Theodor Loesener

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

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.

Identifying climatic refugia is important for long-term conservation planning under climate change. Riparian areas have the potential to provide climatic refugia for wildlife, but literature remains limited, especially for plants. This study was conducted with the purpose of identifying climatic refugia of plant biodiversity in the portion of the Mekong River Basin located in Xishuangbanna, China. We first predicted the current and future (2050s and 2070s) potential distribution of 50 threatened woody species in Xishuangbanna by using an ensemble of small models, then stacked the predictions for individual species to derive spatial biodiversity patterns within each 10 × 10 km grid cell. We then identified the top 17 % of the areas for spatial biodiversity patterns as biodiversity hotspots, with climatic refugia defined as areas that remained as biodiversity hotspots over time. Stepwise regression and linear correlation were applied to analyze the environmental correlations with spatial biodiversity patterns and the relationships between climatic refugia and river distribution, respectively. Our results showed potential upward and northward shifts in threatened woody species, with range contractions and expansions predicted. The spatial biodiversity patterns shift from southeast to northwest, and were influenced by temperature, precipitation, and elevation heterogeneity. Climatic refugia under climate change were related closely to river distribution in Xishuangbanna, with riparian areas identified that could provide climatic refugia. These refugial zones are recommended as priority conservation areas for mitigating the impacts of climate change on biodiversity. Our study confirmed that riparian areas could act as climatic refugia for plants and emphasizes the conservation prioritization of riparian areas within river basins for protecting biodiversity under climate change.

Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.

Aim The relationships between biome shifts and global environmental changes in temperate zone habitats have been extensively explored; yet, the historical dynamics of taxa found in the tropical rain forest (TRF) remain poorly known. This study aims to reconstruct the relationships between tropical rain forest shifts and global environmental changes through the patterns of historical biogeography of a pantropical family of monocots, the Zingiberaceae. Location Global. Taxon Zingiberaceae. Methods We sampled DNA sequences (nrITS, trnK, trnL-trnF and psbA-trnH) from GenBank for 77% of the genera, including 30% of species, in the Zingiberaceae. Global fossil records of the Zingiberaceae were collected from literatures. Rates of speciation, extinction and diversification were estimated based on phylogenetic data and fossil records through methods implemented in BAMM. Ancestral ranges were estimated using single-tree BioGeoBEARS and multiple-trees BioGeoBEARS in RASP. Dispersal rate through time and dispersal rate among regions were calculated in R based on the result of ancestral estimation. Results The common ancestor of the Zingiberaceae likely originated in northern Africa during the mid-Cretaceous, with later dispersal to the Asian tropics. Indo-Burma, rather than Malesia, was likely a provenance of the common ancestor of Alpinioideae–Zingiberoideae. Several abrupt shifts of evolutionary rates from the Palaeocene were synchronized with sudden global environmental changes. Main conclusions Integrating phylogenetic patterns with fossil records suggests that the Zingiberaceae dispersed to Asia through drift of the Indian Plate from Africa in the late Palaeocene. Formation of island chains, land corridors and warming temperatures facilitated the emigration of the Zingiberaceae to a broad distribution across the tropics. Moreover, dramatic fluctuations of the speciation rate of Zingiberoideae appear to have been synchronized with global climate fluctuations. In general, the evolutionary history of the Zingiberaceae broadens our understanding of the association between TRF shifts in distribution and past global environmental changes, especially the origin of TRF in Southeast Asia.

Aims Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence–habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past and recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence–habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence–habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of ARCs, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximize the temporal range of anthropogenic predictors, exclude mismatched occurrences and test for residual data misrepresentations.

During the early to middle Eocene, a mid‐to‐high latitudinal position and enhanced hydrological cycle in Australia would have contributed to a wetter and “greener” Australian continent where today arid to semi‐arid climates dominate. Here, we revisit 12 southern Australian plant megafossil sites from the early to middle Eocene to generate temperature, precipitation and seasonality paleoclimate estimates, net primary productivity (NPP) and vegetation type, based on paleobotanical proxies and compare to early Eocene global climate models. Temperature reconstructions are uniformly subtropical (mean annual, summer, and winter mean temperatures 19–21 °C, 25–27 °C and 14–16 °C, respectively), indicating that southern Australia was ∼5 °C warmer than today, despite a >20° poleward shift from its modern geographic location. Precipitation was less homogeneous than temperature, with mean annual precipitation of ∼60 cm over inland sites and >100 cm over coastal sites. Precipitation may have been seasonal with the driest month receiving 2–7× less than mean monthly precipitation. Proxy‐model comparison is favorable with an 1680 ppm CO2 concentration. However, individual proxy reconstructions can disagree with models as well as with each other. In particular, seasonality reconstructions have systemic offsets. NPP estimates were higher than modern, implying a more homogenously “green” southern Australia in the early to middle Eocene, when this part of Australia was at 48–64 °S, and larger carbon fluxes to and from the Australian biosphere. The most similar modern vegetation type is modern‐day eastern Australian subtropical forest, although distance from coast and latitude may have led to vegetation heterogeneity.

We present a composite terrestrial pollen record of latest Eocene through Oligocene (35.5–23 Ma) vegetation and climate change from the Gippsland Basin of south-eastern Australia. Climates were overwhelmingly mesothermic through this time period, with mean annual temperature (MAT) varying between 13 and 18 °C, with an average of 16 °C. We provide evidence to support a cooling trend through the Eocene–Oligocene Transition (EOT), but also identify three subsequent warming cycles through the Oligocene, leading to more seasonal climates at the termination of the Epoch. One of the warming episodes in the Early Oligocene appears to have also occurred at two other southern hemisphere sites at the Drake Passage as well as off eastern Tasmania, based on recent research. Similarities with sea surface temperature records from modern high southern latitudes which also record similar cycles of warming and cooling, are presented and discussed. Annual precipitation varied between 1200 and 1700 mm/yr, with an average of 1470 mm/yr through the sequence. Notwithstanding the extinction of Nothofagus sg. Brassospora from Australia and some now microthermic humid restricted Podocarpaceae conifer taxa, the rainforest vegetation of lowland south-eastern Australia is reconstructed to have been similar to present day Australian Evergreen Notophyll Vine Forests existing under the sub-tropical Köppen-Geiger climate class Cfa (humid subtropical) for most of the sequence. Short periods of cooler climates, such as occurred through the EOT when MAT was ~ 13 °C, may have supported vegetation similar to modern day Evergreen Microphyll Fern Forest. Of potentially greater significance, however, was a warm period in the Early to early Late Oligocene (32–26 Ma) when MAT was 17–18 °C, accompanied by small but important increases in Araucariaceae pollen. At this time, Araucarian Notophyll/Microphyll Vine Forest likely occurred regionally.

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…