Henry Nicholas Bolander

Nowadays, eucheumatoids lead the rankings in globally cultivated seaweed production, including the seaweeds Kappaphycus alvarezii and Kappaphycus striatus. Eucheumatoids have declined in biomass over recent years, and climate change is regarded as one of the important factors. Thus, it is urgent to investigate the range dynamics of Kappaphycus under climate change. Considering its high practical relevance for conserving biodiversity, the niche conservatism hypothesis was tested between the two species through ecological niche modeling (ENM), ordination, and hypervolume approach which quantify the extent of niche overlap. In this study, we sifted the best-performing algorithm - Maxent and tuned parameters for fitting the distribution of both Kappaphycus species, compared their geographical distribution patterns, and predicted their range dynamics under climate change. All three methodological approaches indicated significant niche differences in both geographical and environmental space between the two Kappaphycus species. Our models predicted that range shifts mainly induced by rising sea surface temperature are likely to differ between two Kappaphycus species, with K. striatus suffering much range contraction (359,448 km2 in 2100s RCP8.5). By the year 2100, both Kappaphycus species are forecast to lose suitable habitats along most of the coastline of Southeast Asia under the RCP8.5 scenario. K. alvarezii is predicted to expand its distributions (96,429 km2) under the RCP2.6 scenario by the year 2100, suggesting resilience to mild global warming. Our study enhances the understanding of Kappaphycus aquaculture, and is conducive to the sustainable development of tropical seaweed by stressing the importance of conservation and investigation under climate change.

The tribe Astereae (Asteraceae) displays an American Amphitropical Disjunction. To understand the eco-evolutionary dynamics associated with a long-distance dispersal event and subsequent colonization of extratropical South America, we compared the climatic and geographic distributions of South American species with their closest North American relatives, focusing on the diverse South American Astereae genus, Haplopappus. Phylogenetic analysis revealed that two South American genera are closely related to seven North American genera. The climatic niche overlap (D = 0.5) between South and North America exhibits high stability (0.89), low expansion (0.12), and very low unfilling (0.04). The distribution of the North American species predicted the climatic and geographic space occupied by the South American species. In central Chile, Haplopappus showed a non-random latitudinal gradient in species richness, with Mediterranean climate variables mainly explaining the variation. Altitudinal patterns indicated peak richness at 600 m, declining at lower and higher elevations. These findings support climatic niche conservatism in shaping Haplopappus species distribution and diversity. Two major endemism zones were identified in central Chile and the southern region, with a transitional zone between Mediterranean and Temperate macro-bioclimates. Our results indicate strong niche conservatism following long-distance dispersal and slight niche expansion due to unique climatic variables in each hemisphere.

Evolutionary correlations between chemical defense and protection by mutualist bodyguards have been long predicted, but tests of these pattern remain rare. We use a phylogenetic framework to test for evolutionary correlations indicative of trade-offs or synergisms between direct defense in the form of plant secondary metabolism, and indirect defense in the form of leaf domatia, across 33 species in the wild grape genus, Vitis. We also performed a bioassay with a generalist herbivore to associate our chemical phenotypes with herbivore palatability. Finally, we tested whether defensive traits correlate with the average abiotic characteristics of each species’ contemporary range and whether these correlations were consistent with plant defense theory. We found a negative evolutionary correlation between domatia size and the diversity of secondary metabolites in Vitis leaf tissue across the genus, and also that leaves with a higher diversity and richness of secondary metabolites were less palatable to a generalist herbivore, consistent with a trade-off in chemical and mutualistic defense investment. Predictions from plant defense theory were not supported by associations between investment in defense phenotypes and abiotic variables. Our work demonstrates an evolutionary pattern indicative of a trade-off between indirect and direct defense strategies across the Vitis genus.

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.

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.

Complex distribution data can be summarized by grouping species with similar or overlapping distributions to unravel spatial patterns and separate trends (e.g., of habitat loss) among spatially unique groups. However, such classifications are often heuristic, lacking the transparency, objectivity, and data‐driven rigor of quantitative methods, which limits their interpretability and utility. Here, we develop and illustrate the clustering of spatially associated species, a methodological framework aimed at statistically classifying species using explicit measures of interspecific spatial association. We investigate several association indices and clustering algorithms and show how these methodological choices drive substantial variations in clustering outcomes and performance. To facilitate robust decision‐making, we provide guidance on choosing methods appropriate to one's study objective(s). As a case study, we apply our framework to modeled tree distributions in Borneo and subsequently evaluate the impact of land‐cover change on separate species groupings. Based on the modeled distribution of 390 tree species prior to anthropogenic land‐cover changes, we identified 11 distinct clusters that unraveled ecologically meaningful patterns in Bornean tree distributions. These clusters then enabled us to quantify trends of habitat loss tied to each of those specific clusters, allowing us to discern particularly vulnerable species clusters and their distributions. This study demonstrates the advantages of adopting quantitatively derived clusters of spatially associated species and elucidates the potential of resultant clusters as a spatially explicit framework for investigating distribution‐related questions in ecology, biogeography, and conservation. By adopting our methodological framework and publicly available codes, practitioners can leverage the ever‐growing abundance of distribution data to better understand complex spatial patterns among species distributions and the disparate effects of global changes on biodiversity.

Background Poa annua (annual bluegrass) is an allotetraploid turfgrass, an agronomically significant weed, and one of the most widely dispersed plant species on earth. Here, we report the chromosome-scale genome assemblies of P. annua’s diploid progenitors, P. infirma and P. supina, and use multi-omic analyses spanning all three species to better understand P. annua’s evolutionary novelty. Results We find that the diploids diverged from their common ancestor 5.5 – 6.3 million years ago and hybridized to form P. annua  ≤ 50,000 years ago. The diploid genomes are similar in chromosome structure and most notably distinguished by the divergent evolutionary histories of their transposable elements, leading to a 1.7 × difference in genome size. In allotetraploid P. annua, we find biased movement of retrotransposons from the larger (A) subgenome to the smaller (B) subgenome. We show that P. annua’s B subgenome is preferentially accumulating genes and that its genes are more highly expressed. Whole-genome resequencing of several additional P. annua accessions revealed large-scale chromosomal rearrangements characterized by extensive TE-downsizing and evidence to support the Genome Balance Hypothesis. Conclusions The divergent evolutions of the diploid progenitors played a central role in conferring onto P. annua its remarkable phenotypic plasticity. We find that plant genes (guided by selection and drift) and transposable elements (mostly guided by host immunity) each respond to polyploidy in unique ways and that P. annua uses whole-genome duplication to purge highly parasitized heterochromatic sequences. The findings and genomic resources presented here will enable the development of homoeolog-specific markers for accelerated weed science and turfgrass breeding .

Low temperature constitutes one of the main barriers to plant distributions, confining many clades to their ancestrally tropical biome. However, recent evidence suggests that transitions from tropical to temperate biomes may be more frequent than previously thought. Here, we study the evolution of cold and frost tolerance in the globally distributed and highly stress-tolerant Salicornieae (Salicornioideae, Amaranthaceae s.l.). We first generate a phylogenetic tree comprising almost all known species (85-90%), using newly generated (n = 106) and published nuclear-ribosomal and plastid sequences. Next, we use geographical occurrence data to document in which clades and geographical regions cold-tolerant species occur and reconstruct how cold tolerance evolved. Finally, we test for correlated evolution between frost tolerance and the annual life form. We find that frost tolerance has evolved independently in up to four Northern Hemisphere lineages but that annuals are no more likely to evolve frost tolerance than perennials, indicating the presence of different strategies for adapting to cold environments. Our findings add to mounting evidence for multiple independent out-of-the-tropics transitions among close relatives of flowering plants and raise new questions about the ecological and physiological mechanism(s) of adaptation to low temperatures in Salicornieae.

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.

Rising temperatures and changes in precipitation patterns under climate change scenarios are accelerating the depletion of soil moisture and increasing the risk of drought, disrupting the conditions that many plant species need to survive. This study aims to establish the bioclimatic characterisation, both qualitative and quantitative, of ten native Californian Pinales for the period 1980–2019, and to determine their habitat suitability by 2050. To achieve this, an exhaustive search of the Gbif database for records of ten conifer taxa was carried out. To conduct the bioclimatic characterisation of the studied taxa, we worked with the monthly values of average temperature and precipitation for the period 1980–2019 from 177 meteorological stations. Linear regressions was performed in order to compile the future evolution of California’s climate. Suitable areas and optimal areas were defined at the present time (1980–2019) and its future projection (2050). We applied Boolean logic and, in this investigation, the Conditional Logic Operator (CON) was used to determine the possible species presence (one) or absence (zero) for each of the 15 variables analysed. In general, most of the conifers studied here will experience a reduction in their habitat range in California by the year 2050 due to climate change, as well as the displacement of species towards optimal areas. Furthermore, the results have highlighted the applicability of bioclimatology to future conditions under climate change. This will aid conservation managers in implementing strategic measures to ameliorate the detrimental impacts of climate change, thereby ensuring the ecological integrity and sustainability of the affected conifer species.