Charles Victor Naudin

Plant adaptation to drought facilitates major ecological transitions, and will likely play a vital role under looming climate change. Mycorrhizas, i.e. strategic associations between plant roots and soil-borne symbiotic fungi, can exert strong influence on the tolerance to drought of extant plants. Here, I show how mycorrhizal strategy and drought adaptation have been shaping one another throughout the course of plant evolution. To characterize the evolutions of both plant characters, I applied a phylogenetic comparative method using data of 1,638 extant species globally distributed. The detected correlated evolution unveiled gains and losses of drought tolerance occurring at faster rates in lineages with ecto- or ericoid mycorrhizas, which were on average about 15 and 300 times faster than in lineages with the arbuscular mycorrhizal and naked root (non-mycorrhizal alone or with facultatively arbuscular mycorrhizal) strategy, respectively. My study suggests that mycorrhizas can play a key facilitator role in the evolutionary processes of plant adaptation to critical changes in water availability across global climates. Phylogenetic comparative analysis using data of 1,638 species of angiosperms and gymnosperms suggests that the evolution of plant adaptation to critical environmental change in water availability across global climates is dependent on mycorrhizas.

The analysis of climate change impact is essential to include in conservation planning of crop wild relatives (CWR) to provide the guideline for adequate long-term protection under unpredictable future environmental conditions. These resources play an important role in sustaining the future of food security, but the evidence shows that they are threatened by climate change. The current analyses show that five taxa were predicted to have contraction of more than 30 % of their current ranges: Artocarpus sepicanus (based on RCP 4.5 in both no dispersal and unlimited dispersal scenario and RCP 8.5 in no dispersal scenario by 2050), Ficus oleifolia (RCP 4.5 5 in both no dispersal and unlimited dispersal scenario by 2080), Cocos nucifera and Dioscorea alata (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050), and Ficus chartacea (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050 and 2080). It shows that the climate change impact is species-specific. Representative Concentration Pathways (RCP) of greenhouse gas (GHG) emission and dispersal scenarios influence the prediction models, and the actual future distribution range of species falls in between those scenarios. Climate refugia, holdout populations, and non-analogue community assemblages were identified based on the Protected Areas (PAs) network. PAs capacity is considered an important element in implementing a conservation strategy for the priority CWR. In areas where PAs are isolated and have less possibility to build corridors to connect each other, such as in Java, unlimited dispersal scenarios are unlikely to be achieved and assisted dispersal is suggested. The holdout populations should be the priority target for the ex situ collection. Therefore, by considering the climate refugia, PAs capacity and holdout populations, the goal of keeping high genetic variations for the long-term conservation of CWR in Indonesia can be achieved.

Climate change is one of the most serious threats to global crops production at present and it will continue to be the largest threat in the future worldwide. Knowing how climate change affects crop productivity might help sustainability and crop improvement efforts. Under existing and projected climate change scenarios (2050s and 2070s in Ethiopia), the effect of global warming on the distribution of V. radiata and V. unguiculata was investigated. MaxEnt models were used to predict the current and future distribution pattern changes of these crops in Ethiopia using different climate change scenarios (i.e., lowest (RCP 2.6), moderate (RCP 4.5), and extreme (RCP 8.5)) for the years 2050s and 2070s. The study includes 81 and 68 occurrence points for V. radiata and V. unguiculata, respectively, along with 22 environmental variables. The suitability maps indicate that the Beneshangul Gumuz, Oromia, Amhara, SNNPR, and Tigray regions are the major Ethiopian regions with the potential to produce V. radiata, while Amhara, Gambella, Oromia, SNNPR, and Tigray are suitable for producing V. unguiculata. The model prediction for V. radiata habitat ranges distribution in Ethiopia indicated that 1.69%, 4.27%, 11.25% and 82.79% are estimated to be highly suitable, moderately suitable, less suitable, and unsuitable, respectively. On the other hand, the distribution of V. unguiculata is predicted to have 1.27%, 3.07%, 5.22%, and 90.44% habitat ranges that are highly suitable, moderately suitable, less suitable, and unsuitable, respectively, under the current climate change scenario by the year (2050s and 2070s) in Ethiopia. Among the environmental variables, precipitation of the wettest quarter (Bio16), solar radiation index (SRI), temperature seasonality (Bio4), and precipitation seasonality (Bio15) are discovered to be the most effective factors for defining habitat suitability for V. radiata, while precipitation of the wettest quarter (Bio16), temperature annual range (Bio7) and precipitation of the driest quarter (Bio17) found to be better habitat suitability indicator for V. unguiculata in Ethiopia. The result indicates that these variables were more relevant in predicting suitable habitat for these crops in Ethiopia. A future projection predicts that the suitable distribution region will become increasingly fragmented. In general, the study provides a scientific basis of suitable agro-ecological habitat for V. radiata and V. unguiculata for long-term crop management and production improvement in Ethiopia. Therefore, projections of current and future climate change impacts on such crops are vital to reduce the risk of crop failure and to identify the potential productive areas in the country.

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.

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…

Aim: Given the importance of environmental heterogeneity as a driver of species richness through its effects on species diversification and coexistence, we asked whether the dramatic difference in species richness per unit area between two similar Mediterranean‐type biodiversity hotspots is explaine…

Antibiotic resistance and viral diseases are rising around the world and are becoming major threats to global health, food security, and development. One measure that has been suggested to mitigate this crisis is the development of new antibiotics. Here, we provide a comprehensive evaluation of the …

Species of plants with different life history strategies may differ in their seed dispersal mechanisms, impacting their distribution and diversification patterns. Shorter or longer distance dispersal is favored by different dispersal modes, facilitating (or constraining) population isolation, which …

Premise: The field of biodiversity informatics has developed rapidly in recent years, with broad availability of large‐scale information resources. However, online biodiversity information is biased spatially as a result of slow and uneven capture and digitization of existing data resources. The Wes…

In addition to their potential against deforestation and climate change, agroforestry systems may have a relevant role in biodiversity conservation. In this sense, not only species richness per se, but also community composition, including the distribution range of the species, should be considered.…