Resource competition drives an invasion-replacement event among shrew species on an island.

Invasive mammals are responsible for the majority of native species extinctions on islands. While most of these extinction events will be due to novel interactions between species (e.g. exotic predators and naive prey), it is more unusual to find incidences where a newly invasive species causes the decline/extinction of a native species on an island when they normally coexist elsewhere in their overlapping mainland ranges. We investigated if resource competition between two insectivorous small mammals was playing a significant role in the rapid replacement of the native pygmy shrew Sorex minutus in the presence of the recently invading greater white-toothed shrew Crocidura russula on the island of Ireland. We used DNA metabarcoding of gut contents from >300 individuals of both species to determine each species' diet and measured the body size (weight and length) during different stages of the invasion in Ireland (before, during and after the species come into contact with one another) and on a French island where both species have long coexisted (acting as a natural 'control' site). Dietary composition, niche width and overlap and body size were compared in these different stages. The body size of the invasive C. russula and composition of its diet changes between when it first invades an area and after it becomes established. During the initial stages of the invasion, individual shrews are larger and consume larger sized invertebrate prey species. During later stages of the invasion, C. russula switches to consuming smaller prey taxa that are more essential for the native species. As a result, the level of interspecific dietary overlap increases from between 11% and 14% when they first come into contact with each other to between 39% and 46% after the invasion. Here we show that an invasive species can quickly alter its dietary niche in a new environment, ultimately causing the replacement of a native species. In addition, the invasive shrew could also be potentially exhausting local resources of larger invertebrate species. These subsequent changes in terrestrial invertebrate communities could have severe impacts further downstream on ecosystem functioning and services.

Meteorological factors associated with the timing and abundance of Hymenoscyphus fraxineus spore release.

The ascomycete Hymenoscyphus fraxineus has spread across most of the host range of European ash with a high level of mortality, causing important economic, cultural and environmental effects. We present a novel method combining a Monte-Carlo approach with a generalised additive model that confirms the importance of meteorology to the magnitude and timing of H. fraxineus spore emissions. The variability in model selection and the relative degree to which our models are over- or under-fitting the data has been quantified. We find that both the daily magnitude and timing of spore emissions are affected by meteorology during and prior to the spore emission diurnal peak. We found the daily emission magnitude has the strongest associations to weekly average net radiation and leaf moisture before the emission, soil temperature during the day before emission and net radiation during the spore emission. The timing of the daily peak in spore emissions has the strongest associations to net radiation both during spore emission and in the day preceding the emission. The seasonal peak in spore emissions has a near-exponential increase/decrease, and the mean daily emission peak is approximately Gaussian.

Phenotypic variation from waterlogging in multiple perennial ryegrass varieties under climate change conditions.

Identifying how various components of climate change will influence ecosystems and vegetation subsistence will be fundamental to mitigate negative effects. Climate change-induced waterlogging is understudied in comparison to temperature and CO2. Grasslands are especially vulnerable through the connection with global food security, with perennial ryegrass dominating many flood-prone pasturelands in North-western Europe. We investigated the effect of long-term waterlogging on phenotypic responses of perennial ryegrass using four common varieties (one diploid and three tetraploid) grown in atmospherically controlled growth chambers during two months of peak growth. The climate treatments compare ambient climatological conditions in North-western Europe to the RCP8.5 climate change scenario in 2050 (+2°C and 550 ppm CO2). At the end of each month multiple phenotypic plant measurements were made, the plants were harvested and then allowed to grow back. Using image analysis and principal component analysis (PCA) methodologies, we assessed how multiple predictors (phenotypic, environmental, genotypic, and temporal) influenced overall plant performance, productivity and phenotypic responses. Long-term waterlogging was found to reduce leaf-color intensity, with younger plants having purple hues indicative of anthocyanins. Plant performance and yield was lower in waterlogged plants, with tetraploid varieties coping better than the diploid one. The climate change treatment was found to reduce color intensities further. Flooding was found to reduce plant productivity via reductions in color pigments and root proliferation. These effects will have negative consequences for global food security brought on by increased frequency of extreme weather events and flooding. Our imaging analysis approach to estimate effects of waterlogging can be incorporated into plant health diagnostics tools via remote sensing and drone-technology.

Loss of functionally unique species may gradually undermine ecosystems.

Functionally unique species contribute to the functional diversity of natural systems, often enhancing ecosystem functioning. An abundance of weakly interacting species increases stability in natural systems, suggesting that loss of weakly linked species may reduce stability. Any link between the functional uniqueness of a species and the strength of its interactions in a food web could therefore have simultaneous effects on ecosystem functioning and stability. Here, we analyse patterns in 213 real food webs and show that highly unique species consistently tend to have the weakest mean interaction strength per unit biomass in the system. This relationship is not a simple consequence of the interdependence of both measures on body size and appears to be driven by the empirical pattern of size structuring in aquatic systems and the trophic position of each species in the web. Food web resolution also has an important effect, with aggregation of species into higher taxonomic groups producing a much weaker relationship. Food webs with fewer unique and less weakly interacting species also show significantly greater variability in their levels of primary production. Thus, the loss of highly unique, weakly interacting species may eventually lead to dramatic state changes and unpredictable levels of ecosystem functioning.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

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.

The fixation of locally beneficial alleles in a metapopulation.

Extinction, recolonization, and local adaptation are common in natural spatially structured populations. Understanding their effect upon genetic variation is important for systems such as genetically modified organism management or avoidance of drug resistance. Theoretical studies on the effect of extinction and recolonization upon genetic variance started appearing in the 1970s, but the role of local adaptation still has no good theoretical basis. Here we develop a model of a haploid species in a metapopulation in which a locally adapted beneficial allele is introduced. We study the effect of different spatial patterns of local adaptation, and different metapopulation dynamics, upon the fixation probability of the beneficial allele. Controlling for the average selection pressure, we find that a small area of positive selection can significantly increase the global probability of fixation. However, local adaptation becomes less important as extinction rate increases. Deme extinction and recolonization have a spatial smoothing effect that effectively reduces spatial variation in fitness.

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.

Does Size Matter? Atmospheric CO2 May Be a Stronger Driver of Stomatal Closing Rate Than Stomatal Size in Taxa That Diversified under Low CO2.

One strategy for plants to optimize stomatal function is to open and close their stomata quickly in response to environmental signals. It is generally assumed that small stomata can alter aperture faster than large stomata. We tested the hypothesis that species with small stomata close faster than species with larger stomata in response to darkness by comparing rate of stomatal closure across an evolutionary range of species including ferns, cycads, conifers, and angiosperms under controlled ambient conditions (380 ppm CO2; 20.9% O2). The two species with fastest half-closure time and the two species with slowest half-closure time had large stomata while the remaining three species had small stomata, implying that closing rate was not correlated with stomatal size in these species. Neither was response time correlated with stomatal density, phylogeny, functional group, or life strategy. Our results suggest that past atmospheric CO2 concentration during time of taxa diversification may influence stomatal response time. We show that species which last diversified under low or declining atmospheric CO2 concentration close stomata faster than species that last diversified in a high CO2 world. Low atmospheric [CO2] during taxa diversification may have placed a selection pressure on plants to accelerate stomatal closing to maintain adequate internal CO2 and optimize water use efficiency.

Effects of spatial heterogeneity in moisture content on the horizontal spread of peat fires.

The gravimetric moisture content of peat is the main factor limiting the ignition and spread propagation of smouldering fires. Our aim is to use controlled laboratory experiments to better understand how the spread of smouldering fires is influenced in natural landscape conditions where the moisture content of the top peat layer is not homogeneous. In this paper, we study for the first time the spread of peat fires across a spatial matrix of two moisture contents (dry/wet) in the laboratory. The experiments were undertaken using an open-top insulated box (22×18×6cm) filled with milled peat. The peat was ignited at one side of the box initiating smouldering and horizontal spread. Measurements of the peak temperature inside the peat, fire duration and longwave thermal radiation from the burning samples revealed important local changes of the smouldering behaviour in response to sharp gradients in moisture content. Both, peak temperatures and radiation in wetter peat (after the moisture gradient) were sensitive to the drier moisture condition (preceding the moisture gradient). Drier peat conditions before the moisture gradient led to higher temperatures and higher radiation flux from the fire during the first 6cm of horizontal spread into a wet peat patch. The total spread distance into a wet peat patch was affected by the moisture content gradient. We predicted that in most peat moisture gradients of relevance to natural ecosystems the fire self-extinguishes within the first 10cm of horizontal spread into a wet peat patch. Spread distances of more than 10cm are limited to wet peat patches below 160% moisture content (mass of water per mass of dry peat). We found that spatial gradients of moisture content have important local effects on the horizontal spread and should be considered in field and modelling studies.

Weak interactions, omnivory and emergent food-web properties.

Empirical studies have shown that, in real ecosystems, species-interaction strengths are generally skewed in their distribution towards weak interactions. Some theoretical work also suggests that weak interactions, especially in omnivorous links, are important for the local stability of a community at equilibrium. However, the majority of theoretical studies use uniform distributions of interaction strengths to generate artificial communities for study. We investigate the effects of the underlying interaction-strength distribution upon the return time, permanence and feasibility of simple Lotka-Volterra equilibrium communities. We show that a skew towards weak interactions promotes local and global stability only when omnivory is present. It is found that skewed interaction strengths are an emergent property of stable omnivorous communities, and that this skew towards weak interactions creates a dynamic constraint maintaining omnivory. Omnivory is more likely to occur when omnivorous interactions are skewed towards weak interactions. However, a skew towards weak interactions increases the return time to equilibrium, delays the recovery of ecosystems and hence decreases the stability of a community. When no skew is imposed, the set of stable omnivorous communities shows an emergent distribution of skewed interaction strengths. Our results apply to both local and global concepts of stability and are robust to the definition of a feasible community. These results are discussed in the light of empirical data and other theoretical studies, in conjunction with their broader implications for community assembly.

Invading and expanding: range dynamics and ecological consequences of the greater white-toothed shrew (Crocidura russula) invasion in Ireland.

Establishing how invasive species impact upon pre-existing species is a fundamental question in ecology and conservation biology. The greater white-toothed shrew (Crocidura russula) is an invasive species in Ireland that was first recorded in 2007 and which, according to initial data, may be limiting the abundance/distribution of the pygmy shrew (Sorex minutus), previously Ireland's only shrew species. Because of these concerns, we undertook an intensive live-trapping survey (and used other data from live-trapping, sightings and bird of prey pellets/nest inspections collected between 2006 and 2013) to model the distribution and expansion of C. russula in Ireland and its impacts on Ireland's small mammal community. The main distribution range of C. russula was found to be approximately 7,600 km2 in 2013, with established outlier populations suggesting that the species is dispersing with human assistance within the island. The species is expanding rapidly for a small mammal, with a radial expansion rate of 5.5 km/yr overall (2008-2013), and independent estimates from live-trapping in 2012-2013 showing rates of 2.4-14.1 km/yr, 0.5-7.1 km/yr and 0-5.6 km/yr depending on the landscape features present. S. minutus is negatively associated with C. russula. S. minutus is completely absent at sites where C. russula is established and is only present at sites at the edge of and beyond the invasion range of C. russula. The speed of this invasion and the homogenous nature of the Irish landscape may mean that S. minutus has not had sufficient time to adapt to the sudden appearance of C. russula. This may mean the continued decline/disappearance of S. minutus as C. russula spreads throughout the island.

Larval transport modeling of deep-sea invertebrates can aid the search for undiscovered populations.

BACKGROUND: Many deep-sea benthic animals occur in patchy distributions separated by thousands of kilometres, yet because deep-sea habitats are remote, little is known about their larval dispersal. Our novel method simulates dispersal by combining data from the Argo array of autonomous oceanographic probes, deep-sea ecological surveys, and comparative invertebrate physiology. The predicted particle tracks allow quantitative, testable predictions about the dispersal of benthic invertebrate larvae in the south-west Pacific. PRINCIPAL FINDINGS: In a test case presented here, using non-feeding, non-swimming (lecithotrophic trochophore) larvae of polyplacophoran molluscs (chitons), we show that the likely dispersal pathways in a single generation are significantly shorter than the distances between the three known population centres in our study region. The large-scale density of chiton populations throughout our study region is potentially much greater than present survey data suggest, with intermediate 'stepping stone' populations yet to be discovered. CONCLUSIONS/SIGNIFICANCE: We present a new method that is broadly applicable to studies of the dispersal of deep-sea organisms. This test case demonstrates the power and potential applications of our new method, in generating quantitative, testable hypotheses at multiple levels to solve the mismatch between observed and expected distributions: probabilistic predictions of locations of intermediate populations, potential alternative dispersal mechanisms, and expected population genetic structure. The global Argo data have never previously been used to address benthic biology, and our method can be applied to any non-swimming larvae of the deep-sea, giving information upon dispersal corridors and population densities in habitats that remain intrinsically difficult to assess.