Edmond Joseph Klein

Habitat suitability calculated from species distribution models (SDMs) has been used to assess population performance, but empirical studies have provided weak or inconclusive support to this approach. Novel approaches measuring population distances to niche centroid and margin in environmental space have been recently proposed to explain population performance, particularly when populations experience exceptional environmental conditions that may place them outside of the species niche. Here, we use data of co‐occurring species' decay, gathered after an extreme drought event occurring in the southeast of the Iberian Peninsula which highly affected rich semiarid shrubland communities, to compare the relationship between population decay (mortality and remaining green canopy) and 1) distances between populations' location and species niche margin and centroid in the environmental space, and 2) climatic suitability estimated from frequently used SDMs (here MaxEnt) considering both the extreme climatic episode and the average reference climatic period before this. We found that both SDMs‐derived suitability and distances to species niche properly predict populations performance when considering the reference climatic period; but climatic suitability failed to predict performance considering the extreme climate period. In addition, while distance to niche margins accurately predict both mortality and remaining green canopy responses, centroid distances failed to explain mortality, suggesting that indexes containing information about the position to niche margin (inside or outside) are better to predict binary responses. We conclude that the location of populations in the environmental space is consistent with performance responses to extreme drought. Niche distances appear to be a more efficient approach than the use of climate suitability indices derived from more frequently used SDMs to explain population performance when dealing with environmental conditions that are located outside the species environmental niche. The use of this alternative metrics may be particularly useful when designing conservation measures to mitigate impacts of shifting environmental conditions.

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.

Cultivated plants provide food, fiber, and energy but they can escape, de-domesticate, colonize agroecosystems as weeds, and disrupt natural ecosystems as invasive species. Escape and invasion depend on traits of the species, type and rate of domestication, and cultivation context. Understanding this “de-domestication invasion process” is critical for managing conservation efforts to reduce unintended consequences of cultivated species in novel areas. Cannabis (Cannabis sativa L.) is an ideal case study to explore this process because it was one of the earliest plants to co-evolve with humans, has a crop to weed history, and has been introduced and cultivated globally. Moreover, recent liberalization of cannabis cultivation and use policies have raised concerns about invasion risk. Here, we synthesize knowledge on cannabis breeding, cultivation, and processing relevant to invasion risk and outline research and management priorities to help overcome the research deficit on the invasion ecology of the species. Understanding the transition of cannabis through the de-domestication-invasion process will inform policy and minimize agricultural and environmental risks associated with cultivation of domesticated species.

Abstract. Artemisia, along with Chenopodiaceae, is the dominant component growing in the desert and dry grassland of the Northern Hemisphere. Artemisia pollen with its high productivity, wide distribution, and easy identification is usually regarded as an eco-indicator for assessing aridity and distinguishing grassland from desert vegetation in terms of the pollen relative abundance ratio of Chenopodiaceae/Artemisia (C/A). Nevertheless, divergent opinions on the degree of aridity evaluated by Artemisia pollen have been circulating in the palynological community for a long time. To solve the confusion, we first selected 36 species from nine clades and three outgroups of Artemisia based on the phylogenetic framework, which attempts to cover the maximum range of pollen morphological variation. Then, sampling, experiments, photography, and measurements were taken using standard methods. Here, we present pollen datasets containing 4018 original pollen photographs, 9360 pollen morphological trait measurements, information on 30 858 source plant occurrences, and corresponding environmental factors. Hierarchical cluster analysis on pollen morphological traits was carried out to subdivide Artemisia pollen into three types. When plotting the three pollen types of Artemisia onto the global terrestrial biomes, different pollen types of Artemisia were found to have different habitat ranges. These findings change the traditional concept of Artemisia being restricted to arid and semi-arid environments. The data framework that we designed is open and expandable for new pollen data of Artemisia worldwide. In the future, linking pollen morphology with habitat via these pollen datasets will create additional knowledge that will increase the resolution of the ecological environment in the geological past. The Artemisia pollen datasets are freely available at Zenodo (https://doi.org/10.5281/zenodo.6900308; Lu et al., 2022).

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 spread and outbreaks of phytophagous pests are often associated with global warming. In addition to economic interest, these species may be of interest in terms of biological indication of climate changes. In this context, we considered the locust digitate leafminer Parectopa robiniella Clemens, 1863 (Lepidoptera: Gracillariidae). This phytophage was first discovered in Europe in 1970 near Milano in Italy. Since then, it has been spreading across the continent. In Ukraine, it was recorded for the first time in 2003. In 2020–2021, we found areas of massive leaf damage caused by the black locust (Robinia pseudoacacia) in locations on Trukhaniv Island in Kyiv and some places in the Kyiv administrative region. Using 1041 georeferenced records of P. robiniella across Europe and a Bayesian additive regression trees algorithm (BART), we modeled the distribution of the moth. Predictors of current climate (WorldClim v.2, CliMond v.1.2 and ENVIREM) and a black locust habitat suitability raster were employed. Sets of SDMs built for P. robiniella with and without the habitat suitability raster for the host tree performed equally well. Amongst the factors that determine the niche of the locust digitate leafminer, most important are temperature-related conditions assumed to facilitate the spread and naturalization of the pest. In Ukraine, the appearance of the moth has coincided with increasing mean annual temperatures. Particularly favorable for the species are areas in the west and south-west of the country, and Transcarpathia. In the near future, the moth could reach locations in Nordic countries, Estonia, the British Isles, Black Sea coastal areas in Turkey, further into Russia, etc.

Climate change is now a reality and is altering ecosystems, with Canada experiencing 2–4 times the global average rate of warming. This will have a critical impact on berry cultivation and horticulture. Enhancing our understanding of how wild and cultivated berries will perform under changing climates will be essential to mitigating impacts on ecosystems, culture and food security. Our objective was to predict the impact of climate change on habitat suitability of four berry producing Vaccinium species: two species with primarily northern distributions (V. uliginosum, V. vitis-idaea), one species with a primarily southern distribution (V. oxycoccos), and the commercially cultivated V. macrocarpon. We used the maximum entropy (Maxent) model and the CMIP6 shared socioeconomic pathways (SSPs) 126 and 585 projected to 2041–2060 and 2061–2080. Wild species showed a uniform northward progression and expansion of suitable habitat. Our modeling predicts that suitable growing regions for commercial cranberries are also likely to shift with some farms becoming unsuitable for the current varieties and other regions becoming more suitable for cranberry farms. Both V. macrocarpon and V. oxycoccos showed a high dependence on precipitation-associated variables. Vaccinium vitis-idaea and V. uliginosum had a greater number of variables with smaller contributions which may improve their resilience to individual climactic events. Future competition between commercial cranberry farms and wild berries in protected areas could lead to conflicts between agriculture and conservation priorities. New varieties of commercial berries are required to maintain current commercial berry farms.

Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation. By analysing the state of representation of traditional varieties of 25 major crops in ex situ repositories, this study demonstrates conservation progress made over more than a half-century and identifies the gaps remaining to be filled.

Biological communities are reshuffling owing to species range shifts in response to climate change. This process inherently leads to novel assemblages of interacting species. Yet, how climatic change and local dynamics in biotic interactions jointly affect range shifts is still poorly understood.We combine a unique long‐term transplant competition‐exclusion experiment with species distribution models (SDMs) to test the effects of biotic interactions on understorey species range shifts under climate change in European temperate forests. Using a time‐series of 18 years of individual‐level demographic data of four common understorey plant species transplanted beyond their cold range edge to plots with and without interspecific competition, we built integral projection models (IPMs) and analysed the effects of competition on five key vital rates and population growth. We assessed the results of the transplant experiment in the context of the modelled species’ current and future potential distributions.We find that species’ population performances in the transplant experiment decreased with lower predicted habitat suitability from the SDMs. The population performance at the transplant sites was mediated by biotic interactions with the local plant community: for two species with intermediate levels of predicted habitat suitability at the transplant sites, competition effects could explicitly differentiate between net population growth (λ > 1) or shrinkage (λ < 1).Synthesis: Our findings contest the long‐standing idea that at cold range edges, mainly abiotic factors structure species’ distributions. We conclude that biotic interactions, through acting on local population dynamics, may impact species distributions at the continental scale. Hence, predicting climate‐change impacts on biodiversity redistributions ultimately requires us to also integrate dynamics in biotic interactions.

BACKGROUND In the coming decades, geographical distribution patterns of farmland organisms may undergo drastic changes due to climate change, with significant implications for global food security. In China, Rhopalosiphum maidis and its spread of sugarcane mosaic virus (ScMV) can become an increasingly serious threat to maize (Zea mays) production. We conducted ecological niche modeling for Z. mays, R. maidis, and ScMV under current and future (2041–2060 and 2081–2100) climate scenarios by using MaxEnt software to explore changes in this system. RESULTS The Heihe-Tengchong line (an imaginary separation line of human population density) can divide China into main (east of the line) and secondary (west of the line) habitats for the three species. With climate change, rapid expansion in suitable areas is projected for ScMV and the aphid vector R. maidis. Taking species interactions into consideration, our overlaying analyses show that most areas east of the Heihe-Tengchong line (optimal for maize and suitable for R. maidis) will become increasingly highly suitable for ScMV, suggesting that the prevention and control of this plant virus and its aphid vector in China's main maize-growing areas (e.g. northeast) will become an increasing challenge in the future. CONCLUSION Climate change will profoundly affect ScMV–vector–maize interactions, which may contribute favorably to invasion of this virus into new areas. Our comprehensive and in-depth analyses on shifts in this multi-species system under climate change provide useful and insightful information for devising strategies for the prevention and control of plant viruses and aphid vectors on maize in the future. © 2022 Society of Chemical Industry.