Summary1. Shifts in the spatial and temporal patterns of flowering could affect the resources available to pollinators, and such shifts might become more common as climate change progresses. 2. As mid-summer temperatures have warmed, we found that a montane meadow ecosystem in the southern Rocky Mountains of the United States exhibits a trend toward a bimodal distribution of flower abundance, characterized by a mid-season reduction in total flower number, instead of a broad, unimodal flowering peak lasting most of the summer season. 3. We examined the shapes of community-level flowering curves in this system and found that the typical unimodal peak results from a pattern of complementary peaks in flowering among three distinct meadow types (dry, mesic and wet) within the larger ecosystem. However, high mid-summer temperatures were associated with divergent shifts in the flowering curves of these individual meadow types. Specifically, warmer summers appeared to cause increasing bimodality in mesic habitats, and a longer interval between early and late flowering peaks in wet and dry habitats. 4. Together, these habitat-specific shifts produced a longer mid-season valley in floral abundance across the larger ecosystem in warmer years. Because of these warming-induced changes in flowering patterns, and the significant increase in summer temperatures in our study area, there has been a trend toward non-normality of flowering curves over the period . This trend reflects increasing bimodality in total community-wide flowering. 5. The resulting longer periods of low flowering abundance in the middle of the summer season could negatively affect pollinators that are active throughout the season, and shifts in flowering peaks within habitats might create mismatches between floral resources and demand by pollinators with limited foraging ranges. 6. Synthesis. Early-season climate conditions are getting warmer and drier in the high altitudes of the southern Rocky Mountains. We present evidence that this climate change is disrupting flowering phenology within and among different moisture habitats in a sub-alpine meadow ecosystem, causing a mid-season decline in floral resources that might negatively affect mutualists, especially pollinators. Our findings suggest that climate change can have complex effects on phenology at small spatial scales, depending on patch-level habitat differences.

Bovid astragali are one of the most commonly preserved bones in the fossil record. Accordingly, astragali are an important target for studies seeking to predict the habitat preferences of fossil bovids based on bony anatomy. However, previous work has not tested functional hypotheses linking astragalar morphology with habitat while controlling for body size and phylogenetic signal. This article presents a functional framework relating the morphology of the bovid astragalus to habitat-specific locomotor ecology and tests four hypotheses emanating from this framework. Highly cursorial bovids living in structurally open habitats are hypothesized to differ from their less cursorial closed-habitat dwelling relatives in having (1) relatively short astragali to maintain rotational speed throughout the camming motion of the rotating astragalus, (2) a greater range of angular excursion at the hock, (3) relatively larger joint surface areas, and (4) a more pronounced "spline-and-groove" morphology promoting lateral joint stability. A diverse sample of 181 astragali from 50 extant species was scanned using a Next Engine laser scanner. Species were assigned to one of four habitat categories based on the published ecological literature. A series of 11 linear measurements and three joint surface areas were measured on each astragalus. A geometric mean body size proxy was used to size-correct the measurement data. Phylogenetic generalized least squares (PGLS) was used to test for differences between habitat categories while controlling for body size differences and phylogenetic signal. Statistically significant PGLS results support Hypotheses 1 and 2 (which are not mutually exclusive) as well as Hypothesis 3. No support was found for Hypothesis 4. These findings confirm that the morphology of the bovid astragalus is related to habitat-specific locomotor ecology, and that this relationship is statistically significant after controlling for body size and phylogeny. Thus, this study validates the use of this bone as an ecomorphological indicator.

A longstanding challenge is to understand how ribosomes parse mRNA open reading frames (ORFs). Significantly, GCN codons are over-represented in the initial codons of ORFs of prokaryote and eukaryote mRNAs. We describe a ribosome rRNA-protein surface that interacts with an mRNA GCN codon when next in line for the ribosome A-site. The interaction surface is comprised of the edges of two stacked rRNA bases: the Watson–Crick edge of 16S/18S rRNA C1054 and the adjacent Hoogsteen edge of A1196 (Escherichia coli 16S rRNA numbering). Also part of the interaction surface, the planar guanidinium group of a conserved Arginine (R146 of yeast ribosomal protein Rps3) is stacked adjacent to A1196. On its other side, the interaction surface is anchored to the ribosome A-site through base stacking of C1054 with the wobble anticodon base of the A-site tRNA. Using molecular dynamics simulations of a 495-residue subsystem of translocating ribosomes, we observed base pairing of C1054 to nucleotide G at position 1 of the next-in-line codon, consistent with previous cryo-EM observations, and hydrogen bonding of A1196 and R146 to C at position 2. Hydrogen bonding to both of these codon positions is significantly weakened when C at position 2 is changed to G, A or U. These sequence-sensitive mRNA-ribosome interactions at the C1054-A1196-R146 (CAR) surface potentially contribute to the GCN-mediated regulation of protein translation.

Large mammals are at high risk of extinction globally. To understand the consequences of their demise for community assembly, we tracked community structure through the end-Pleistocene megafaunal extinction in North America. We decomposed the effects of biotic and abiotic factors by analyzing co-occurrence within the mutual ranges of species pairs. Although shifting climate drove an increase in niche overlap, co-occurrence decreased, signaling shifts in biotic interactions. Furthermore, the effect of abiotic factors on co-occurrence remained constant over time while the effect of biotic factors decreased. Biotic factors apparently played a key role in continental-scale community assembly before the extinctions. Specifically, large mammals likely promoted co-occurrence in the Pleistocene, and their loss contributed to the modern assembly pattern in which co-occurrence frequently falls below random expectations.

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Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales. Biotic Interactions in the Fossil RecordBiotic interactions occur when organisms living in the same community directly or indirectly influence one another. Biotic interactions can occur within or among species, be positive or negative, and cover a wide range of interactions including predation, commensalism, mutualism, resource competition, and parasitism [1]. Biotic interactions play an important role in structuring modern communities (e.g., [2]). Understanding their importance in the past therefore has the potential to shed light on their role in shaping ancient and recent diversity patterns. Historically, however, the study of biotic interactions in the fossil record has largely focused on direct physical evidence of interactions such as bore holes in shells, plant damage by insects, patterns of bryozoan encrustation, rare occurrences of gut contents, and carnivore damage on bones (e.g., [3,4]). Analysis of unusually well-preserved fossil assemblages allows reconstruction of trophic relationships among diverse organisms (e.g., [5]) and earlier work documented long-term trends in ecospace (see Glossary) occupation [6]. However, temporally continuous evidence for biotic interactions (traditionally thought to structure biodiversity on only very limited spatiotemporal scales [7]) with appropriate temporal resolution (i.e., high-resolution stratigraphic sequences) is only rarely preserved. Consequently, paleontologists have focused primarily on the more accessible long-term trends in climate as important regulators of biodiversity and the differential success of species (e.g., [8]); only short-term ecological phenomena or long-term patterns that cannot be explained by climate have typically been attributed to the outcome of biotic interactions (e.g., [9], but see [6]). However, as the only source of sufficiently long-term data, and in light of several recent methodological advances, the fossil record is now uniquely positioned to answer many of the questions at the core of the evolutionary and ecological sciences. Herein, we address important recent advances in understanding the role of biotic interactions in shaping macroevolutionary and macroecological phenomena in the fossil record (Figure 1) and highlight areas o...

In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, <5.6% of DFAs and <8.26% of PGLS analyses were significant. When characters contained phylogenetic signal and actual habitats were used, 33.27 to 45.07% of DFAs and <13.09% of PGLS analyses were significant. False Discovery Rate (FDR) corrections for multiple PGLS analyses reduced the rate of significance to <4.64%. In all cases using actual habitats and characters with phylogenetic signal, correct classification rates of DFAs exceeded random chance. In simulations involving phylogenetic signal in both predictor variables and predicted categories, PGLS with FDR was rarely significant, while DFA often was. In short, DFA offered no indication that differences between categories might be explained by phylogenetic signal, while PGLS did. As such, PGLS provides a valuable tool for testing the functional hypotheses at the heart of ecomorphology.