Sara Plummer Lemmon

Fir forests (Abies, Pinaceae) are dominant in temperate regions of North America; however, they have experienced high degradation rates that can threaten their long-term continuity. This study aimed to identify the priority areas for the conservation of the genus Abies in North America. First, we modeled the species distribution of the 17 native species through ecological niche modeling, considering 21 environmental variables. Then, we defined the priority areas through multi-criteria analysis, considering the species richness, geographic rareness, irreplaceability, habitat degradation, and risk extinction. We also built six scenarios, giving more priority to each criterion. Finally, we identified the proportion of the extent of the priority areas covered by protected areas. Elevation, precipitation seasonality, and winter precipitation influenced the distribution of most of the Abies species. When considering equal weights to each criterion, the priority areas summed up 6% of the total extent covered by the Abies species in North America. Most priority areas were located on the West Coast of the United States, the Eastern Sierra Madre, Southern Sierra Madre, Sierras of Chiapas and Central America, and the Trans-Mexican Volcanic Belt ecoregions. In these ecoregions, the Abies species are restricted to small areas facing high degradation levels. Only 16% of the area covered by the Abies species in North America is protected, mainly under restrictive schemes such as National Parks and Wilderness Areas. The priority areas identified could be the basis for establishing or enlarging protected areas. The preservation of the genus Abies could also maintain other ecological features and processes such as biodiversity, forest resources, and environmental services.

Rubus (Rosaceae), one of the most complicated angiosperm genera, contains about 863 species, and is notorious for its taxonomic difficulty. The most recent (1910–1914) global taxonomic treatment of the genus was conducted by Focke, who defined 12 subgenera. Phylogenetic results over the past 25 years suggest that Focke's subdivisions of Rubus are not monophyletic, and large‐scale taxonomic revisions are necessary. Our objective was to provide a comprehensive phylogenetic analysis of the genus based on an integrative evidence approach. Morphological characters, obtained from our own investigation of living plants and examination of herbarium specimens are combined with chloroplast genomic data. Our dataset comprised 196 accessions representing 145 Rubus species (including cultivars and hybrids) and all of Focke's subgenera, including 60 endemic Chinese species. Maximum likelihood analyses inferred phylogenetic relationships. Our analyses concur with previous molecular studies, but with modifications. Our data strongly support the reclassification of several subgenera within Rubus. Our molecular analyses agree with others that only R. subg. Anoplobatus forms a monophyletic group. Other subgenera are para‐ or polyphyletic. We suggest a revised subgeneric framework to accommodate monophyletic groups. Character evolution is reconstructed, and diagnostic morphological characters for different clades are identified and discussed. Based on morphological and molecular evidence, we propose a new classification system with 10 subgenera: R. subg. Anoplobatus, R. subg. Batothamnus, R. subg. Chamaerubus, R. subg. Cylactis, R. subg. Dalibarda, R. subg. Idaeobatus, R. subg. Lineati, R. subg. Malachobatus, R. subg. Melanobatus, and R. subg. Rubus. The revised infrageneric nomenclature inferred from our analyses is provided along with synonymy and type citations. Our new taxonomic backbone is the first systematic and complete global revision of Rubus since Focke's treatment. It offers new insights into deep phylogenetic relationships of Rubus and has important theoretical and practical significance for the development and utilization of these important agronomic crops.

Species climate niche models (CNMs) have been widely used for assessing climate change impact, developing conservation strategies and guiding assisted migration for adaptation to future climates. However, the CNMs built based on species occurrence data only reflect the species’ realized niche, which can overestimate the potential loss of suitable habitat of existing forests and underestimate the potential of assisted migration to mitigate climate change. In this study, we explored building a fundamental climate niche model using widely available species occurrence data with two important forest tree species, lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.), which were introduced to many countries worldwide. We first compared and optimized three individual modeling techniques and their ensemble by adjusting the ratio of presence to absence (p/a) observations using an innovative approach to predict the realized climate niche of the two species. We then extended the realized climate niches to their fundamental niches by determining a new cut-off threshold based on species occurrence data beyond the native distributions. We found that the ensemble model comprising Random Forest and Maxent had the best performance and identified a common cut-off threshold of 0.3 for predicting the fundamental climate niches of the two species, which is likely applicable to other species. We then predicted the fundamental climate niches of the two species under current and future climate conditions. Our study demonstrated a novel approach for predicting species’ fundamental climate niche with high accuracy using only species occurrence data, including both presence and absence data points. It provided a new tool for assessing climate change impact on the future loss of existing forests and implementing assisted migration for better adapting to future climates.

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

The genus Viola (Violaceae) is among the 40–50 largest genera among angiosperms, yet its taxonomy has not been revised for nearly a century. In the most recent revision, by Wilhelm Becker in 1925, the then-known 400 species were distributed among 14 sections and numerous unranked groups. Here, we provide an updated, comprehensive classification of the genus, based on data from phylogeny, morphology, chromosome counts, and ploidy, and based on modern principles of monophyly. The revision is presented as an annotated global checklist of accepted species of Viola, an updated multigene phylogenetic network and an ITS phylogeny with denser taxon sampling, a brief summary of the taxonomic changes from Becker’s classification and their justification, a morphological binary key to the accepted subgenera, sections and subsections, and an account of each infrageneric subdivision with justifications for delimitation and rank including a description, a list of apomorphies, molecular phylogenies where possible or relevant, a distribution map, and a list of included species. We distribute the 664 species accepted by us into 2 subgenera, 31 sections, and 20 subsections. We erect one new subgenus of Viola (subg. Neoandinium, a replacement name for the illegitimate subg. Andinium), six new sections (sect. Abyssinium, sect. Himalayum, sect. Melvio, sect. Nematocaulon, sect. Spathulidium, sect. Xanthidium), and seven new subsections (subsect. Australasiaticae, subsect. Bulbosae, subsect. Clausenianae, subsect. Cleistogamae, subsect. Dispares, subsect. Formosanae, subsect. Pseudorupestres). Evolution within the genus is discussed in light of biogeography, the fossil record, morphology, and particular traits. Viola is among very few temperate and widespread genera that originated in South America. The biggest identified knowledge gaps for Viola concern the South American taxa, for which basic knowledge from phylogeny, chromosome counts, and fossil data is virtually absent. Viola has also never been subject to comprehensive anatomical study. Studies into seed anatomy and morphology are required to understand the fossil record of the genus.

We analyzed the geographical distribution of Habromys species based on distributional data from museum specimens, web databases, and literature. We recorded species-presence data of each species in 0.5° × 0.5° grid cells and biogeographic provinces in Mexico and Central America. We analyzed the association between vegetation types and land use. We carried out species distribution models of most species of Habromys and those tree species frequently harboring these mice, finding a high distributional congruence among mice and trees. Species of Habromys occur throughout the montane systems of Mexico and northern Central America, so they can be considered characteristic elements of the Neotropical montane cloud forests. All species of the genus occur in Mexico, whereas Guatemala and El Salvador have only one species. Although all species of Habromys are highly restricted and considered rare species, only one (H. simulatus) is currently protected by Mexican laws. We assigned two species to a high and four to the critical conservation risk. Habromys species contribute to the recognition of Mesoamerica as a biodiversity hotspot.

Digital point‐occurrence records from the Global Biodiversity Information Facility (GBIF) and other data providers enable a wide range of research in macroecology and biogeography. However, data errors may hamper immediate use. Manual data cleaning is time‐consuming and often unfeasible, given that the databases may contain thousands or millions of records. Automated data cleaning pipelines are therefore of high importance. Taking North American Ephedra as a model, we examined how different data cleaning pipelines (using, e.g., the GBIF web application, and four different R packages) affect downstream species distribution models (SDMs). We also assessed how data differed from expert data. From 13,889 North American Ephedra observations in GBIF, the pipelines removed 31.7% to 62.7% false positives, invalid coordinates, and duplicates, leading to datasets between 9484 (GBIF application) and 5196 records (manual‐guided filtering). The expert data consisted of 704 records, comparable to data from field studies. Although differences in the absolute numbers of records were relatively large, species richness models based on stacked SDMs (S‐SDM) from pipeline and expert data were strongly correlated (mean Pearson's r across the pipelines: .9986, vs. the expert data: .9173). Our results suggest that all R package‐based pipelines reliably identified invalid coordinates. In contrast, the GBIF‐filtered data still contained both spatial and taxonomic errors. Major drawbacks emerge from the fact that no pipeline fully discovered misidentified specimens without the assistance of taxonomic expert knowledge. We conclude that application‐filtered GBIF data will still need additional review to achieve higher spatial data quality. Achieving high‐quality taxonomic data will require extra effort, probably by thoroughly analyzing the data for misidentified taxa, supported by experts.

The strength of interactions between plants and river processes is mediated by plant traits and fluvial conditions, including above‐ground biomass, stem density and flexibility, channel and bed material properties, and flow and sediment regimes. In many rivers, concurrent changes in 1) the composition of riparian vegetation communities as a result of exotic species invasion and 2) shifts in hydrology have altered physical and ecological conditions in a manner that has been mediated by feedbacks between vegetation and morphodynamic processes. We review how Tamarix, which has invaded many U.S. Southwest waterways, and Populus species, woody pioneer trees that are native to the region, differentially affect hydraulics, sediment transport, and river morphology. We draw on flume, field, and modeling approaches spanning the individual seedling to river‐corridor scales. In a flume study, we found differences in the crown morphology, stem density, and flexibility of Tamarix compared to Populus influenced near‐bed flow velocities in a manner that favored aggradation associated with Tamarix. Similarly, at the patch and corridor scales, observations confirmed increased aggradation with increased vegetation density. Furthermore, long‐term channel adjustments were different for Tamarix‐ versus Populus‐dominated reaches, with faster and greater geomorphic adjustments for Tamarix. Collectively, our studies show how plant‐trait differences between Tamarix and Populus, from individual seedlings to larger spatial and temporal scales, influence the co‐adjustment of rivers and riparian plant communities. These findings provide a basis for predicting changes in alluvial riverine systems which we conceptualize as a Green New Balance model that considers how channels may adjust to changes in plant traits and community structure in additional to alterations in flow and sediment supply. We offer suggestions regarding how the Green New Balance can be used in management and invasive species management.

Abstract. Statistical climate reconstruction techniques are fundamental tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (or PDFs) can be used in various environments and with different climate proxies because they rely on elementary calibration data (i.e. modern geolocalised presence data). However, the difficulty of accessing and curating these calibration data and the complexity of interpreting probabilistic results have often limited their use in palaeoclimatological studies. Here, I introduce a new R package (crestr) to apply the PDF-based method CREST (Climate REconstruction SofTware) on diverse palaeoecological datasets and address these problems. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) associated with an extensive range of climate variables (20 terrestrial and 19 marine variables) that enables its use in most terrestrial and marine environments. Private data collections can also be used instead of, or in combination with, the provided calibration dataset. The package includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment and thus be more easily integrated with existing workflows. It is hoped that crestr will be used to produce the much-needed quantified climate reconstructions from the many regions where they are currently lacking, despite the availability of suitable fossil records. To support this development, the use of the package is illustrated with a step-by-step replication of a 790 000-year-long mean annual temperature reconstruction based on a pollen record from southeastern Africa.

Mexico hosts the highest species richness of pines (Pinus, Pinaceae) worldwide; however, the priority areas for their conservation in the country are unknown. In this study, the ecological niche of the 50 native pine species was modeled. Then, through a multi-criteria analysis, the priority areas for the conservation of the genus Pinus were identified according to the spatial patterns of richness, geographic rareness, irreplaceability, the level of vulnerability of their habitat and the status of legal protection. The results revealed that the regions with high species richness differed from those with high endemism. Also, most pine species have undergone processes of habitat degradation, having been the endemic species the most affected. The priority areas covered regions with high species richness, high endemism, and highly degraded forests, located at mountainous portions of the Baja California Peninsula, the Sierra Madre Occidental, the Sierra Madre Oriental, the Trans-Mexican Volcanic Belt, and the Sierra Madre del Sur. A low proportion of priority areas overlapped with protected areas or terrestrial regions considered priorities for biological conservation. These results suggest that conservation efforts for this genus should be focused beyond regions with high species richness and current protected areas. Besides, the priority areas identified in this study can be the basis to create biological corridors and new protected areas, which could contribute significantly to the conservation of this genus in Mexico.