Félix Heuertz

It would be advantageous to grow legume forage crops in order to increase the productivity and sustainability of sloped croplands in Hamkyongbukdo. In particular, the identification of potential cultivation areas for alfalfa in the given region could aid decision-making on policies and management related to forage crop production in the future. This study aimed to analyze the climate suitability of alfalfa in Hamkyongbukdo under current and future climate conditions using the Fuzzy Union model. The climate suitability predicted by the Fuzzy Union model was compared with the actual alfalfa cultivation area in the northern United States. Climate data obtained from 11 global climate models were used as input data for calculation of climate suitability in the study region to examine the uncertainty of projections under future climate conditions. The area where the climate suitability index was greater than a threshold value (22.6) explained about 44% of the variation in actual alfalfa cultivation areas by state in the northern United States. The climatic suitability of alfalfa was projected to decrease in most areas of Hamkyongbukdo under future climate scenarios. The climatic suitability in Onseong and Gyeongwon County was analyzed to be over 88 in the current climate conditions. However, it was projected to decrease by about 66% in the given areas by the 2090s. Our study illustrated that the impact of climate change on suitable cultivation areas was highly variable when different climate data were used as inputs to the Fuzzy Union model. Still, the ensemble of the climate suitability projections for alfalfa was projected to decrease considerably due to summer depression in Hamkyongbukdo. It would be advantageous to predict suitable cultivation areas by adding soil conditions or to predict the climate suitability of other leguminous crops such as hairy vetch, which merits further studies.

Climate change has been suggested as an important human-induced driver for the ongoing sixth mass extinction. As a common response to climate change, and particularly global warming, species move toward higher latitudes or shift uphill. Furthermore, rapid climate change impacts the biotic interactions of species, particularly in the case of Zygaenid moths which exhibit high specialization in both habitat and host plant preferences. Iranian Zygaenidae are relatively well-known and represent a unique fauna with a high endemism rate (46%) in the whole Palearctic; as such they are a good model group to study the impact of climate change on future distributions. In this study, we used species distribution models (SDMs) and ensembles of small models (ESMs) to investigate the impact of climate change on the future distribution of endemic and non-endemic species of zygaenids, as well as their larval host plants. Three different climate scenarios were applied to forecast the probable responses of the species to different climate change intensities. Our results suggest that the central and southern parts of the country will be impacted profoundly by climate change compared to the northern regions. Beyond this, most endemic species will experience an altitudinal shift from their current range, while non-endemic species may move towards higher latitudes. Considering that the regions with higher diversity of zygaenids are limited to mountainous areas, mainly within the Irano-Anatolian biodiversity hotspot, the identification of their local high diversity regions for conservation practices has a high priority.

The threat of invasive species to biodiversity and ecosystem structure is exacerbated by the increasingly concerning outlook of predicted climate change and other human influences. Developing preventative management strategies for invasive plant species before they establish is crucial for effective management. To examine how climate change may impact habitat suitability, we modeled the current and future habitat suitability of two terrestrial species, Geranium lucidum and Pilosella officinarum , and two aquatic species, Butomus umbellatus and Pontederia crassipes , that are relatively new invasive plant species regionally, and are currently spreading in the Pacific Northwest (PNW, North America), an area of unique natural areas, vibrant economic activity, and increasing human population. Using North American presence records, downscaled climate variables, and human influence data, we developed an ensemble model of six algorithms to predict the potential habitat suitability under current conditions and projected climate scenarios RCP 4.5, 7.0, and 8.5 for 2050 and 2080. One terrestrial species ( P. officinarum ) showed declining habitat suitability in future climate scenarios (contracted distribution), while the other terrestrial species ( G. lucidum ) showed increased suitability over much of the region (expanded distribution overall). The two aquatic species were predicted to have only moderately increased suitability, suggesting aquatic plant species may be less impacted by climate change. Our research provides a template for regional-scale modelling of invasive species of concern, thus assisting local land managers and practitioners to inform current and future management strategies and to prioritize limited available resources for species with expanding ranges.

The first comprehensive species distribution models for orchid, its fungal symbionts and pollinator are presented. To evaluate impact of global warming on these organisms three different projections and four various climate change scenarios were analysed. The niche modelling was based on presence-only records of Limodorum abortivum , two species of Russula and three insects pollinating orchid ( Anthophora affinis, Bombus terrestris, Rhodanthidium septemdentatum ). Two sets of orchid predictions were examined—the first one included only climatic data and the second one was based on climate data and data on future distribution of orchid fungal symbionts. Overall, a poleward range shift is predicted to occur as a result of climate change and apparently global warming will be favorable for L. abortivum and its potential geographical range will expand. However, due to the negative effect of global warming on fungal symbionts of L. abortivum , the actual extension of the suitable niches of the orchid will be much limited. Considering future possibility of cross-pollination, the availability of A. affinis for L. abortivum will decrease and this bee will be available in the worst case scenarios only for 21% of orchid populations. On the other hand, the overlap of orchid and the buff-tailed bumblebee will increase and as much as 86.5% of plant populations will be located within B. terrestris potential range. Also the availability of R. septemdentatum will be higher than currently observed in almost all analysed climate change projections. This study showed the importance of inclusion of ecological factors in species distribution models as the climate data itself are not enough to estimate the future distribution of plant species. Moreover, the availability of pollen vectors which is crucial for long-term survival of orchid populations should be analysed in context of climate changes.

Many studies have quantified ecological impacts of individual foundation species (FS). However, emerging data suggest that FS often co‐occur, potentially inhibiting or facilitating one another, thereby causing indirect, cascading effects on surrounding communities. Furthermore, global warming is accelerating, but little is known about how interactions between co‐occurring FS vary with temperature.Shallow aquatic sedimentary systems are often dominated by three types of FS: slower‐growing clonal angiosperms, faster‐growing solitary seaweeds, and shell‐forming filter‐ and deposit‐feeding bivalves. Here, we tested the impacts of one FS on another by analyzing manipulative interaction experiments from 148 papers with a global meta‐analysis.We calculated 1,942 (non‐independent) Hedges’ g effect sizes, from 11,652 extracted values over performance responses, such as abundances, growths or survival of FS, and their associated standard deviations and replication levels. Standard aggregation procedures generated 511 independent Hedges’ g that was classified into six types of reciprocal impacts between FS.We found that (i) seaweeds had consistent negative impacts on angiosperms across performance responses, organismal sizes, experimental approaches, and ecosystem types; (ii) angiosperms and bivalves generally had positive impacts on each other (e.g., positive effects of angiosperms on bivalves were consistent across organismal sizes and experimental approaches, but angiosperm effect on bivalve growth and bivalve effect on angiosperm abundance were not significant); (iii) bivalves positively affected seaweeds (particularly on growth responses); (iv) there were generally no net effects of seaweeds on bivalves (except for positive effect on growth) or angiosperms on seaweeds (except for positive effect on ‘other processes’); and (v) bivalve interactions with other FS were typically more positive at higher temperatures, but angiosperm‐seaweed interactions were not moderated by temperature.Synthesis: Despite variations in experimental and spatiotemporal conditions, the stronger positive interactions at higher temperatures suggest that facilitation, particularly involving bivalves, may become more important in a future warmer world. Importantly, addressing research gaps, such as the scarcity of FS interaction experiments from tropical and freshwater systems and for less studied species, as well as testing for density‐dependent effects, could better inform aquatic ecosystem conservation and restoration efforts and broaden our knowledge of FS interactions in the Anthropocene.

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.

Premise Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models Methods In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal. Key Results We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models are able to predict North American summer occurrences very well. Conclusions The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.

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).

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.

Climate change causes environmental variation worldwide, which is one of the most serious threats to global food security. In addition, more than 2 billion people in the world are reported to suffer from serious malnutrition, referred to as ‘hidden hunger.’ Dependence on only a few crops could lead to the loss of genetic diversity and high fragility of crop breeding in systems adapting to global scale climate change. The exploitation of underutilized species and genetic resources, referred to as orphan crops, could be a useful approach for resolving the issue of adaptability to environmental alteration, biodiversity preservation, and improvement of nutrient quality and quantity to ensure food security. Moreover, the use of these alternative crops will help to increase the human health benefits and the income of farmers in developing countries. In this review, we highlight the potential of orphan crops, especially amaranths, for use as vegetables and health-promoting nutritional components. This review highlights promising diversified sources of amaranth germplasms, their tolerance to abiotic stresses, and their nutritional, phytochemical, and antioxidant values for vegetable purposes. Betalains (betacyanins and betaxanthins), unique antioxidant components in amaranth vegetables, are also highlighted regarding their chemodiversity across amaranth germplasms and their stability and degradation. In addition, we discuss the physiological functions, antioxidant, antilipidemic, anticancer, and antimicrobial activities, as well as the biosynthesis pathway, molecular, biochemical, genetics, and genomic mechanisms of betalains in detail.