Roy Chapman Andrews

Abstract Trichomes are diverse and functionally important plant structures that vary in response to selection pressures across ecological gradients and evolutionary timescales. Classic hypotheses predict higher investment in trichomes in arid environments, at lower latitudes, and in long-lived species, as well as shifts in trichome production to reduce conflict between defense traits and mutualisms. However, tests of these hypotheses often rely on aggregate trichome metrics and neglect the rich diversity of trichome phenotypes. Here, we collected data on fine-scale patterns of trichome length, density, and type in 52 species of blazingstars (Mentzelia: Loasaceae) and tested whether individual trichome traits were consistent with existing adaptive hypotheses. Contrary to longstanding hypotheses, we found that Mentzelia species tend to display greater trichome investment in less arid environments and at higher latitudes. Barbed trichomes are significantly less common on the upper surface of the leaf, possibly reducing defense-pollination conflict. Species with larger petals (a proxy for reliance on insect pollinators) also shift investment away from insect-trapping hairs on the underside of the leaf. Examining trichome types separately revealed that different morphologies show distinct responses to abiotic and biotic factors, demonstrating the need to consider multiple axes of diversity when testing adaptive hypotheses for complex traits.

AbstractPremiseBiotic disjunctions have attracted scientific attention for the past 200 years. Despite being represented in many familiar plants (such as bald cypress, flowering dogwood, sweetgum, partridgeberry, etc.), the eastern North American (ENA)–Mexican (M) disjunction remains poorly understood. Major outstanding questions include the divergence times of taxa exhibiting the disjunction and environmental/geological processes that may underlie the disjunction. Symphyotrichum Nees (Asteraceae), one of the most diverse genera in the eastern USA, displays several examples of disjunct ENA–M taxa.MethodsWe generated target capture data using the Angiosperms353 baitset and generated the first well‐sampled phylogenomic hypothesis for Symphyotrichum and its close relatives. Focusing on S. subgenus Virgulus, we used MCMCTREE to perform divergence time estimation and the R package BioGeoBEARS to infer ancestral regions and biogeographic transitions between North America and Mexico. Finally, we used the ancestral niche reconstruction method Utremi to test for a role of historical aridification in generating the disjunction.ResultsOur molecular data suggest a recent radiation of Symphyotrichum at the Plio‐Pleistocene boundary (~2.5 mya), with early connections to Mexico in ancestral lineages that closed off shortly after and were followed by vicariance across this region. Except for some present‐day broadly distributed species, there is a complete lack of movement between ENA and M after ~0.5 mya.ConclusionsA reconstructed disjunct distribution of suitable habitat in Pleistocene climatic models corroborates results from biogeographic modeling and confirms glacial cycles are more likely to be associated with the breakup of ENA–M biogeographic connections.

Past climate change is one of the important factors influencing primate speciation. Populations of various species could have risen or declined in response to these climatic fluctuations. Northeast India harbors a rich diversity of primates, where such fluctuations can be implicated. Recent advances in climate modeling as well as genomic data analysis has paved the way for understanding how species accumulate at a particular geographic region. We utilized these methods to explore the primate diversity in this unique region in relation to past climate change. To ascertain the population level changes, we inferred the demographic history of nine species of primates found in Northeast India and compared it with species distribution models of Pliocene and Pleistocene period. Through this study, we are able to provide a detailed picture of how past climatic changes have resulted in the present species diversity and this mixture of species have either originated in the region or have dispersed from mainland Southeast Asia. We observe that effective population size has decreased for all the species, but distributions are different for all the four genera: Macaca, Trachypithecus, Hoolock and Nycticebus. It also gives an idea about how each species is affected differently by climate change, and why it should be given emphasis in framing species‐wise conservation models for future climate change.

Without appropriate and ongoing management interventions, weeds will continue to economically and environmentally disadvantage agricultural and natural ecosystems. For these management strategies to have long‐term sustained success, they need to carefully consider the biological aspects of the targeted weed. These strategies will also need to consider potential adaptations evolved by the targeted weed in response to a range of selection pressures imposed by anthropogenetic factors, climate change, changing environmental conditions, and inappropriate or unsuccessful management regimes. One group of weeds that has been observed to readily adapt to a wide range of conditions and has shown considerable challenges in their management is invasive grasses. Adding to these challenges is that several invasive grasses have also developed resistance to a range of herbicide modes of action, which, to date, has been one of the most commonly used methods of control. To address these challenges, this review explores the biology and ecology of the globally invasive annuals Echinochloa crus‐galli (Barnyard grass) and Panicum capillare (Witchgrass), and the perennial Sorghum halepense (Johnson grass) to identify (i) the most suitable management options for their control and (ii) potential research gaps that may assist in the future management direction of these species. Based on the findings of this review, it is clear that an integrated management approach that targets different aspects of the plant's biology, in combination with early detection and treatment and ongoing surveillance, is necessary for the long‐term control of these species. Although a combination of methods appears promising, further investigation still is required to evaluate their efficiency and long‐term success in a changing environment, all of which are further discussed within this review.

Understanding the drivers of species richness patterns is a major goal of ecology and evolutionary biology, and the drivers vary across regions and taxa. Here, we assessed the influence of environmental factors and evolutionary history on the pattern of species richness in the genus Sorbus (110 species). We mapped the global species richness pattern of Sorbus at a spatial resolution of 200 × 200 km, using 10,652 specimen records. We used stepwise regression to assess the relationship between 23 environmental predictors and species richness and estimated the diversification rate of Sorbus based on chloroplast genome data. The effects of environmental factors were explained by adjusted R2, and evolutionary factors were inferred based on differences in diversification rates. We found that the species richness of Sorbus was highest in the Hengduan Mountains (HDM), which is probably the center of diversity. Among the selected environmental predictors, the integrated model including all environmental predictors had the largest explanatory power for species richness. The determinants of species richness show regional differences. On the global and continental scale, energy and water availability become the main driving factors. In contrast, climate seasonality is the primary factor in the HDM. The diversification rate results showed no significant differences between HDM and non-HDM, suggesting that evolutionary history may have limited impact on the pattern of Sorbus species richness. We conclude that environmental factors play an important role in shaping the global pattern of Sorbus species richness, while diversification rates have a lesser impact.

Distributions of plants are expected to change in response to climate change, but the relative probability of that change is often unknown. Curl-leaf mountain mahogany (Cercocarpus ledifolius), an important browse species used by ungulates as forage and cover across the western US, is thought to be moderately to highly vulnerable to climate change this century, and a reduction in curl-leaf mountain mahogany occurrence may negatively impact ungulates reliant upon it. A combination of probability density estimation and vector analysis was used to predict curl-leaf mountain mahogany distribution across the species range relative to climate space and how that relationship would affect curl-leaf mountain mahogany at a local scale. Locally, we used the curl-leaf mountain mahogany population at the Bighorn Canyon National Recreation Area (BICA) in Montana and Wyoming for comparison. We modeled the probability of curl-leaf mountain mahogany occurrence across its distribution using water balance data to spatially and temporally assess the vulnerability of a population at a local scale. Modeled probabilities of occurrence and vector analysis indicated the species to remain in some areas within BICA but will be vulnerable in others given the predicted changes in temperature and precipitation in BICA if historical trajectories continue. This information allows managers to direct limited resources to other management actions by using the best available science to inform decisions. Other curl-leaf mountain mahogany populations currently inhabiting wetter, drier sites may follow a similar trajectory as the effects of climate change manifest. The approach used serves as a model to assess the predicted trend for species-specific plant communities of concern that may be adversely affected by climate change.

Island ecosystems have significant conservation value owing to their higher endemic biotas. Moreover, studies of regional communities that compare differences in species composition (species dissimilarity) among islands and the mainland suggest that community assembly on islands is different from that on the mainland. However, the uniqueness of island biotic assembly has been little studied at the global scale, nor have phylogenetic information or alien species been considered in these patterns. We evaluate taxonomic and phylogenetic change from one community to the next, focusing on differences in species composition between mainland-mainland (M-M) pairs compared to differences between mainland-island pairs (M-I) and between island-island pairs (I-I), using herpetofauna on islands and adjacent mainland areas worldwide. Our analyses detect greater taxonomic and phylogenetic dissimilarity for M-I and I-I comparisons than predicted by M-M model, indicating different island herpetofauna assembly patterns compared with mainland counterparts across the world. However, this higher M-I dissimilarity has been significantly decreased after considering alien species. Our results provide global evidence on the importance of island biodiversity conservation from the aspect of both the taxonomic and phylogenetic uniqueness of island biotic assembly.

Nonnative invasive plants (weeds) negatively impact native ecosystems, and their effects are likely to increase with continuing global trade. Biological weed control has been employed as a cost-effective and sustainable management option for weeds in the USA since 1902. Biological control programs require careful prioritization of target weeds to ensure the most appropriate targets are selected to obtain the greatest beneficial outcomes with available resources. The Biological Control Target Selection (BCTS) system was developed by researchers in South Africa as an objective, transparent approach to prioritizing new weed biological control targets. The BCTS system was recently modified and applied to 295 state-regulated weeds in the western USA for which no biological control agents have yet been released. This paper presents the results of that application, identifying the most suitable candidates for new biological control programs as well as problematic weeds for which the likelihood of successful biological control is low.Top-ranked species in the western USA are biennial or perennial weeds that occur in stable habitats, are established in more than one state, have traits deemed difficult to control with conventional methods, have large negative impacts and no conflicts of interest outside of the horticultural industry, and have substantial information available on potential biocontrol agents. Fifteen of the 20 top-ranked species are already targets of ongoing biological control programs in the USA. When species with current programs are excluded from the analysis, the next 20 top-ranked species largely differ by having less information available on potential biological control agents and having native or economically important congeners in the USA. Results from this framework provide valuable insights to the prioritization of current and future biocontrol research programs in the western USA.

Saussurea is one of the largest and most rapidly evolving genera within the Asteraceae, comprising approximately 520 species from the Northern Hemisphere. A comprehensive infrageneric classification, supported by robust phylogenetic trees and corroborated by morphological and other data, has not yet been published. For the first time, we recovered a well-resolved nuclear phylogeny of Saussurea consisting of four main clades, which was also supported by morphological data. Our analyses show that ancient hybridization is the most likely source of deep cytoplasmic-nuclear conflict in Saussurea, and a phylogeny based on nuclear data is more suitable than one based on chloroplast data for exploring the infrageneric classification of Saussurea. Based on the nuclear phylogeny obtained and morphological characters, we proposed a revised infrageneric taxonomy of Saussurea, which includes four subgenera and 13 sections. Specifically, 1) S. sect. Cincta, S. sect. Gymnocline, S. sect. Lagurostemon, and S. sect. Strictae were moved from S. subg. Saussurea to S. subg. Amphilaena, 2) S. sect. Pseudoeriocoryne was moved from S. subg. Eriocoryne to S. subg. Amphilaena, and 3) S. sect. Laguranthera was moved from S. subg. Saussurea to S. subg. Theodorea.

Non‐native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well‐timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range‐wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat‐insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within‐season or within‐year decision support.