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The study of rare events in molecular and atomic systems such as conformal changes and cluster rearrangements has been one of the most important research themes in chemical physics. Key challenges are associated with long waiting times rendering molecular simulations inefficient, high dimensionality impeding the use of PDE-based approaches, and the complexity or breadth of transition processes limiting the predictive power of asymptotic methods. Diffusion maps are promising algorithms to avoid or mitigate all these issues. We adapt the diffusion map with Mahalanobis kernel proposed by Singer and Coifman (2008) for the SDE describing molecular dynamics in collective variables in which the diffusion matrix is position-dependent and, unlike the case considered by Singer and Coifman, is not associated with a diffeomorphism. We offer an elementary proof showing that one can approximate the generator for this SDE discretized to a point cloud via the Mahalanobis diffusion map. We use it to calculate the committor functions in collective variables for two benchmark systems: alanine dipeptide, and Lennard-Jones-7 in 2D. For validating our committor results, we compare our committor functions to the finite-difference solution or by conducting a "committor analysis" as used by molecular dynamics practitioners. We contrast the outputs of the Mahalanobis diffusion map with those of the standard diffusion map with isotropic kernel and show that the former gives significantly more accurate estimates for the committors than the latter., Comment: Restructured introduction, additional Theorem 3.1 and Appendix A, B

To understand the geographic distribution of and area-level factors associated with malignant mesothelioma incidence and survival in Australia.Generalised linear models and Bayesian spatial models were fitted using population registry data. Area-level covariates were socioeconomic quintile, remoteness category and state or territory. The maximised excess events test was used to test for spatial heterogeneity.There was strong evidence of spatial differences in standardised incidence rates for malignant mesothelioma but survival was uniformly poor. Incidence rates varied by state or territory and were lower in remote areas. Patterns in the geographic distribution of modelled incidence counts for malignant mesothelioma differed substantially from patterns of standardised incidence rates.Geographic variation in the modelled incidence counts of malignant mesothelioma demonstrates varying demand for diagnostic and management services. The long latency period for this cancer coupled with migration complicates any associations with patterns of exposure, however some of the geographic distribution of diagnoses can be explained by the location of historical mines and asbestos-related industries.

Plant functional traits can greatly influence invasion success on islands. However, interrelationships between traits and invasion success are rarely integrated with the island biogeography theory. Here, we explored relations between functional traits and plant distributions to assess which traits are associated with invasion success (i.e. high island occupancy), test whether non-native richness and seed mass of species with distinct growth forms and dispersal modes vary differently with island characteristics (e.g. area, isolation, exposure to ocean-borne disturbances, distance from the nearest urban area, and whether islands were managed for conservation), and whether results differ from native species. We assembled a database of 264 northern New Zealand offshore islands, amalgamating species lists from field surveys and previously published data, and comprising 822 native and 855 non-native species. Non-native graminoids occurred on islands more frequently than forbs and woody species, and long-distance dispersal modes (wind, animal, unspecialized) more than species with short-distance dispersal modes. Most differences among trait categories of non-native species were associated with human-related variables (i.e. distance from the nearest urban area, and whether islands were conservation areas). Non-native plant species with high island occupancy were less commonly associated with human-related variables than non-native species with low island occupancy. Instead, they were more similar in their distributional patterns to native species within the same trait category, suggesting comparable processes regulate both sets of species. Our results illustrate that integrating trait-based approaches in the island biogeography framework can be a useful tool in understanding and predicting plant invasions.

Spatial modelling of cancer survival is an important tool for identifying geographic disparities and providing an evidence base for resource allocation. Many different approaches have attempted to understand how survival varies geographically. This is the first scoping review to describe different methods and visualization techniques and to assess temporal trends in publications. The review was carried out using the PRISMA guideline using PubMed and Web of Science databases. Two authors independently screened articles. Articles were eligible for review if they measured cancer survival outcomes in small geographical areas by using spatial regression and/or mapping. Thirty-two articles were included, and the number increased over time. Most articles have been conducted in high-income countries using cancer registry databases. Eight different methods of modelling spatial survival were identified, and there were seven different ways of visualizing the results. Increasing the use of spatial modelling through enhanced data availability and knowledge sharing could help inform and motivate efforts to improve cancer outcomes and reduce excess deaths due to geographical inequalities. Efforts to improve the coverage and completeness of population-based cancer registries should continue to be a priority, in addition to encouraging the open sharing of relevant statistical programming syntax and international collaborations.

A polymer network fractures by breaking covalent bonds, but the experimentally measured strength of the polymer network is orders of magnitude lower than the strength of covalent bonds. We investigate the effect of statistical variation of the number of links in polymer chains on strength using a parallel chain model. Each polymer chain is represented by a freely-jointed chain, with a characteristic J-shaped force-extension curve. The chain carries entropic forces for most of the extension and carries covalent forces only for a narrow range of extension. The entropic forces are orders of magnitude lower than the covalent forces. Chains with a statistical distribution of the number of links per chain are pulled between two rigid parallel plates. Chains with fewer links attain covalent forces and rupture at smaller extensions, while chains with more links still carry entropic forces. We compute the applied force on the rigid plates as a function of extension and define the strength of the parallel chain model by the maximum force divided by the total number of chains. With the J-shaped force-extension curve of each chain, even a small scatter in the number of links per chain greatly reduces the strength of the parallel chain model. We further show that the strength of the parallel chain model relates to the scatter in the number of links per chain according to a power law., 17 pages, 5 figures

In the current paper we present an updated checklist of all the megadrile earthworms (Crassiclitellata: Annelida) in the world, and notes on the distribution of families worldwide. Biogeographic responses to geological phenomena including plate tectonics, as well as to past and present climate and habitat distributions, are the main factors determining the present distribution of earthworm families. A total of ca. 5,738 species/subspecies (5,406 species and 332 unique subspecies; i.e., not counting the nomino-typical subspecies) belonging to 23 families (including one non-crassiclitellate family: Moniligastridae) are currently recognized worldwide, of which three families (Tritogeniidae and Kazimierzidae from Southern Africa and Arecoidae, a new family from Brazil described herein), 35 genera and close to 1200 new taxa (including subspecies) were described in the 21st century. Nonetheless, the large number of still undescribed species will likely increase this value to well over 8,000 species. Ten families are monospecific and/or monogeneric and have a mostly restricted distribution. On the other hand, more than 87 widespread cosmopolitan species have been catalogued, some of them with important invasive potential, belonging mainly to families Lumbricidae, Acanthodrilidae, Benhamiidae, Megascolecidae, Rhinodrilidae and Ocnerodrilidae. Taxonomic housekeeping was performed for the preoccupied Rhinodrilidae genus Tairona Righi – herein substituted by Taironina nom. nov., and Guarani camaqua Rodríguez & Lima was reinstated and removed from synonymy with Criodrilus lacuum Hoffmeister, 1845, resulting in a wider definition of the Almidae family. Furthermore, Amynthas maximalis nom. nov. is proposed herein as a substitution name for the preoccupied name Amynthas maximus Qiu & Dong, 2019, and Arecoidae is proposed herein as a new monotypic family for the aquamegadrile species Areco reco Righi, Ayres & Bittencourt, 1978.

Anthropogenic global changes are impacting biodiversity, however, many previous meta-analyses investigating the impact of different global changes on biodiversity have omitted soil fauna, or are limited in the scope of the global changes studied. Threats to soil biodiversity by global changes need to be understood to mitigate effects on ecosystem services provided by soils. We conducted a meta-analysis using 3,173 effect sizes from 627 publications focused on six global changes (climate change, land-use intensification, pollution, nutrient enrichment, invasive species, and habitat fragmentation) and their associated environmental stressors on soil fauna. We classified stressors as either pulse (short-term, acute) or press (long-term, chronic) stressors, and expected pulse stressors to have less impact on soil biodiversity due to buffering effects of the soil. Unexpectedly, pollution caused the largest loss in soil fauna communities, which is worrying due to continually increasing levels of pollution, as well as the poor mechanistic understanding of pollution impacts. There was no clear pattern of pulse stressors having a smaller impact on soil biodiversity than press stressors. Overall, this work shows the importance of including soil biodiversity in large-scale global change analyses, as soil organisms often do not show the same responses as organisms above-ground.

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/s13225-021-00493-7. Fungi are highly important biotic components of terrestrial ecosystems, but we still have a very limited understanding about their diversity and distribution. This data article releases a global soil fungal dataset of the Global Soil Mycobiome consortium (GSMc) to boost further research in fungal diversity, biogeography and macroecology. The dataset comprises 722,682 fungal operational taxonomic units (OTUs) derived from PacBio sequencing of full-length ITS and 18S-V9 variable regions from 3200 plots in 108 countries on all continents. The plots are supplied with geographical and edaphic metadata. The OTUs are taxonomically and functionally assigned to guilds and other functional groups. The entire dataset has been corrected by excluding chimeras, index-switch artefacts and potential contamination. The dataset is more inclusive in terms of geographical breadth and phylogenetic diversity of fungi than previously published data. The GSMc dataset is available over the PlutoF repository.

Rare cancers collectively account for around a quarter of cancer diagnoses and deaths. However, epidemiological studies are sparse. We describe spatial and geographical patterns in incidence and survival of rare cancers across Australia using a population-based cancer registry cohort of rare cancer cases diagnosed among Australians aged at least 15 years, 2007 to 2016. Rare cancers were defined using site- and histology-based categories from the European RARECARE study, as individual cancer types having crude annual incidence rates of less than 6/100 000. Incidence and survival patterns were modelled with generalised linear and Bayesian spatial Leroux models. Spatial heterogeneity was tested using the maximised excess events test. Rare cancers (n = 268 070) collectively comprised 22% of all invasive cancer diagnoses and accounted for 27% of all cancer-related deaths in Australia, 2007 to 2016 with an overall 5-year relative survival of around 53%. Males and those living in more remote or more disadvantaged areas had higher incidence but lower survival. There was substantial evidence for spatial variation in both incidence and survival for rare cancers between small geographical areas across Australia, with similar patterns so that those areas with higher incidence tended to have lower survival. Rare cancers are a substantial health burden in Australia. Our study has highlighted the need to better understand the higher burden of these cancers in rural and disadvantaged regions where the logistical challenges in their diagnosis, treatment and support are magnified.

Recent work underscores that ants are highly proficient and ubiquitous scavengers. These tendencies extend to numerically and behaviorally dominant introduced ants, which exhibit a suite of traits that allow them to exploit and monopolize carrion to a greater extent than is widely appreciated. We thus contend that an understanding of how introduced ants fit into food webs remains incomplete. Monopolization of carrion resources by introduced ants could increase worker production, enhance the ability of these species to compete with and prey upon other organisms, and alter the strength of direct and indirect interactions within food webs. Future work should consider how ant invasions influence energy transfer within and between green and brown food webs.

The invasion of jumping worms, a small group of pheretimoid earthworm species from Asia, has increasingly become an ecological, environmental and conservation issue in forest ecosystems and urban-suburban landscapes around the world. Their presence is often noticed due to their high abundance, distinctive “jumping” behavior, and prominent granular casts on the soil surface. Although they are known to affect soil carbon dynamics and nutrient availability, no single paper has summarized their profound impacts on soil biodiversity, plant community, and animals of all trophic groups that rely on soil and the leaf litter layer for habitat, food, and shelter. In this study, we summarize the biology, invasion, and ecological impacts of invasive jumping worms across North America. We highlight potential impacts of this second wave of earthworm invasion, contrast them with the preceding European earthworm invasion in temperate forests in North America, and identify annual life cycle, reproductive and cocoon survival strategies, casting behavior and co-invasion dynamics as the key factors that contribute to their successful invasion and distinct ecological impacts. We then suggest potential management and control strategies for practitioners and policy makers, underscore the importance of coordinated community science projects in tracking the spread, and identify knowledge gaps that need to be addressed to understand and control the invasion.

The study of phenomena such as protein folding and conformational changes in molecules is a central theme in chemical physics. Molecular dynamics (MD) simulation is the primary tool for the study of transition processes in biomolecules, but it is hampered by a huge timescale gap between the processes of interest and atomic vibrations which dictate the time step size. Therefore, it is imperative to combine MD simulations with other techniques in order to quantify the transition processes taking place on large timescales. In this work, the diffusion map with Mahalanobis kernel, a meshless approach for approximating the Backward Kolmogorov Operator (BKO) in collective variables, is upgraded to incorporate standard enhanced sampling techniques such as metadynamics. The resulting algorithm, which we call the "target measure Mahalanobis diffusion map" (tm-mmap), is suitable for a moderate number of collective variables in which one can approximate the diffusion tensor and free energy. Imposing appropriate boundary conditions allows use of the approximated BKO to solve for the committor function and utilization of transition path theory to find the reactive current delineating the transition channels and the transition rate. The proposed algorithm, tm-mmap, is tested on the two-dimensional Moro-Cardin two-well system with position-dependent diffusion coefficient and on alanine dipeptide in two collective variables where the committor, the reactive current, and the transition rate are compared to those computed by the finite element method (FEM). Finally, tm-mmap is applied to alanine dipeptide in four collective variables where the use of finite elements is infeasible., Restructured introduction, improved explanation of key algorithms and formulas (Section II.C and III.B,C). Streamlined presentation and proof of Theorem 1

The impacts of climate change on biodiversity can be modulated by other changing environmental conditions (e.g. induced by land‐use change). The potential interactive effects of climate change and land use have rarely been studied for soil organisms. To test the effects of changing climatic conditions and land use on soil invertebrates, we examined earthworm communities across different seasons in different grassland‐use types (intensively managed grassland, extensively managed meadow and extensively managed sheep pasture). We predicted that the strength of climate change effects would vary with season and land use. Overall, extracted earthworm populations showed the strongest variations in response to the season, indicating major differences in activity patterns and extraction efficiency, whereas climate change and different grassland‐use types had fewer and weaker effects. Future climate, characterized by slightly higher precipitation in spring and autumn but a strong reduction during the summer, had positive effects on the abundance of extracted adult earthworms in spring but then reduced the abundance of active earthworms across the remaining seasons. In contrast, the total biomass of juveniles tended to be consistently lower under future climate conditions. Earthworm species responded differently to the climate change and different grassland management types, and these species‐specific responses further varied strongly across seasons. Intensive grassland management had negative effects, due to plant community composition, whereas sheep grazing favoured earthworm populations, due to dung deposition. There were only limited interactive effects between climate and land use, which thus did not support our main hypothesis. Nevertheless, these results highlight the complex and context‐dependent responses of earthworm communities and activity patterns to climate change, with potential consequences for long‐term population dynamics and crucial ecosystem functions. HIGHLIGHTS: We explored earthworm communities in response to climate change, different grassland‐use types and seasons Climate had species‐specific effects on active earthworms, but few interactions with land‐use type Intensive grassland management decreased, but sheep grazing favoured, active earthworm populations Strong seasonal variations in earthworm activity periods will be modulated by climate change

SummaryFungi play pivotal roles in ecosystem functioning, but little is known about their global patterns of diversity, endemicity, vulnerability to global change drivers and conservation priority areas. We applied the high-resolution PacBio sequencing technique to identify fungi based on a long DNA marker that revealed a high proportion of hitherto unknown fungal taxa. We used a Global Soil Mycobiome consortium dataset to test relative performance of various sequencing depth standardization methods (calculation of residuals, exclusion of singletons, traditional and SRS rarefaction, use of Shannon index of diversity) to find optimal protocols for statistical analyses. Altogether, we used six global surveys to infer these patterns for soil-inhabiting fungi and their functional groups. We found that residuals of log-transformed richness (including singletons) against log-transformed sequencing depth yields significantly better model estimates compared with most other standardization methods. With respect to global patterns, fungal functional groups differed in the patterns of diversity, endemicity and vulnerability to main global change predictors. Unlike α-diversity, endemicity and global-change vulnerability of fungi and most functional groups were greatest in the tropics. Fungi are vulnerable mostly to drought, heat, and land cover change. Fungal conservation areas of highest priority include wetlands and moist tropical ecosystems.