Reinhold Conrad Muschler

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.

Abstract Background and Aims The hart’s tongue fern (HTF) complex is a monophyletic group composed of five geographically segregated members with divergent abundance patterns across its broad geographic range. We postulated hierarchical systems of environmental controls in which climatic and land-use change drive abundance patterns at the global scale, while various ecological conditions function as finer-scale determinants that further increase geographic disparities at regional to local scales. Methods After quantifying the abundance patterns of the HTF complex, we estimated their correlations with global climate and land-use dynamics. Regional determinants were assessed using boosted regression tree models with 18 potential ecological variables. Moreover, we investigated long-term population trends in the U.S. to understand the interplay of climate change and anthropogenic activities on a temporal scale. Key Results Latitudinal climate shifts drove latitudinal abundance gradients, and regionally different levels of land-use change resulted in global geographic disparities in population abundance. At a regional scale, population isolation, which accounts for rescue effects, played an important role, particularly in Europe and East Asia where several hotspots occurred. Furthermore, the variables most strongly influencing abundance patterns greatly differed by region: precipitation seasonality in Europe, spatial heterogeneity of temperature and precipitation in East Asia, and magnitudes of past climate change, temperature seasonality, and edaphic conditions in North America. In the U.S., protected populations showed increasing trends compared to unprotected populations at the same latitude, highlighting the critical role of habitat protection in conservation measures. Conclusions Geographic disparities in the abundance patterns of HTF complex were determined by hierarchical systems of environmental controls, wherein climatic and land-use dynamics act globally but are modulated by various regional and local determinants operating at increasingly finer scales. We highlighted that fern conservation must be tailored to particular geographic contexts and environmental conditions by incorporating a better understanding of the dynamics acting at different spatiotemporal scales.

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.

Angola has a great diversity of species and ecosystems and a high level of endemism. However, knowledge of the native flora remains very incomplete and outdated. Leguminosae is the largest family in the country, including many species which are of local or more regional economic importance. Based on an extensive review of bibliographic sources, natural history collections, and online databases, the checklist of Angolan Leguminosae plants was updated, including data on their native distribution, conservation status, and principal uses. The endemic taxa were the subject of additional investigation, including the main habitat, the number of collections preserved in herbaria, and the locality of the first collection. We identified 953 Leguminosae taxa occurring in Angola, of which 165 are endemic to the country. Among the 180 genera found, Crotalaria (136) and Indigofera (96) have the highest number of taxa. Almost half of the studied species have important applications, mainly in traditional medicine (385), forage (267), timber (188), and food (120). Nevertheless, only 27.7% have been assessed according to the IUCN Red List and 10 species are classified as threatened. Thirty-three endemics are known only from the type specimen, revealing the lack of knowledge on these species and the need for further field research. More than 30 type specimens were collected in the Serra da Chela, which highlights the importance of this region for biodiversity conservation.

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.

An updated checklist of Mozambique’s vascular plants is presented. It was compiled referring to several information sources such as existing literature, relevant online databases and herbaria collections. The checklist includes 7,099 taxa (5,957 species, 605 subspecies, 537 varieties), belonging to …

The Qinghai-Tibetan Plateau (QTP) harbors abundant and diverse plant life owing to its high habitat heterogeneity. However, the distribution pattern of biodiversity hotspots and their conservation status remain unclear. Based on 148,283 high-resolution occurrence coordinates of 13,450 seed plants, w…

Plant invasion has been proved to threaten biodiversity conservation and ecosystem maintenance at a global scale. It is a challenge to project suitable habitat distributions of invasive plant species (IPS) for invasion risk assessment at large spatial scales. Interaction outcomes between native and …

In sub-Saharan Africa, grain legumes (pulses) are essential food sources and play an important role in sustainable agriculture. Among the major pulse crops, the native cowpea (Vigna unguiculata) and introduced common bean (Phaseolus vulgaris) stand out. This paper has two main goals. First, we provi…

Question: Do invasions by invasive plant species with contrasting trait profiles (Arctotheca calendula, Carpobrotus spp., Conyza bonariensis, and Opuntia dillenii) change the climatic niche of coastal plant communities? Location: Atlantic coastal habitats in Huelva (Spain). Methods: We identifi…