using polygons, rather than points, to represent tracked individuals and defining “contact” as polygon intersections.