Comment on "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate", author Coro.

In this letter we present comments on the article "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus" by Coro published in 2020.

Q(ST)-F(ST) comparisons: evolutionary and ecological insights from genomic heterogeneity.

Comparative studies of the divergence of quantitative traits and neutral molecular markers, known as Q(ST)-F(ST) comparisons, provide a means for researchers to distinguish between natural selection and genetic drift as causes of population differentiation in complex polygenic traits. The use of Q(ST)-F(ST) comparisons has increased rapidly in the last few years, highlighting the utility of this approach for addressing a wide range of questions that are relevant to evolutionary and ecological genetics. These studies have also provided lessons for the design of future Q(ST)-F(ST) comparisons. Methods based on the Q(ST)-F(ST) approach could also be used to analyse various types of 'omics' data in new and revealing ways.

Uncovering the drivers of host-associated microbiota with joint species distribution modelling.

In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates such as diet and collection site, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including (a) model-based ordination to visualize and quantify the main patterns in the data; (b) variance partitioning to assess how influential the included host-specific factors are in structuring the microbiota; and (c) co-occurrence networks to visualize microbe-to-microbe associations.

Disentangling the effects of multiple environmental drivers on population changes within communities.

The effects of different environmental drivers on the changes in species' population abundances can be difficult to disentangle as they often act simultaneously. Researchers have built statistical models that include environmental variables (such as annual temperature) or species attributes (such as a species' temperature preference), which are assumed to detect the impacts of specific drivers (such as climate change). However, these approaches are often applied separately or, if combined, not explicitly compared. We show the complementary insights gained by applying both these approaches to a community dataset on Danish terrestrial birds. We use our analysis to compare the relative importance of climate change and agricultural land-use change for the abundance changes within the community between 1983 and 2013. Population models were fitted to the community data of species' annual abundances with predictors comprising: species attributes (species' temperature and habitat preferences), environmental variables (climatic and agricultural land-use change variables) or both. Relationships between species' abundances and environmental variables were used to identify the drivers associated with average abundance changes of species in the community. Relationships between species' abundances and their attributes were used to understand the drivers causing interspecific variation in abundance changes. Warmer winters were positively associated with community-level abundances, and warm-adapted species had more positive abundance changes than cold-adapted ones. Agricultural land-use area was negatively associated with community-level abundances, and birds using a high proportion of meadow and habitat specialists had more negative abundance changes than birds using other habitats and habitat generalists. Effect sizes of environmental variables were larger for agricultural land-use change while those of species attributes were larger for climate change. The environmental data approach suggested that agricultural land-use change has decreased the average abundances of species in the community, affecting total community size while the species attribute-based approach suggested that climate change has caused variation in abundance among species, affecting community composition. Environmental variables and species attributes that are hypothesized to link to specific drivers can be used together to provide complementary information on the impacts of different drivers on communities.

Disentangling synergistic disease dynamics: Implications for the viral biocontrol of rabbits.

European rabbits (Oryctolagus cuniculus) have been exposed to rabbit haemorrhagic disease virus (RHDV) and myxoma virus (MYXV) in their native and invasive ranges for decades. Yet, the long-term effects of these viruses on rabbit population dynamics remain poorly understood. In this context, we analysed 17 years of detailed capture-mark-recapture data (2000-2016) from Turretfield, South Australia, using a probabilistic state-space hierarchical modelling framework to estimate rabbit survival and epidemiological dynamics. While RHDV infection and disease-induced death were most prominent during annual epidemics in winter and spring, we found evidence for continuous infection of susceptible individuals with RHDV throughout the year. RHDV-susceptible rabbits had, on average, 25% lower monthly survival rates compared to immune individuals, while the average monthly force of infection in winter and spring was ~38%. These combined to result in an average infection-induced mortality rate of 69% in winter and spring. Individuals susceptible to MYXV and immune to RHDV had similar survival probabilities to those having survived infections from both viruses, whereas individuals susceptible to both RHDV and MYXV had higher survival probabilities than those susceptible to RHDV and immune to MYXV. This suggests that MYXV may reduce the future survival rates of individuals that endure initial MYXV infection. There was no evidence for long-term changes in disease-induced mortality and infection rates for either RHDV or MYXV. We conclude that continuous, year-round virus perpetuation (and perhaps heterogeneity in modes of transmission and infectious doses during and after epidemics) acts to reduce the efficiency of RHDV and MYXV as biocontrol agents of rabbits in their invasive range. However, if virulence can be maintained as relatively constant through time, RHDV and MYXV will likely continue realizing strong benefits as biocontrol agents.

Cross-taxa generalities in the relationship between population abundance and ambient temperatures.

Identifying patterns in the effects of temperature on species' population abundances could help develop a general framework for predicting the consequences of climate change across different communities and realms. We used long-term population time series data from terrestrial, freshwater, and marine species communities within central Europe to compare the effects of temperature on abundance across a broad range of taxonomic groups. We asked whether there was an average relationship between temperatures in different seasons and annual abundances of species in a community, and whether species attributes (temperature range of distribution, range size, habitat breadth, dispersal ability, body size, and lifespan) explained interspecific variation in the relationship between temperature and abundance. We found that, on average, warmer winter temperatures were associated with greater abundances in terrestrial communities (ground beetles, spiders, and birds) but not always in aquatic communities (freshwater and marine invertebrates and fish). The abundances of species with large geographical ranges, larger body sizes, and longer lifespans tended to be less related to temperature. Our results suggest that climate change may have, in general, positive effects on species' abundances within many terrestrial communities in central Europe while the effects are less predictable in aquatic communities.

Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes.

The reproduction of many species is determined by seasonally-driven resource supply. But it is difficult to quantify whether the fecundity is sensitive to short- or long-term exposure to environmental conditions such as rainfall that drive resource supply. Using 25 years of data on individual fecundity of European female rabbits, Oryctolagus cuniculus, from semiarid Australia, we investigate the role of individual body condition, rainfall and temperature as drivers of seasonal and long-term and population-level changes in fecundity (breeding probability, ovulation rate, embryo survival). We built distributed lag models in a hierarchical Bayesian framework to account for both immediate and time-lagged effects of climate and other environmental drivers, and possible shifts in reproduction over consecutive seasons. We show that rainfall during summer, when rabbits typically breed only rarely, increased breeding probability immediately and with time lags of up to 10 weeks. However, an earlier onset of the yearly breeding period did not result in more overall reproductive output. Better body condition was associated with an earlier onset of breeding and higher embryo survival. Breeding probability in the main breeding season declined with increased breeding activity in the preceding season and only individuals in good body condition were able to breed late in the season. Higher temperatures reduce breeding success across seasons. We conclude that a better understanding of seasonal dynamics and plasticity (and their interplay) in reproduction will provide crucial insights into how lagomorphs are likely to respond and potentially adapt to the influence of future climate and other environmental change.

Relocation, high-latitude warming and host genetic identity shape the foliar fungal microbiome of poplars.

Micro-organisms associated with plants and animals affect host fitness, shape community structure and influence ecosystem properties. Climate change is expected to influence microbial communities, but their reactions are not well understood. Host-associated micro-organisms are influenced by the climate reactions of their hosts, which may undergo range shifts due to climatic niche tracking, or may be actively relocated to mitigate the effects of climate change. We used a common-garden experiment and rDNA metabarcoding to examine the effect of host relocation and high-latitude warming on the complex fungal endophytic microbiome associated with leaves of an ecologically dominant boreal forest tree (Populus balsamifera L.). We also considered the potential effects of poplar genetic identity in defining the reactions of the microbiome to the treatments. The relocation of hosts to the north increased the diversity of the microbiome and influenced its structure, with results indicating enemy release from plausible pathogens. High-latitude warming decreased microbiome diversity in comparison with natural northern conditions. The warming also caused structural changes, which made the fungal communities distinct in comparison with both low-latitude and high-latitude natural communities, and increased the abundance of plausible pathogens. The reactions of the microbiome to relocation and warming were strongly dependent on host genetic identity. This suggests that climate change effects on host-microbiome systems may be mediated by the interaction of environmental factors and the population genetic processes of the hosts.

Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal.

BACKGROUND: Over the last decade, the incidence of confirmed malaria has declined significantly in Nepal. The aim of this paper is to assess the spatio-temporal distribution of malaria and its association with climatic factors and vector control interventions in two high-risk districts of Nepal. METHODS: Hotspot analysis was used to visualize the spatio-temporal variation of malaria incidence over the years at village level and generalized additive mixed models were fitted to assess the association of malaria incidence with climatic variables and vector control interventions. RESULTS: Opposing trends of malaria incidence were observed in two high-risk malaria districts of eastern and far-western Nepal after the introduction of long-lasting insecticidal nets (LLINs). The confirmed malaria incidence was reduced from 2.24 per 10,000 in 2007 to 0.31 per 10,000 population in 2011 in Morang district but increased from 3.38 to 8.29 per 10,000 population in Kailali district. Malaria hotspots persisted mostly in the same villages of Kailali district, whereas in Morang district malaria hotspots shifted to new villages after the introduction of LLINs. A 1° C increase in minimum and mean temperatures increased malaria incidence by 27% (RR =1.27, 95% CI =1.12-1.45) and 25% (RR =1.25, 95% CI =1.11-1.43), respectively. The reduction in malaria incidence was 25% per one unit increase of LLINs (RR =0.75, 95% CI =0.62-0.92). The incidence of malaria was 82% lower in Morang than in Kailali district (RR =0.18, 95% CI =0.11-0.33). CONCLUSIONS: The study findings suggest that LLIN coverage should be scaled up to entire districts rather than high-incidence foci only. Climatic factors should be considered for malaria micro-stratification, mosquito repellents should be prescribed for those living in forests, forest fringe and foothills and have regular visits to forests, and imported cases should be controlled by establishing fever check posts at border crossings.

Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers.

We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939-1940). We measured facial width-to-height ratio-a trait known to predict aggressive behaviour in males-and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank.

Inferring host specificity and network formation through agent-based models: tick-mammal interactions in Borneo.

Patterns of host-parasite association are poorly understood in tropical forests. While we typically observe only snapshots of the diverse assemblages and interactions under variable conditions, there is a desire to make inferences about prevalence and host-specificity patterns. We studied the interaction of ticks with non-volant small mammals in forests of Borneo. We inferred the probability of species interactions from individual-level data in a multi-level Bayesian model that incorporated environmental covariates and advanced estimates for rarely observed species through model averaging. We estimated the likelihood of observing particular interaction frequencies under field conditions and a scenario of exhaustive sampling and examined the consequences for inferring host specificity. We recorded a total of 13 different tick species belonging to the five genera Amblyomma, Dermacentor, Haemaphysalis, Ixodes, and Rhipicephalus from a total of 37 different host species (Rodentia, Scandentia, Carnivora, Soricidae) on 237 out of 1,444 host individuals. Infestation probabilities revealed most variation across host species but less variation across tick species with three common rat and two tree shrew species being most heavily infested. Host species identity explained ca. 75 % of the variation in infestation probability and another 8-10 % was explained by local host abundance. Host traits and site-specific attributes had little explanatory power. Host specificity was estimated to be similarly low for all tick species, which were all likely to infest 34-37 host species if exhaustively sampled. By taking into consideration the hierarchical organization of individual interactions that may take place under variable conditions and that shape host-parasite networks, we can discern uncertainty and sampling bias from true interaction frequencies, whereas network attributes derived from observed values may lead to highly misleading results. Multi-level approaches may help to move this field towards inferential approaches for understanding mechanisms that shape the strength and dynamics in ecological networks.

Recognizability bias in citizen science photographs.

Citizen science and automated collection methods increasingly depend on image recognition to provide the amounts of observational data research and management needs. Recognition models, meanwhile, also require large amounts of data from these sources, creating a feedback loop between the methods and tools. Species that are harder to recognize, both for humans and machine learning algorithms, are likely to be under-reported, and thus be less prevalent in the training data. As a result, the feedback loop may hamper training mostly for species that already pose the greatest challenge. In this study, we trained recognition models for various taxa, and found evidence for a 'recognizability bias', where species that are more readily identified by humans and recognition models alike are more prevalent in the available image data. This pattern is present across multiple taxa, and does not appear to relate to differences in picture quality, biological traits or data collection metrics other than recognizability. This has implications for the expected performance of future models trained with more data, including such challenging species.

Limited climatic space for alternative ecosystem states in Africa.

One of the foundational premises of ecology is that climate determines ecosystems. This has been challenged by alternative ecosystem state models, which illustrate that internal ecosystem dynamics acting on the initial ecosystem state can overwhelm the influence of climate, and by observations suggesting that climate cannot reliably discriminate forest and savanna ecosystem types. Using a novel phytoclimatic transform, which estimates the ability of climate to support different types of plants, we show that climatic suitability for evergreen trees and C4 grasses are sufficient to discriminate between forest and savanna in Africa. Our findings reassert the dominant influence of climate on ecosystems and suggest that the role of feedbacks causing alternative ecosystem states is less prevalent than has been suggested.

Ectoparasite infestation patterns of domestic dogs in suburban and rural areas in Borneo.

Domestic dogs, Canis lupus, have been one of the longest companions of humans and have introduced their own menagerie of parasites and pathogens into this relationship. Here, we investigate the parasitic load of 212 domestic dogs with fleas (Siphonaptera) chewing lice (Phthiraptera), and ticks (Acarina) along a gradient from rural areas with near-natural forest cover to suburban areas in Northern Borneo (Sabah, Malaysia). We used a spatially-explicit hierarchical Bayesian model that allowed us to impute missing data and to consider spatial structure in modelling dog infestation probability and parasite density. We collected a total of 1,968 fleas of two species, Ctenocephalides orientis and Ctenocephalides felis felis, from 195 dogs (prevalence, 92 %). Flea density was higher on dogs residing in houses made of bamboo or corrugated metal (increase of 40 % from the average) compared to timber or stone/compound houses. Host-dependent and landscape-level environmental variables and spatial structure only had a weak explanatory power. We found adults of the invasive chewing louse Heterodoxus spiniger on 42 dogs (20 %). The effect of housing conditions was opposite to those for fleas; lice were only found on dogs residing in stone or timber houses. We found ticks of the species Rhipicephalus sanguineus as well as Haemaphysalis bispinosa gp., Haemaphysalis cornigera, Haemaphysalis koenigsbergi, and Haemaphysalis semermis on 36 dogs (17 %). The most common tick species was R. sanguineus, recorded from 23 dogs. Tick infestations were highest on dogs using both plantation and forest areas (282 % increase in overall tick density of dogs using all habitat types). The infestation probability of dogs with lice and ticks decreased with elevation, most infestations occurred below 800 m above sea level. However, the density of lice and ticks revealed no spatial structure; infestation probability of dogs with these two groups revealed considerable autocorrelation. Our study shows that environmental conditions on the house level appeared to be more influential on flea and lice density whereas tick density was also influenced by habitat use. Infestation of dogs with Haemaphysalis ticks identified an important link between dogs and forest wildlife for potential pathogen transmission.

Rewriting results sections in the language of evidence.

Despite much criticism, black-or-white null-hypothesis significance testing with an arbitrary P-value cutoff still is the standard way to report scientific findings. One obstacle to progress is likely a lack of knowledge about suitable alternatives. Here, we suggest language of evidence that allows for a more nuanced approach to communicate scientific findings as a simple and intuitive alternative to statistical significance testing. We provide examples for rewriting results sections in research papers accordingly. Language of evidence has previously been suggested in medical statistics, and it is consistent with reporting approaches of international research networks, like the Intergovernmental Panel on Climate Change, for example. Instead of re-inventing the wheel, ecology and evolution might benefit from adopting some of the 'good practices' that exist in other fields.

Insights into the quantification and reporting of model-related uncertainty across different disciplines.

Quantifying uncertainty associated with our models is the only way we can express how much we know about any phenomenon. Incomplete consideration of model-based uncertainties can lead to overstated conclusions with real-world impacts in diverse spheres, including conservation, epidemiology, climate science, and policy. Despite these potentially damaging consequences, we still know little about how different fields quantify and report uncertainty. We introduce the "sources of uncertainty" framework, using it to conduct a systematic audit of model-related uncertainty quantification from seven scientific fields, spanning the biological, physical, and political sciences. Our interdisciplinary audit shows no field fully considers all possible sources of uncertainty, but each has its own best practices alongside shared outstanding challenges. We make ten easy-to-implement recommendations to improve the consistency, completeness, and clarity of reporting on model-related uncertainty. These recommendations serve as a guide to best practices across scientific fields and expand our toolbox for high-quality research.

Female-biased expression on the X chromosome as a key step in sex chromosome evolution in threespine sticklebacks.

Given that the genome of males and females are almost identical with the exception of genes on the Y (or W) chromosome or sex-determining alleles (in organisms without sex chromosomes), it is likely that many downstream processes resulting in sexual dimorphism are produced by changes in regulation. In early stages of sex chromosome evolution, as the Y-chromosome degenerates, gene expression should be significantly impacted for genes residing on the sex chromosome pair as regulatory mutations accumulate. However, this has rarely been examined because most model organisms have clearly diverged sex chromosomes. Fish provide a unique opportunity to examine the evolution of sex chromosomes because genetic sex determination has evolved quite recently in some groups of fish. We compared sex-specific transcription in threespine stickleback (Gasterosteus aculeatus) liver tissue using a long-oligo microarray. Of the 1,268 genes that were differentially expressed between sexes, a highly significant proportion (23%) was concentrated on chromosome 19, corresponding to the recently described nascent sex chromosomes. The sex-biased genes are enriched for different functional categories in males and females, although there is no specific functional enrichment on the sex chromosomes. Female-biased genes are concentrated at one end of the sex chromosome, corresponding to a deletion in the Y, suggesting a lack of global dosage compensation. Prior research on threespine sticklebacks has demonstrated various degrees of dissimilarity in upstream regions of genes on the Y providing a potential mechanism for the observed patterns of female-biased expression. We hypothesize that degeneration of the Y chromosome results in regulatory mutations that create a sex-specific expression pattern and that this physical concentration of sex-biased expression on the nascent sex chromosome may be a key feature characterizing intermediate phases of sex chromosome evolution.

Tree allometries reflect a lifetime of herbivory in an African savanna.

Theories of plant allometry provide a general description of allometric scaling that is supposedly applicable across a wide array of environmental conditions. Scaling theories, however, ignore disturbances such as herbivory in their derivation. Here we examine the influence of herbivores on the scaling of height and diameter of two common African savanna tree species. Using Bayesian piecewise regressions, we show that herbivores modify tree allometry. We also show that the pattern of allometric modification contains information regarding herbivore foraging behavior and the resultant alteration of plant architecture. Interpreting realized allometries in the light of theoretical predictions based on assumptions of zero disturbances may help reveal the degree of herbivore impacts. However, predictions of plant form and function that fail to include disturbances such as herbivory may struggle to find general applicability.

A multispecies perspective on ecological impacts of climatic forcing.

1. In the prevailing context of concerns over climate change and its potential impacts on ecosystems, evaluating ecological consequences of climatic forcing has become a critical issue. 2. Historical data on the abundance of organisms have been extensively used to characterize the ecological effects of climatic forcing through specific weather and/or climatic variables, with most of the studies confined to single population models. 3. However, population responses to environmental fluctuations typically depend upon positive and negative feedbacks induced by interactions with other species. It is therefore important to integrate the insights gained from single population approaches into a multispecies perspective. 4. Here we combine the hierarchical Bayesian modelling approach with the state-space formulation to extend the scope of previously proposed models of population dynamics under climatic forcing to multi-species systems. 5. We use our model to analyse long-term macro-moth (Lepidoptera) community data from the Rothamsted Insect Survey network in the UK, using winter rainfall and winter temperature as environmental covariates. 6. The effects of the two weather variables were consistent across species, being negative for winter rainfall and positive for winter temperature. The two weather variables jointly explained 15-40% of the total environmental variation affecting the dynamics of individual species, and could explain up to 90% of covariances in species dynamics. 7. The contribution of interspecific interactions to community-level variation was found to be weak compared to the contributions of environmental forcing and intraspecific interactions.

Integrating the niche and neutral perspectives on community structure and dynamics.

Elucidating the mechanisms underlying the assembly and dynamics of ecological communities is a fundamental goal of ecology. Two conceptual approaches have emerged in this respect: the niche-assembly view and the neutral perspective. The debate as to which approach best explains the biodiversity patterns observed in nature is becoming outdated, as ecologists increasingly agree on the existence of a niche-neutral continuum of community dynamical behaviors. However, attempts to make the continuum idea operational and measurable remain sparse. Here, we propose a model-based approach to achieving this. The proposed methodology consists of separating out fluctuations in species abundances into niche-mediated and stochastic factors, linking the niche configuration to community dynamics through competition, and adding demographic stochasticity. This results in a comprehensive framework including neutrality and strict niche segregation as extreme cases. We develop an index of departure from neutral drift as a surrogate for community position on the niche-neutral continuum. We evaluate the performance of our modeling approach with simulated data, and subsequently use the model to analyze rodent web-trapping data from a real-world system. The model fitting is carried out with a Bayesian approach using Markov chain Monte Carlo simulation methods.