Ciencia habilitada por datos de especímenes

Lima, V. P., R. A. Ferreira de Lima, F. Joner, L. D’Orangeville, N. Raes, I. Siddique, and H. ter Steege. 2023. Integrating climate change into agroforestry conservation: A case study on native plant species in the Brazilian Atlantic Forest. Journal of Applied Ecology.

Designing multispecies systems with suitable climatic affinity and identifying species' vulnerability under human‐driven climate change are current challenges to achieve successful adaptation of natural systems. To address this problem, we need to (1) identify groups of species with climatic similarity under climate scenarios and (2) identify areas with high conservation value under predicted climate change.To recognize species with similar climatic niche requirements that can be grouped for mixed cropping in Brazil, we employed ecological niche models (ENMs) and Spearman's ρ for overlap. We also used prioritization algorithms to map areas of high conservation value using two Shared Socioeconomic Pathways (SSP2‐4.5 and SSP5‐8.5) to assess mid‐term (2041–2060) and long‐term (2061–2080) climate change impacts.We identified 15 species groups with finer climatic affinities at different times depicted on hierarchical clustering dendrograms, which can be combined into agroecological agroforestry systems. Furthermore, we highlight the climatically suitable areas for these groups of species, thus providing an outlook of where different species will need to be planted over time to be conserved. In addition, we observed that climate change is predicted to modify the spatial association of these groups under different future climate scenarios, causing a mean negative change in species climatic similarity of 9.5% to 13.7% under SSP2‐4.5 scenario and 9.5% to 10.5% under SSP5‐8.5, for 2041–2060 and 2061–2080, respectively.Synthesis and applications. Our findings provide a framework for agroforestry conservation. The groups of species with finer climatic affinities identified and the climatically suitable areas can be combined into agroecological productive systems, and provide an outlook of where different species may be planted over time. In addition, the conservation priority zones displaying high climate stability for each species individually and all at once can be incorporated into Brazil's conservation plans by policymakers to prioritize specific sites. Lastly, we urge policymakers, conservation organizations and donors to promote interventions involving farmers and local communities, since the species' evaluated have proven to maintain landscapes with productive forest fragments and can be conserved in different Brazilian ecosystems.

Richard-Bollans, A., C. Aitken, A. Antonelli, C. Bitencourt, D. Goyder, E. Lucas, I. Ondo, et al. 2023. Machine learning enhances prediction of plants as potential sources of antimalarials. Frontiers in Plant Science 14.

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families – Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) – and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms – Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks – and compare these to two ethnobotanical selection approaches – based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best – attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

Clemente, K. J. E., and M. S. Thomsen. 2023. High temperature frequently increases facilitation between aquatic foundation species: a global meta‐analysis of interaction experiments between angiosperms, seaweeds, and bivalves. Journal of Ecology.

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.

Huang, T., J. Chen, K. E. Hummer, L. A. Alice, W. Wang, Y. He, S. Yu, et al. 2023. Phylogeny of Rubus (Rosaceae): Integrating molecular and morphological evidence into an infrageneric revision. TAXON.

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.

Vicente, S., H. Trindade, C. Máguas, and J. J. Le Roux. 2023. Genetic analyses reveal a complex introduction history of the globally invasive tree Acacia longifolia. NeoBiota 82: 89–117.

AbstractAcacialongifolia (Sydney golden wattle) is considered one of the most problematic plant invaders in Mediterranean-type ecosystems. In this study, we investigate the species’ invasion history by comparing the genetic diversity and structure of native (Australia) and several invasive range (Brazil, Portugal, South Africa, Spain, and Uruguay) populations and by modelling different introduction scenarios using these data. We sampled 272 A.longifolia individuals – 126 from different invasive ranges and 146 from the native range – from 41 populations. We genotyped all individuals at four chloroplast and 12 nuclear microsatellite markers. From these data we calculated diversity metrics, identified chloroplast haplotypes, and estimated population genetic structure based on Bayesian assignment tests. We used Approximate Bayesian Computation (ABC) models to infer the likely introduction history into each invaded country. In Australia, population genetic structure of A.longifolia appears to be strongly shaped by the Bass Strait and we identified two genetic clusters largely corresponding to mainland Australian and Tasmanian populations. We found invasive populations to represent a mixture of these clusters. Similar levels of genetic diversity were present in native and invasive ranges, indicating that invasive populations did not go through a genetic bottleneck. Bayesian assignment tests and chloroplast haplotype frequencies further suggested a secondary introduction event between South Africa and Portugal. However, ABC analyses could not confidently identify the native source(s) of invasive populations in these two countries, probably due to the known high propagule pressure that accompanied these introductions. ABC analyses identified Tasmania as the likely source of invasive populations in Brazil and Uruguay. A definitive native source for Spanish populations could also not be identified. This study shows that tracing the introduction history of A.longifolia is difficult, most likely because of the complexity associated with the extensive movement of the species around the world. Our findings should be considered when planning management and control efforts, such as biological control, in some invaded regions.

Reichgelt, T., A. Baumgartner, R. Feng, and D. A. Willard. 2023. Poleward amplification, seasonal rainfall and forest heterogeneity in the Miocene of the eastern USA. Global and Planetary Change 222: 104073.

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.

Marcussen, T., H. E. Ballard, J. Danihelka, A. R. Flores, M. V. Nicola, and J. M. Watson. 2022. A Revised Phylogenetic Classification for Viola (Violaceae). Plants 11: 2224.

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.

Reichgelt, T., D. R. Greenwood, S. Steinig, J. G. Conran, D. K. Hutchinson, D. J. Lunt, L. J. Scriven, and J. Zhu. 2022. Plant Proxy Evidence for High Rainfall and Productivity in the Eocene of Australia. Paleoceanography and Paleoclimatology 37.

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.

Tazikeh, S., S. Zendehboudi, S. Ghafoori, A. Lohi, and N. Mahinpey. 2022. Algal bioenergy production and utilization: Technologies, challenges, and prospects. Journal of Environmental Chemical Engineering 10: 107863.

Increasing demand for energy and also escalating environmental pollution show that industries cannot rely on fossil fuels, and it is necessary to adopt an alternative. In recent decades, algal bioenergy has emerged as a renewable energy source in different industries. However, algal bioenergy production is costly and faces different challenges and unknown aspects that need to be addressed. Experimental and theoretical research works have revealed that the efficiency of algal bioenergy production is influenced by several factors, including algae species, temperature, light, CO2, cultivation method, and available nutrients. Algal bioenergy production on commercial scales in cost-effective ways is the main aim of industries to compete with fossil fuels. Hence, it is vital to have a comprehensive knowledge of the previous findings and attain a suitable pathway for future studies/activities. In the present review paper, the potential of microalgae bioenergy production, influential parameters, previous experimental and theoretical studies, and different methods for microalgae biofuel production from cultivation stage to utilization are reviewed. Moreover, this work discusses the engineering activities and economic analysis of microalgae cultivation to utilization, and also useful suggestions are made for future research works. The outcomes of the present work confirm that innovative engineering methods can overcome scale-up challenging, increase the rate of production, and decrease the cost of algae bioenergy production. Hence, there is no long way to produce cost-effective algae bioenergy on commercial scales.

Chevalier, M. 2022. <i>crestr</i>: an R package to perform probabilistic climate reconstructions from palaeoecological datasets. Climate of the Past 18: 821–844.

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.