Ciencia habilitada por datos de especímenes

Marchuk, E. A., A. K. Kvitchenko, L. A. Kameneva, A. A. Yuferova, and D. E. Kislov. 2024. East Asian forest-steppe outpost in the Khanka Lowland (Russia) and its conservation. Journal of Plant Research 137: 997–1018. https://doi.org/10.1007/s10265-024-01570-z

The Khanka Lowland forest-steppe is the most eastern outpost of the Eurasian steppe biome. It includes unique grassland plant communities with rare steppe species. These coenosis have changed under the influence of anthropogenic activity, especially during the last 100 years and included both typical steppe species and nemoral mesophytic species. To distinguish these ecological groups of plants the random forest method with three datasets of environmental variables was applied. Specifically, a model of classification with the most important bioindices to predict a mesophytic ecological group of plants with a sensitivity greater than 80% was constructed. The data demonstrated the presence of steppe species that arrived at different times in the Primorye Territory. Most of these species are associated with the Mongolian-Daurian relict steppe complex and habit in the Khanka Lowland. Other species occur only in mountains in Primorye Territory and do not persist in the Khanka Lowland. These findings emphasize the presence of relict steppe communities with a complex of true steppe species in the Khanka Lowland. Steppe communities exhibit features of anthropogenic influence definitely through the long land use period but are not anthropogenic in origin. The most steppe species are located at the eastern border of distribution in the Khanka Lowlands and are valuable in terms of conservation and sources of information about steppe species origin and the emergence of the steppe biome as a whole.

Bürger, M., and J. Chory. 2024. A potential role of heat‐moisture couplings in the range expansion of Striga asiatica. Ecology and Evolution 14. https://doi.org/10.1002/ece3.11332

Parasitic weeds in the genera Orobanche, Phelipanche (broomrapes) and Striga (witchweeds) have a devastating impact on food security across much of Africa, Asia and the Mediterranean Basin. Yet, how climatic factors might affect the range expansion of these weeds in the context of global environmental change remains unexplored. We examined satellite‐based environmental variables such as surface temperature, root zone soil moisture, and elevation, in relation to parasitic weed distribution and environmental conditions over time, in combination with observational data from the Global Biodiversity Information Facility (GBIF). Our analysis reveals contrasting environmental and altitude preferences in the genera Striga and Orobanche. Asiatic witchweed (Striga asiatica), which infests corn, rice, sorghum, and sugar cane crops, appears to be expanding its range in high elevation habitats. It also shows a significant association with heat‐moisture coupling events, the frequency of which is rising in such environments. These results point to geographical shifts in distribution and abundance in parasitic weeds due to climate change.

Ferreira, G. E., J. L. Clark, L. Clavijo, A. Zuluaga, A. Chautems, M. J. G. Hopkins, A. O. Araujo, and M. Perret. 2024. Phylogenetics, character evolution, and historical biogeography of the Neotropical genus Besleria (Gesneriaceae). Botanical Journal of the Linnean Society. https://doi.org/10.1093/botlinnean/boae007

Besleria, a genus of perennial herbs, shrubs, or small trees growing in the understorey of rainforests, is one of the largest genera of neotropical Gesneriaceae, with over 165 species. Despite the ecological importance and ubiquity of Besleria in rainforest ecosystems, taxonomic and evolutionary studies of Besleria are limited. Here, we generated a phylogenetic analysis of Besleria using four nuclear and chloroplast DNA regions (ITS, matK, rps16, and trnL-trnF) covering more than 50% of the recognized species, along with two secondary calibration points to infer divergence times. Our results support the monophyly of Besleria and allowed us to revise the infrageneric classification and biogeographical history of the genus. We identified five major clades that do not correspond to sections or subsections in previous classifications. These clades are well circumscribed geographically but remain difficult to characterize using previously hypothesized morphological characters. Biogeographical reconstructions indicate an origin in the northern Andes during the Middle Miocene (ca. 15 Mya). The current distribution patterns of this plant group have been significantly shaped by geological and climatic events, particularly Andean uplift and the formation of the Panama Isthmus.

Noori, S., A. Hofmann, D. Rödder, M. Husemann, and H. Rajaei. 2024. A window to the future: effects of climate change on the distribution patterns of Iranian Zygaenidae and their host plants. Biodiversity and Conservation. https://doi.org/10.1007/s10531-023-02760-2

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.

Weiss, R. M., F. Zanetti, B. Alberghini, D. Puttick, M. A. Vankosky, A. Monti, and C. Eynck. 2024. Bioclimatic analysis of potential worldwide production of spring‐type camelina [Camelina sativa (L.) Crantz] seeded in the spring. GCB Bioenergy 16. https://doi.org/10.1111/gcbb.13126

Camelina [Camelina sativa (L.) Crantz] is a Brassicaceae oilseed that is gaining interest worldwide as low‐maintenance crop for diverse biobased applications. One of the most important factors determining its productivity is climate. We conducted a bioclimate analysis in order to analyze the relationship between climatic factors and the productivity of spring‐type camelina seeded in the spring, and to identify regions of the world with potential for camelina in this scenario. Using the modelling tool CLIMEX, a bioclimatic model was developed for spring‐seeded spring‐type camelina to match distribution, reported seed yields and phenology records in North America. Distribution, yield, and phenology data from outside of North America were used as independent datasets for model validation and demonstrated that model projections agreed with published distribution records, reported spring‐seeded camelina yields, and closely predicted crop phenology in Europe, South America, and Asia. Sensitivity analysis, used to quantify the response of camelina to changes in precipitation and temperature, indicated that crop performance was more sensitive to moisture than temperature index parameters, suggesting that the yield potential of spring‐seeded camelina may be more strongly impacted by water‐limited conditions than by high temperatures. Incremental climate scenarios also revealed that spring‐seeded camelina production will exhibit yield shifts at the continental scale as temperature and precipitation deviate from current conditions. Yield data were compared with indices of climatic suitability to provide estimates of potential worldwide camelina productivity. This information was used to identify new areas where spring‐seeded camelina could be grown and areas that may permit expanded production, including eastern Europe, China, eastern Russia, Australia and New Zealand. Our model is the first to have taken a systematic approach to determine suitable regions for potential worldwide production of spring‐seeded camelina.

Örücü, Ö. K., E. S. Arslan, E. Hoşgör, I. Kaymaz, and S. Gülcü. 2023. Potential distribution pattern of the Quercus brantii Lindl. and Quercus frainetto Ten. under the future climate conditions. European Journal of Forest Research. https://doi.org/10.1007/s10342-023-01636-y

This research aims to predict the potential distribution patterns of Brant's oak ( Quercus brantii Lindl.) and Hungarian oak ( Quercus frainetto Ten.) using three different climate models: HadGEM3-GC31-LL, MPI-ESM1-2-HR, and INM-CM5-0, all with a spatial resolution of 30 s (1 km 2 ). These models were developed for CMIP 6 and utilize scenarios of SSP2-4.5 and SSP5-8.5 for various time periods spanning from 2041 to 2100. To compare the current potential distribution area with those of the periods for different climate models, a change analysis was conducted. The study area covers distribution areas extending from the coastline of Portugal to the southwest of Iran. When comparing the medium–low and high forcing climate models based on the climate sensitivity, we observed that the distribution patterns of both species vary depending on the scenario and time period. Compared to the current distribution, suitable areas of Quercus brantii Lindl. expected to decrease as 84% (109,854 km 2 ) for HadGEM3-GC31-LL climate model and SSP5-8.5 scenario 2081–2100 time period. On the other hand, suitable areas of Quercus frainetto Ten. expected to increase as 59% (618,848 km 2 ) for INM-CM5-0 climate model and SSP5-8.5 during the time period 2081–2100. When it comes to change analysis result, HadGEM3-GC31-LL climate model and SSP5-8.5 scenario project the most significant alterations in the distribution areas of Quercus frainetto Ten. and Quercus brantii Lindl. during the time period 2081–2100, resulting in a loss of 763,046 km 2 and 220,759 km 2 , respectively. The results of the change analysis indicate that the areas marked as loss and gain for both species exhibit differences between the climate change scenarios and time periods. The findings of this research highlight that climate models offer a technological approach to adaptive forest management, enabling the development of strategies to mitigate issues related to climate change.

Zhang, H., W. Guo, and W. Wang. 2023. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecology and Evolution 13. https://doi.org/10.1002/ece3.10747

How to effectively obtain species‐related low‐dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high‐dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

Metreveli, V., H. Kreft, I. Akobia, Z. Janiashvili, Z. Nonashvili, L. Dzadzamia, Z. Javakhishvili, and A. Gavashelishvili. 2023. Potential Distribution and Suitable Habitat for Chestnut (Castanea sativa). Forests 14: 2076. https://doi.org/10.3390/f14102076

Chestnut, Castanea sativa Miller (Fagales: Fagaceae), is an ecologically and economically important tree species of the forest ecosystem in Southern Europe, North-Western Europe, Western Asia, North Africa, and the Caucasus. The distributional range of chestnut in Europe has been highly modified by humans since ancient times. Biotic and abiotic factors have dramatically changed its distribution. Historic anthropogenic range expansion makes it difficult to identify habitat requirements for natural stands of chestnut. In the Caucasus, natural stands of chestnut survived in glacial forest refugia and landscapes that have been difficult for humans to colonize. To identify the species reliable habitat requirements, we estimated the relationship between climatic variables and 620 occurrence locations of natural chestnut stands from the Caucasus and validated the model using GBIF data from outside the Caucasus. We found that our best model is reasonably accurate and the data from the Caucasus characterize chestnut stands throughout the species range well.

Nikkel, E., D. R. Clements, D. Anderson, and J. L. Williams. 2023. Regional habitat suitability for aquatic and terrestrial invasive plant species may expand or contract with climate change. Biological Invasions. https://doi.org/10.1007/s10530-023-03139-8

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.

Hill, A., M. F. T. Jiménez, N. Chazot, C. Cássia‐Silva, S. Faurby, L. Herrera‐Alsina, and C. D. Bacon. 2023. Apparent effect of range size and fruit colour on palm diversification may be spurious. Journal of Biogeography. https://doi.org/10.1111/jbi.14683

Aim Fruit selection by animal dispersers with different mobility directly impacts plant geographical range size, which, in turn, may impact plant diversification. Here, we examine the interaction between fruit colour, range size and diversification rate in palms by testing two hypotheses: (1) species with fruit colours attractive to birds have larger range sizes due to high dispersal ability and (2) disperser mobility affects whether small or large range size has higher diversification, and intermediate range size is expected to lead to the highest diversification rate regardless of disperser. Location Global. Time Period Contemporary (or present). Major Taxa Studied Palms (Arecaceae). Methods Palm species were grouped based on likely animal disperser group for given fruit colours. Range sizes were estimated by constructing alpha convex hull polygons from distribution data. We examined disperser group, range size or an interaction of both as possible drivers of change in diversification rate over time in a likelihood dynamic model (Several Examined State-dependent Speciation and Extinction [SecSSE]). Models were fitted, rate estimates were retrieved and likelihoods were compared to those of appropriate null models. Results Species with fruit colours associated with mammal dispersal had larger ranges than those with colours associated with bird dispersal. The best fitting SecSSE models indicated that the examined traits were not the primary driver of the heterogeneity in diversification rates in the model. Extinction rate complexity had a marked impact on model performance and on diversification rates. Main Conclusions Two traits related to dispersal mobility, range size and fruit colour, were not identified as the main drivers of diversification in palms. Increased model extinction rate complexity led to better performing models, which indicates that net diversification should be estimated rather than speciation alone. However, increased complexity may lead to incorrect SecSSE model conclusions without careful consideration. Finally, we find palms with more mobile dispersers do not have larger range sizes, meaning other factors are more important determinants of range size.