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Zhao, Y., G. A. O’Neill, N. C. Coops, and T. Wang. 2024. Predicting the site productivity of forest tree species using climate niche models. Forest Ecology and Management 562: 121936. https://doi.org/10.1016/j.foreco.2024.121936

Species occurrence-based climate niche models (CNMs) serve as valuable tools for predicting the future ranges of species’ suitable habitats, aiding the development of climate change adaptation strategies. However, these models do not address an essential aspect - productivity, which holds economic significance for timber production and ecological importance for carbon sequestration and ecosystem services. In this study, we investigated the potential to extend the CNMs to predict species productivity under various climate conditions. Lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.) were selected as our model species due to their comprehensive range-wide occurrence data and measurement of site productivity. To achieve this, we compared and optimized the performance of four individual modeling algorithms (Random Forest (RF), Maxent, Generalized Boosted Models (GBM), and Generalized Additive Model (GAM)) in reflecting site productivity by evaluating the effect of spatial filtering, and the ratio of presence to absence (p/a ratio) observations. Additionally, we applied a binning process to capture the overarching trend of climatic effects while minimizing the impact of other factors. We observed consistency in optimal performance across both species when using the unfiltered data and a 1:1.5 p/a ratio, which could potentially be extended to other species. Among the modeling algorithms explored, we selected the ensemble model combining RF and Maxent as the final model to predict the range-wide site productivity for both species. The predicted range-wide site productivity was validated with an independent dataset for each species and yielded promising results (R2 above 0.7), affirming our model’s credibility. Our model introduced an innovative approach for predicting species productivity with high accuracy using only species occurrence data, and significantly advanced the application of CNMs. It provided crucial tools and insights for evaluating climate change's impact on productivity and holds a better potential for informed forest management and conservation decisions.

Zachos, L. G., and A. Ziegler. 2024. Selective concentration of iron, titanium, and zirconium substrate minerals within Gregory’s diverticulum, an organ unique to derived sand dollars (Echinoidea: Scutelliformes). PeerJ 12: e17178. https://doi.org/10.7717/peerj.17178

Gregory’s diverticulum, a digestive tract structure unique to a derived group of sand dollars (Echinoidea: Scutelliformes), is filled with sand grains obtained from the substrate the animals inhabit. The simple methods of shining a bright light through a specimen or testing response to a magnet can reveal the presence of a mineral-filled diverticulum. Heavy minerals with a specific gravity of >2.9 g/cm3 are selectively concentrated inside the organ, usually at concentrations one order of magnitude, or more, greater than found in the substrate. Analyses of diverticulum content for thirteen species from nine genera, using optical mineralogy, powder X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, as well as micro-computed tomography shows the preference for selection of five major heavy minerals: magnetite (Fe3O4), hematite (Fe2O3), ilmenite (FeTiO3), rutile (TiO2), and zircon (ZrSiO4). Minor amounts of heavy or marginally heavy amphibole, pyroxene and garnet mineral grains may also be incorporated. In general, the animals exhibit a preference for mineral grains with a specific gravity of >4.0 g/cm3, although the choice is opportunistic and the actual mix of mineral species depends on the mineral composition of the substrate. The animals also select for grain size, with mineral grains generally in the range of 50 to 150 μm, and do not appear to alter this preference during ontogeny. A comparison of analytical methods demonstrates that X-ray attenuation measured using micro-computed tomography is a reliable non-destructive method for heavy mineral quantification when supported by associated analyses of mineral grains extracted destructively from specimens or from substrate collected together with the specimens. Commonalities in the electro-chemical surface properties of the ingested minerals suggest that such characteristics play an important role in the selection process.

White, S. V., and A. M. Royer. 2024. Floral colour variation across life history and geography in Mimulus ringens (Phrymaceae). Botanical Journal of the Linnean Society. https://doi.org/10.1093/botlinnean/boad065

Floral and life history traits play important roles in plant speciation. The genus Mimulus is a model system for studying speciation. It includes examples of species in which floral colour facilitates isolation through pollinator shifts, as well as life history changes that result in temporal or ecogeographic isolation. We investigate the possibility that both floral colour and life history have shifted together in a recently described, genetically distinct group within the species Mimulus ringens. Using a large, range-wide citizen science dataset, we test for geographic trends in flower colour and flowering time. We combine this with greenhouse studies in populations of known life history to test for differences in flower colour with life history. We show that darker-flowered plants are more common at higher latitudes, that annual-like populations have darker flowers, and that flowering time varies with latitude only in the subset of populations that have lighter flowers. This suggests that annual-like populations (with the earlier flowering time typical of this life history) are restricted to the northern part of the species range and may have distinct trends in flowering date.

Gillespie, L. J., P. C. Sokoloff, G. A. Levin, J. Doubt, and R. T. McMullin. 2024. Vascular plant, bryophyte, and lichen biodiversity of Agguttinni Territorial Park, Baffin Island, Nunavut, Canada: an annotated species checklist of a new Arctic protected area. Check List 20: 279–443. https://doi.org/10.15560/20.2.279

Agguttinni Territorial Park is a large, newly established park on the east-central coast of Baffin Island in Nunavut, Canada. Previous knowledge of the plant and lichen biodiversity was limited and based mostly on collections made during the 1950 Baffin Island Expedition. We conducted a floristic inventory of the park in 2021 and re-examined previous collections. We recorded 141 species of vascular plants belonging to 25 families, 69 species of bryophytes in 27 families, and 93 species of lichens in 23 families. Most of the vascular plant and bryophyte species are new records for the park area, and some vascular plants, bryophytes, and lichens are newly reported for Baffin Island, Nunavut, or the Canadian Arctic or represent significant range extensions. Vascular plant species diversity varied greatly among localities, with inland valleys at the heads of fiords showing highest diversity and interior rocky barrens showing the lowest.

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.

Xiao, S., S. Li, J. Huang, X. Wang, M. Wu, R. Karim, W. Deng, and T. Su. 2024. Influence of climate factors on the global dynamic distribution of Tsuga (Pinaceae). Ecological Indicators 158: 111533. https://doi.org/10.1016/j.ecolind.2023.111533

Throughout the Quaternary period, climate change has significantly influenced plant distribution, particularly affecting species within the genus Tsuga (Endl.) Carrière. This climatic impact ultimately led to the extinction of all Tsuga species in Europe. Today, there are ten recognized species of Tsuga worldwide, one of listed as a vulnerable species and four as near-threatened species. The genus Tsuga exhibits a disjunctive distribution in East Asia (EA), eastern North America (ENA), and western North America (WNA). It is crucial to comprehend the mechanisms underlying these distributional changes and to identify key climate variables to develop effective conservation strategies for Tsuga under future climate scenarios. In this study, we applied the maximum entropy (MaxEnt) model by combining distribution data for Tsuga with abundant pollen fossil data. Our objective was to investigate the climate factors that shape the distribution of Tsuga, identify climate thresholds, and elucidate distribution dynamics in the context of significant climate changes over the past 1070 thousand years (ka). Our findings highlight the pivotal role of precipitation as the key climate factor affecting the distribution of Tsuga. Specifically, in EA, summer precipitation was the key driver, while in North America (NA), winter precipitation exerted greater importance. Moreover, we observed similarities in climatic requirements between Tsuga species in Europe and EA, and declines in summer precipitation and winter temperature were major factors contributing to the extinction of Tsuga species in Europe. Quaternary glacial and interglacial fluctuations exerted substantial impacts on Tsuga distribution dynamics. The disappearance of Tsuga species in the Korean Peninsula may have occurred during the LGM (Last Glacial Maximum). The potential suitable area for Tsuga species in EA expanded during the cold periods, while in NA, it contracted. In the future, climate change may result Tsuga distribution area contraction in both the EA and NA. Our study has identified distinct response patterns of Tsuga in various geographic regions to Quaternary climate change and offers corresponding suggestions for Tsuga conservation. In the future, it will be imperative to prioritize the conservation of natural Tsuga distributions in EA and NA, with a focus on the impacts of precipitation fluctuation on the dynamic distribution of this genus.

Putra, A. R., K. A. Hodgins, and A. Fournier‐Level. 2023. Assessing the invasive potential of different source populations of ragweed (Ambrosia artemisiifolia L.) through genomically informed species distribution modelling. Evolutionary Applications. https://doi.org/10.1111/eva.13632

The genetic composition of founding populations is likely to play a key role in determining invasion success. Individual genotypes may differ in habitat preference and environmental tolerance, so their ability to colonize novel environments can be highly variable. Despite the importance of genetic variation on invasion success, its influence on the potential distribution of invaders is rarely investigated. Here, we integrate population genomics and ecological niche models (ENMs) into a single framework to predict the distribution of globally invasive common ragweed (Ambrosia artemisiifolia) in Australia. We identified three genetic clusters for ragweed and used these to construct cluster‐specific ENMs and characterize within‐species niche differentiation. The potential range of ragweed in Australia depended on the genetic composition and continent of origin of the introduced population. Invaders originating from warmer, wetter climates had a broader potential distribution than those from cooler, drier ones. By quantifying this change, we identified source populations most likely to expand the ragweed distribution. As prevention remains the most effective method of invasive species management, our work provides a valuable way of ranking the threat posed by different populations to better inform management decisions.

Silva-Valderrama, I., J.-R. Úrbez-Torres, and T. J. Davies. 2024. From host to host: The taxonomic and geographic expansion of Botryosphaeriaceae. Fungal Biology Reviews 48: 100352. https://doi.org/10.1016/j.fbr.2023.100352

Fungal pathogens are responsible for 30% of emerging infectious diseases (EIDs) in plants. The risk of a pathogen emerging on a new host is strongly tied to its host breadth; however, the determinants of host range are still poorly understood. Here, we explore the factors that shape host breadth of plant pathogens within Botryosphaeriaceae, a fungal family associated with several devastating diseases in economically important crops. While most host plants are associated with just one or a few fungal species, some hosts appear to be susceptible to infection by multiple fungi. However, the variation in the number of fungal taxa recorded across hosts is not easily explained by heritable plant traits. Nevertheless, we reveal strong evolutionary conservatism in host breadth, with most fungi infecting closely related host plants, but with some notable exceptions that seem to have escaped phylogenetic constraints on host range. Recent anthropogenic movement of plants, including widespread planting of crops, has provided new opportunities for pathogen spillover. We suggest that constraints to pathogen distributions will likely be further disrupted by climate change, and we may see future emergence events in regions where hosts are present but current climate is unfavorable.

Schertler, A., B. Lenzner, S. Dullinger, D. Moser, J. L. Bufford, L. Ghelardini, A. Santini, et al. 2023. Biogeography and global flows of 100 major alien fungal and fungus‐like oomycete pathogens. Journal of Biogeography. https://doi.org/10.1111/jbi.14755

AbstractAimSpreading infectious diseases associated with introduced pathogens can have devastating effects on native biota and human livelihoods. We analyse the global distribution of 100 major alien fungal and oomycete pathogens with substantial socio‐economic and environmental impacts and examine their taxonomy, ecological characteristics, temporal accumulation trajectories, regional hot‐ and coldspots of taxon richness and taxon flows between continents.LocationGlobal.TaxonAlien/cryptogenic fungi and fungus‐like oomycetes, pathogenic to plants or animals.MethodsTo identify over/underrepresented classes and phyla, we performed Chi2 tests of independence. To describe spatial patterns, we calculated the region‐wise richness and identified hot‐ and coldspots, defined as residuals after correcting taxon richness for region area and sampling effort via a quasi‐Poisson regression. We examined the relationship with environmental and socio‐economic drivers with a multiple linear regression and evaluated a potential island effect. Regional first records were pooled over 20‐year periods, and for global flows the links between the native range to the alien regions were mapped.ResultsPeronosporomycetes (Oomycota) were overrepresented among taxa and regional taxon richness was positively correlated with area and sampling effort. While no island effect was found, likely due to host limitations, hotspots were correlated with human modification of terrestrial land, per capita gross domestic product, temperate and tropical forest biomes, and orobiomes. Regional first records have increased steeply in recent decades. While Europe and Northern America were major recipients, about half of the taxa originate from Asia.Main ConclusionsWe highlight the putative importance of anthropogenic drivers, such as land use providing a conducive environment, contact opportunities and susceptible hosts, as well as economic wealth likely increasing colonisation pressure. While most taxa were associated with socio‐economic impacts, possibly partly due to a bias in research focus, about a third show substantial impacts to both socio‐economy and the environment, underscoring the importance of maintaining a wholescale perspective across natural and managed systems.

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.