Shining a light on species coexistence: visual traits drive bumblebee communities.

Local coexistence of bees has been explained by flower resource partitioning, but coexisting bumblebee species often have strongly overlapping diets. We investigated if light microhabitat niche separation, underpinned by visual traits, could serve as an alternative mechanism underlying local coexistence of bumblebee species. To this end, we focused on a homogeneous flower resource-bilberry-in a heterogeneous light environment-hemi-boreal forests. We found that bumblebee communities segregated along a gradient of light intensity. The community-weighted mean of the eye parameter-a metric measuring the compromise between light sensitivity and visual resolution-decreased with light intensity, showing a higher investment in light sensitivity of communities observed in darker conditions. This pattern was consistent at the species level. In general, species with higher eye parameter (larger investment in light sensitivity) foraged in dimmer light than those with a lower eye parameter (higher investment in visual resolution). Moreover, species realized niche optimum was linearly related to their eye parameter. These results suggest microhabitat niche partitioning to be a potential mechanism underpinning bumblebee species coexistence. This study highlights the importance of considering sensory traits when studying pollinator habitat use and their ability to cope with changing environments.

Predicting the impact of invasive trees from different measures of abundance.

Biological invasions produce negative impacts worldwide, causing massive economic costs and ecological impacts. Knowing the relationship between invasive species abundance and the magnitude of their impacts (abundance-impact curves) is critical to designing prevention and management strategies that effectively tackle these impacts. However, different measures of abundance may produce different abundance-impact curves. Woody plants are among the most transformative invaders, especially in grassland ecosystems because of the introduction of hitherto absent life forms. In this study, our first goal was to assess the impact of a woody invader, Pinus contorta (hereafter pine), on native grassland productivity and livestock grazing in Patagonia (Argentina), building abundance-impact curves. Our second goal, was to compare different measure of pine abundance (density, basal area and canopy cover) as predictors of pine's impact on grassland productivity. Our third goal, was to compare abundance-impact curves among the mentioned measures of pine abundance and among different measures of impact: total grassland productivity, palatable productivity and sheep stocking rate (the number of sheep that the grassland can sustainably support). Pine canopy cover, closely followed by basal area, was the measure of abundance that best explained the impact on grassland productivity, but the shape of abundance impact curves differed between measures of abundance. While increases in pine density and basal area always reduced grassland productivity, pine canopy cover below 30% slightly increased grassland productivity and higher values caused an exponential decline. This increase in grassland productivity with low levels of pine canopy cover could be explained by the amelioration of stressful abiotic conditions for grassland species. Different measures of impact, namely total productivity, palatable productivity and sheep stocking rate, drew very similar results. Our abundance-impact curves are key to guide the management of invasive pines because a proper assessment of how many invasive individuals (per surface unit) are unacceptable, according to environmental or economic impact thresholds, is fundamental to define when to start management actions.

Case Report of Puffinosis in a Manx Shearwater (Puffinus puffinus) Suggesting Environmental Aetiology.

Puffinosis is a disease of a range of seabirds characterised by dorsal and ventral blistering of their webbed feet, conjunctivitis, dry necrosis, leg spasticity, head shaking, loss of balance, tremors, and death. It is associated with Manx shearwaters (Puffinus puffinus), frequently affecting chicks within their underground nesting burrows. The aetiology of the disease is unclear but has been attributed to a type-2 coronavirus associated with Neotombicula mites as a potential vector. However, there is some uncertainty given potential laboratory contamination with mouse hepatitis virus and failure to fulfil Koch's postulates, with birds injected with isolates remaining healthy. We describe a detailed case report of puffinosis in a Manx Shearwater covering necropsy, histology, bacteriology, and metagenomics including viral sequencing. We found no evidence of viral infection or parasites. Our results are consistent with an entirely environmental aetiology, with caustic faecal ammonia in damp nesting burrows causing conjunctivitis and foot dermatitis breaking the skin, allowing common soil bacteria (i.e., Flavobacterium, Staphylococcus and Serratia spp., Clostridia perfringens and Enterococcus faecalis) to cause opportunistic infection, debilitating the bird and leading to death. A similar condition (foot pad dermatitis or FPD) has been reported in broiler chickens, attributed to caustic faeces, high humidity, and poor environmental conditions during indoor rearing, preventable by adequate ventilation and husbandry. This is consistent with puffinosis being observed in Shearwater nesting burrows situated in tall, dense, vegetation (e.g., bracken Pteridium aquilinum) but rarely reported in burrows situated in well-ventilated, short coastal grasslands. This proposed environmental aetiology accounts for the disease's non-epizootic prevalence, spatial variation within colonies, and higher frequency in chicks that are restricted to nesting burrows.

Understanding the role of wild ruminants in anthelmintic resistance in livestock.

Wild ruminants are susceptible to infection from generalist helminth species, which can also infect domestic ruminants. A better understanding is required of the conditions under which wild ruminants can act as a source of helminths (including anthelmintic-resistant genotypes) for domestic ruminants, and vice versa, with the added possibility that wildlife could act as refugia for drug-susceptible genotypes and hence buffer the spread and development of resistance. Helminth infections cause significant productivity losses in domestic ruminants and a growing resistance to all classes of anthelmintic drug escalates concerns around helminth infection in the livestock industry. Previous research demonstrates that drug-resistant strains of the pathogenic nematode Haemonchus contortus can be transmitted between wild and domestic ruminants, and that gastro-intestinal nematode infections are more intense in wild ruminants within areas of high livestock density. In this article, the factors likely to influence the role of wild ruminants in helminth infections and anthelmintic resistance in livestock are considered, including host population movement across heterogeneous landscapes, and the effects of climate and environment on parasite dynamics. Methods of predicting and validating suspected drivers of helminth transmission in this context are considered based on advances in predictive modelling and molecular tools.

Comparison of the distribution and phenology of Arctic Mountain plants between the early 20th and 21st centuries.

Arctic plants are adapted to climatic variability, but their long-term responses to warming remain unclear. Responses may occur by range shifts, phenological adjustments in growth and reproduction, or both. Here, we compare distribution and phenology of 83 arctic and boreal mountain species, sampled identically in the early 20th (1917-1919) and 21st centuries (2017-2018) from a region of northern Sweden that has warmed significantly. We test two compensatory hypotheses to high-latitude warming-upward shifts in distribution, and earlier or extended growth and reproduction. For distribution, we show dramatic upward migration by 69% of species, averaging 6.1 m per decade, especially boreal woodland taxa whose upward expansion has reduced arctic montane habitat by 30%. Twenty percent of summit species showed distributional shifts but downward, especially moisture-associated snowbed flora. For phenology, we detected wide inter-annual variability in the onset of leafing and flowering in both eras. However, there was no detectable change in growing-season length, relating to two mechanisms. First, plot-level snow melt data starting in 1917 demonstrated that melt date, rather than vernal temperatures, better predicts plant emergence, with snow melt influenced by warmer years having greater snowfall-warmer springs did not always result in earlier emergence because snowbeds can persist longer. Second, the onset of reproductive senescence between eras was similar, even when plant emergence was earlier by a month, possibly due to intensified summer heat stress or hard-wired 'canalization' where senescence occurs regardless of summer temperature. Migrations in this system have possibly buffered arctic species against displacement by boreal expansion and warming, but ongoing temperature increases, woody plant invasion, and a potential lack of flexibility in timing of senescence may foreshadow challenges.

Data quantity is more important than its spatial bias for predictive species distribution modelling.

Biological records are often the data of choice for training predictive species distribution models (SDMs), but spatial sampling bias is pervasive in biological records data at multiple spatial scales and is thought to impair the performance of SDMs. We simulated presences and absences of virtual species as well as the process of recording these species to evaluate the effect on species distribution model prediction performance of (1) spatial bias in training data, (2) sample size (the average number of observations per species), and (3) the choice of species distribution modelling method. Our approach is novel in quantifying and applying real-world spatial sampling biases to simulated data. Spatial bias in training data decreased species distribution model prediction performance, but sample size and the choice of modelling method were more important than spatial bias in determining the prediction performance of species distribution models.

Quantifying large-scale ecosystem stability with remote sensing data.

To fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite-derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field-plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small-scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely-sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices.

Land cover drives large scale productivity-diversity relationships in Irish vascular plants.

The impact of productivity on species diversity is often studied at small spatial scales and without taking additional environmental factors into account. Focusing on small spatial scales removes important regional scale effects, such as the role of land cover heterogeneity. Here, we use a regional spatial scale (10 km square) to establish the relationship between productivity and vascular plant species richness across the island of Ireland that takes into account variation in land cover. We used generalized additive mixed effects models to relate species richness, estimated from biological records, to plant productivity. Productivity was quantified by the satellite-derived enhanced vegetation index. The productivity-diversity relationship was fitted for three land cover types: pasture-dominated, heterogeneous, and non-pasture-dominated landscapes. We find that species richness decreases with increasing productivity, especially at higher productivity levels. This decreasing relationship appears to be driven by pasture-dominated areas. The relationship between species richness and heterogeneity in productivity (both spatial and temporal) varies with land cover. Our results suggest that the impact of pasture on species richness extends beyond field level. The effect of human modified landscapes, therefore, is important to consider when investigating classical ecological relationships, particularly at the wider landscape scale.

Usefulness of Species Traits in Predicting Range Shifts.

Information on the ecological traits of species might improve predictions of climate-driven range shifts. However, the usefulness of traits is usually assumed rather than quantified. Here, we present a framework to identify the most informative traits, based on four key range-shift processes: emigration of individuals or propagules away from the natal location; the distance a species can move; establishment of self-sustaining populations; and proliferation following establishment. We propose a framework that categorises traits according to their contribution to range-shift processes. We demonstrate how the framework enables the predictive value of traits to be evaluated empirically and how this categorisation can be used to better understand range-shift processes; we also illustrate how range-shift estimates can be improved.

Seed terminal velocity, wind turbulence, and demography drive the spread of an invasive tree in an analytical model.

Little is known about the relative importance of mechanistic drivers of plant spread, particularly when long-distance dispersal (LDD) events occur. Most methods to date approach LDD phenomenologically, and all mechanistic models, with one exception, have been implemented through simulation. Furthermore, the few recent mechanistically derived spread models have examined the relative role of different dispersal parameters using simulations, and a formal analytical approach has not yet been implemented. Here we incorporate an analytical mechanistic wind dispersal model (WALD) into a demographic matrix model within an analytical integrodifference equation spread model. We carry out analytical perturbation analysis on the combined model to determine the relative effects of dispersal and demographic traits and wind statistics on the spread of an invasive tree. Models are parameterized using data collected in situ and tested using independent data on historical spread. Predicted spread rates and direction match well the two historical phases of observed spread. Seed terminal velocity has the greatest potential influence on spread rate, and three wind properties (turbulence coefficient, mean horizontal wind speed, and standard deviation of vertical wind speed) are also important. Fecundity has marginal importance for spread rate, but juvenile survival and establishment are consistently important. This coupled empirical/theoretical framework enables prediction of plant spread rate and direction using fundamental dispersal and demographic parameters and identifies the traits and environmental conditions that facilitate spread. The development of an analytical perturbation analysis for a mechanistic spread model will enable multispecies comparative studies to be easily implemented in the future.

Modeling population dynamics, landscape structure, and management decisions for controlling the spread of invasive plants.

Invasive plants cause substantial economic and environmental damage throughout the world. However, eradication of most invasive species is impossible and, in some cases, undesirable. An alternative is to slow the spread of an invasive species, which can delay impacts or reduce their extent. We identify three main areas where models are used extensively in the study of plant spread and its management: (i) identifying the key drivers of spread to better target management, (ii) determining the role spatial structure of landscapes plays in plant invasions, and (iii) integrating management structures and limitations to guide the implementation of control measures. We show how these three components have been approached in the ecological literature as well as their potential for improving management practices. Particularly, we argue that scientists can help managers of invasive species by providing information about plant invasion on which managers can base their decisions (i and ii) and by modeling the decision process through optimization and agent-based models (iii). Finally, we show how these approaches can be articulated for integrative studies.

Integrating ecological knowledge, public perception and urgency of action into invasive species management.

Recently Prévot-Julliard and colleagues presented a concept paper on biological conservation strategies using exotic species as a case study. They emphasized the difficulty of integrating conservation into a broad picture that accounts for public perception as well as scientific knowledge. We support this general call for better integration of society in conservation research, but we believe that the original framework might misguide conservation practices if wrongly interpreted. Our objective is to complement their paper and correct a few misleading points, by showing that (1) for regions of high endemicity "reservation" may be the best conservation practice, and does not prevent public participation, (2) aiming for broad societal agreement is valuable, but in some cases risky, and always complex, and (3) calling a harmful invasive species harmful shouldn't be an issue. The Australian context provides us with many cases of the labeling of exotic species as harmful or not, using inputs from scientists, industry, and the public. Integration of social and scientific points of view can only improve conservation on the ground if it allows managers to use the ecological, economic and social impacts of exotic species to prioritize conservation actions in an operative way.