Archetype models upscale understanding of natural pest control response to land-use change.

Control of crop pests by shifting host plant availability and natural enemy activity at landscape scales has great potential to enhance the sustainability of agriculture. However, mainstreaming natural pest control requires improved understanding of how its benefits can be realized across a variety of agroecological contexts. Empirical studies suggest significant but highly variable responses of natural pest control to land-use change. Current ecological models are either too specific to provide insight across agroecosystems or too generic to guide management with actionable predictions. We suggest obtaining the full benefit of available empirical, theoretical, and methodological knowledge by combining trait-mediated understanding from correlative studies with the explicit representation of causal relationships achieved by mechanistic modeling. To link these frameworks, we adapt the concept of archetypes, or context-specific generalizations, from sustainability science. Similar responses of natural pest control to land-use gradients across cases that share key attributes, such as functional traits of focal organisms, indicate general processes that drive system behavior in a context-sensitive manner. Based on such observations of natural pest control, a systematic definition of archetypes can provide the basis for mechanistic models of intermediate generality that cover all major agroecosystems worldwide. Example applications demonstrate the potential for upscaling understanding and improving predictions of natural pest control, based on knowledge transfer and scientific synthesis. A broader application of this mechanistic archetype approach promises to enhance ecology's contribution to natural resource management across diverse regions and social-ecological contexts.

Growth rate mediates hidden developmental plasticity of female yellow dung fly reproductive morphology in response to environmental stressors.

Understanding how environmental variation influences even cryptic traits is important to clarify the roles of selection and developmental constraints in past evolutionary divergence and to predict future adaptation under environmental change. Female yellow dung flies (Scathophaga stercoraria) typically have three sperm storage compartments (3S), but occasionally four (4S). More spermathecae are thought to be a female adaptation facilitating sperm sorting after mating, but the phenotype is very rare in nature. We manipulated the flies' developmental environment by food restriction, pesticides, and hot temperatures to investigate the nature and extent of developmental plasticity of this trait, and whether spermatheca expression correlates with measures of performance and developmental stability, as would be expected if 4S expression is a developmental aberration. The spermathecal polymorphism of yellow dung fly females is heritable, but also highly developmentally plastic, varying strongly with rearing conditions. 4S expression is tightly linked to growth rate, and weakly positively correlated with fluctuating asymmetry of wings and legs, suggesting that the production of a fourth spermatheca could be a nonadaptive developmental aberration. However, spermathecal plasticity is opposite in the closely related and ecologically similar Scathophaga suilla, demonstrating that overexpression of spermathecae under developmental stress is not universal. At the same time, we found overall mortality costs as well as benefits of 4S pheno- and genotypes (also affecting male siblings), suggesting that a life history trade-off may potentially moderate 4S expression. We conclude that the release of cryptic genetic variation in spermatheca number in the face of strong environmental variation may expose hidden traits (here reproductive morphology) to natural selection (here under climate warming or food augmentation). Once exposed, hidden traits can potentially undergo rapid genetic assimilation, even in cases when trait changes are first triggered by random errors that destabilize developmental processes.

Heritable responses to combined effects of heat stress and ivermectin in the yellow dung fly.

In current times of global change, several sources of stress such as contaminants and high temperatures may act synergistically. The extent to which organisms persist in stressful conditions will depend on the fitness consequences of multiple simultaneously acting stressors and the genetic basis of compensatory genetic responses. Ivermectin is an antiparasitic drug used in livestock that is excreted in dung of treated cattle, causing severe negative consequences on non-target fauna. We evaluated the effect of a combination of heat stress and exposure to ivermectin in the yellow dung fly, Scathophaga stercoraria (Diptera: Scathophagidae). In a first experiment we investigated the effects of high rearing temperature on susceptibility to ivermectin, and in a second experiment we assayed flies from a latitudinal gradient to assess potential effects of local thermal adaptation on ivermectin sensitivity. The combination of heat and ivermectin synergistically reduced offspring survival, revealing severe effects of the two stressors when combined. However, latitudinal populations did not systematically vary in how ivermectin affected offspring survival, body size, development time, cold and heat tolerance. We also found very low narrow-sense heritability of ivermectin sensitivity, suggesting evolutionary constraints for responses to the combination of these stressors beyond immediate maternal or plastic effects. If the revealed patterns hold also for other invertebrates, the combination of increasing climate warming and ivermectin stress may thus have severe consequences for biodiversity. More generally, our study underlines the need for quantitative genetic analyses in understanding wildlife responses to interacting stressors that act synergistically and threat biodiversity.

Comprehensive thermal performance curves for yellow dung fly life history traits and the temperature-size-rule.

Ambient temperature strongly determines the behaviour, physiology, and life history of all organisms. The technical assessment of organismal thermal niches in form of now so-called thermal performance curves (TPC) thus has a long tradition in biological research. Nevertheless, several traits do not display the idealized, intuitive dome-shaped TPC, and in practice assessments often do not cover the entire realistic or natural temperature range of an organism. We here illustrate this by presenting comprehensive sex-specific TPCs for the major (juvenile) life history traits of yellow dung flies (Scathophaga stercoraria; Diptera: Scathophagidae). This concerns estimation of prominent biogeographic rules, such as the temperature-size-rule (TSR), the common phenomenon in ectothermic organisms that body size decreases as temperature increases. S. stercoraria shows an untypical asymptotic TPC of continuous body size increase with decreasing temperature without a peak (optimum), thus following the TSR throughout their entire thermal range (unlike several other insects presented here). Egg-to-adult mortality (our best fitness estimator) also shows no intermediate maximum. Both may relate to this fly entering pupal winter diapause below 12 °C. While development time presents a negative exponential relationship with temperature, development rate and growth rate typify the classic TPC form for this fly. The hitherto largely unexplored close relative S. suilla with an even more arctic distribution showed very similar responses, demonstrating large overlap among two ecologically similar, coexisting dung fly species, thus implying limited utility of even complete TPCs for predicting species distribution and coexistence.

Elevated temperature increases genome-wide selection on de novo mutations.

Adaptation in new environments depends on the amount of genetic variation available for evolution, and the efficacy by which natural selection discriminates among this variation. However, whether some ecological factors reveal more genetic variation, or impose stronger selection pressures than others, is typically not known. Here, we apply the enzyme kinetic theory to show that rising global temperatures are predicted to intensify natural selection throughout the genome by increasing the effects of DNA sequence variation on protein stability. We test this prediction by (i) estimating temperature-dependent fitness effects of induced mutations in seed beetles adapted to ancestral or elevated temperature, and (ii) calculate 100 paired selection estimates on mutations in benign versus stressful environments from unicellular and multicellular organisms. Environmental stress per se did not increase mean selection on de novo mutation, suggesting that the cost of adaptation does not generally increase in new ecological settings to which the organism is maladapted. However, elevated temperature increased the mean strength of selection on genome-wide polymorphism, signified by increases in both mutation load and mutational variance in fitness. These results have important implications for genetic diversity gradients and the rate and repeatability of evolution under climate change.

Evaluating a trait-based approach to compare natural enemy and pest communities in agroforestry vs. arable systems.

Diversified farming systems, for example those that incorporate agroforestry elements, have been proposed as a solution that could maintain and improve multiple ecosystem services. However, habitat diversification in and around arable fields has complex and inconsistent effects on invertebrate crop pests and their natural enemies. This hinders the development of policy recommendations to promote the adoption of such management strategies for the provision of natural pest control services. Here, for the first time, we conducted a trait-based approach to investigate the effect of farming system on plant, invertebrate herbivore, and invertebrate natural enemy communities. We then evaluated this approach by comparing the results to those generated using a traditional taxonomic approach. At each of three working farms, we sampled within an agroforestry field (a diverse farming system comprising alleys of arable crops separated by tree rows), and within a paired non-diversified area of the farm (arable control field). Each of 96 sample points was sampled between 8 and 10 times, yielding 393,318 invertebrate specimens from 344 taxonomic groups. Diet specialization or granivory, lack of a pupal stage, and wing traits in invertebrates, along with late flowering, short flowering duration, creeping habit, and perenniality in plants, were traits more strongly associated with agroforestry crop alleys than the arable control fields. We hypothesize that this is a result of reduced habitat disturbance and increased habitat complexity in the agroforestry system. Taxonomic richness and diversity were higher in the agroforestry crop alleys compared to the arable control fields, but these effects were stronger at lower trophic levels. However, functional trait diversity of natural enemies was significantly higher in the agroforestry crop alleys than the arable control fields, suggesting an improved level of biocontrol, which was not detected by traditional diversity metrics. Of eight key pest taxa, three were significantly suppressed in the agroforestry system, while two were more abundant, compared to the arable control fields. Trait-based approaches can provide a better mechanistic understanding of farming system effects on pests and their natural enemies, therefore we recommend their application and testing in future studies of diversified farming systems.

Behavior underpins the predictive power of a trait-based model of butterfly movement.

Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short-term movements.Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random-walk model of butterfly movement that incorporates relationships between wingspan and sex-specific movement behaviors.The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates.We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex- and species-specific movement behaviors.We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

The importance of including habitat-specific behaviour in models of butterfly movement.

Dispersal is a key process affecting population persistence and major factors affecting dispersal rates are the amounts, connectedness and properties of habitats in landscapes. We present new data on the butterfly Maniola jurtina in flower-rich and flower-poor habitats that demonstrates how movement and behaviour differ between sexes and habitat types, and how this effects consequent dispersal rates. Females had higher flight speeds than males, but their total time in flight was four times less. The effect of habitat type was strong for both sexes, flight speeds were ~ 2.5 × and ~ 1.7 × faster on resource-poor habitats for males and females, respectively, and flights were approximately 50% longer. With few exceptions females oviposited in the mown grass habitat, likely because growing grass offers better food for emerging caterpillars, but they foraged in the resource-rich habitat. It seems that females faced a trade-off between ovipositing without foraging in the mown grass or foraging without ovipositing where flowers were abundant. We show that taking account of habitat-dependent differences in activity, here categorised as flight or non-flight, is crucial to obtaining good fits of an individual-based model to observed movement. An important implication of this finding is that incorporating habitat-specific activity budgets is likely necessary for predicting longer-term dispersal in heterogeneous habitats, as habitat-specific behaviour substantially influences the mean (> 30% difference) and kurtosis (1.4 × difference) of dispersal kernels. The presented IBMs provide a simple method to explicitly incorporate known activity and movement rates when predicting dispersal in changing and heterogeneous landscapes.

Data on the movement behaviour of four species of grassland butterfly.

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of Maniola jurtina, Aricia agestis, Pyronia tithonus, and Melanargia galathea, recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models.

Integrating the influence of weather into mechanistic models of butterfly movement.

BACKGROUND: Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. METHODS: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5 °C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. RESULTS: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23 °C and 26 °C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. CONCLUSIONS: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum.

The Spatial and Temporal Influence of Cloud Cover on Satellite-Based Emergency Mapping of Earthquake Disasters.

The ability to rapidly access optical satellite imagery is now an intrinsic component of managing the disaster response that follows a major earthquake. These images provide synoptic data on the impacts, extent, and intensity of damage, which is essential for mitigating further losses by feeding into the response coordination. However, whilst the efficiency of the response can be hampered when cloud cover limits image availability, spatio-temporal variations in cloud cover have never been considered as part of the design of effective disaster mapping. Here we show how annual variations in cloud cover may affect our capacity to respond rapidly throughout the year and consequently contribute to overall earthquake risk. We find that on a global scale when accounting for cloud, the worst time of year for an earthquake disaster is between June and August. During these months, 40% of the global population at risk from earthquakes are obscured from optical satellite view for >3 consecutive days. Southeastern Asia is particularly strongly affected, accounting for the majority of the population at risk from earthquakes that could be obscured by cloud in every month. Our results demonstrate the importance of the timing of earthquakes in terms of our capacity to respond effectively, highlighting the need for more intelligent design of disaster response that is not overly reliant on optical satellite imagery.

Implications of existing local (mal)adaptations for ecological forecasting under environmental change.

Standing genetic variation represents a genetic load on population fitness but can also support a rapid response to short-term environmental change, and the greatest potential source of such standing genetic variation typically exists among locally adapted populations living along an environmental gradient. Here, we develop a spatially explicit simulation model to quantify the contribution of existing genetic variation arising from migration-mutation-selection-drift balance to time to extinction under environmental change. Simulations reveal that local adaptation across a species range associated with an underlying environmental gradient could extend time to extinction by nearly threefold irrespective of the rate of environmental change. The potential for preadapted alleles to increase the rate of adaptation changes the relative importance of established extinction risk factors; in particular, it reduced the importance of the breadth of environmental tolerance and it increased the relative importance of fecundity. Although migration of preadapted alleles generally increased persistence time, it decreased it at rates of environmental change close to the critical rate of change by creating a population bottleneck, which ultimately limited the rate at which de novo mutations could arise. An analysis of the extinction dynamics further revealed that one consequence of gene flow is the potential to maximize population growth rate in at least part of the species range, which is likely to have consequences for forecasting the consequences of ecological interactions. Our study shows that predictions of persistence time change fundamentally when existing local adaptations are explicitly taken into account, underscoring the need to preserve and manage genetic diversity.

Cold spot microrefugia hold the key to survival for Brazil's Critically Endangered Araucaria tree.

Brazil's Araucaria tree (Araucaria angustifolia) is an iconic living fossil and a defining element of the Atlantic Forest global biodiversity hotspot. But despite more than two millennia as a cultural icon in southern Brazil, Araucaria is on the brink of extinction, having lost 97% of its extent to 20th-century logging. Although logging is now illegal, 21st-century climate change constitutes a new-but so far unevaluated-threat to Araucaria's future survival. We use a robust ensemble modelling approach, using recently developed climate data, high-resolution topography and fine-scale vegetation maps, to predict the species' response to climate change and its implications for conservation on meso- and microclimate scales. We show that climate-only models predict the total disappearance of Araucaria's most suitable habitat by 2070, but incorporating topographic effects allows potential highland microrefugia to be identified. The legacy of 20th-century destruction is evident-more than a third of these likely holdouts have already lost their natural vegetation-and 21st-century climate change will leave just 3.5% of remnant forest and 28.4% of highland grasslands suitable for Araucaria. Existing protected areas cover only 2.5% of the surviving microrefugia for this culturally important species, and none occur in any designated indigenous territory. Our results suggest that anthropogenic climate change is likely to commit Araucaria to a second consecutive century of significant losses, but targeted interventions could help ensure its survival in the wild.

Constant strain accumulation rate between major earthquakes on the North Anatolian Fault.

Earthquakes are caused by the release of tectonic strain accumulated between events. Recent advances in satellite geodesy mean we can now measure this interseismic strain accumulation with a high degree of accuracy. But it remains unclear how to interpret short-term geodetic observations, measured over decades, when estimating the seismic hazard of faults accumulating strain over centuries. Here, we show that strain accumulation rates calculated from geodetic measurements around a major transform fault are constant for its entire 250-year interseismic period, except in the ~10 years following an earthquake. The shear strain rate history requires a weak fault zone embedded within a strong lower crust with viscosity greater than ~1020 Pa s. The results support the notion that short-term geodetic observations can directly contribute to long-term seismic hazard assessment and suggest that lower-crustal viscosities derived from postseismic studies are not representative of the lower crust at all spatial and temporal scales.

Near-field fault slip of the 2016 Vettore Mw 6.6 earthquake (Central Italy) measured using low-cost GNSS.

The temporal evolution of slip on surface ruptures during an earthquake is important for assessing fault displacement, defining seismic hazard and for predicting ground motion. However, measurements of near-field surface displacement at high temporal resolution are elusive. We present a novel record of near-field co-seismic displacement, measured with 1-second temporal resolution during the 30th October 2016 Mw 6.6 Vettore earthquake (Central Italy), using low-cost Global Navigation Satellite System (GNSS) receivers located in the footwall and hangingwall of the Mt. Vettore - Mt. Bove fault system, close to new surface ruptures. We observe a clear temporal and spatial link between our near-field record and InSAR, far-field GPS data, regional measurements from the Italian Strong Motion and National Seismic networks, and field measurements of surface ruptures. Comparison of these datasets illustrates that the observed surface ruptures are the propagation of slip from depth on a surface rupturing (i.e. capable) fault array, as a direct and immediate response to the 30th October earthquake. Large near-field displacement ceased within 6-8 seconds of the origin time, implying that shaking induced gravitational processes were not the primary driving mechanism. We demonstrate that low-cost GNSS is an accurate monitoring tool when installed as custom-made, short-baseline networks.

Quantitative genetic divergence and standing genetic (co)variance in thermal reaction norms along latitude.

Although the potential to adapt to warmer climate is constrained by genetic trade-offs, our understanding of how selection and mutation shape genetic (co)variances in thermal reaction norms is poor. Using 71 isofemale lines of the fly Sepsis punctum, originating from northern, central, and southern European climates, we tested for divergence in juvenile development rate across latitude at five experimental temperatures. To investigate effects of evolutionary history in different climates on standing genetic variation in reaction norms, we further compared genetic (co)variances between regions. Flies were reared on either high or low food resources to explore the role of energy acquisition in determining genetic trade-offs between different temperatures. Although the latter had only weak effects on the strength and sign of genetic correlations, genetic architecture differed significantly between climatic regions, implying that evolution of reaction norms proceeds via different trajectories at high latitude versus low latitude in this system. Accordingly, regional genetic architecture was correlated to region-specific differentiation. Moreover, hot development temperatures were associated with low genetic variance and stronger genetic correlations compared to cooler temperatures. We discuss the evolutionary potential of thermal reaction norms in light of their underlying genetic architectures, evolutionary histories, and the materialization of trade-offs in natural environments.

Modelling dispersal of a temperate insect in a changing climate.

We construct a novel individual-based random-walk model to assess how predicted global climate change might affect the dispersal rates of a temperate insect. Using a novel approach we obtained accurate field measurements of daily movements for individuals over time to parameterize our model. Males were found to move significantly further on average than females. Significant variation in movement was evident among individuals; the most dispersive individuals moved up to five (females) and seven (males) times as far on average as the least dispersive individuals. Mean relative daily movement of both males and females were exponentially related to maximum daily temperature recorded within the grass sward. Variability, both within and among individuals, in relative daily movement was incorporated into the model using gamma probability distributions. Resultant dispersal functions for seasonal movement are predicted to be highly leptokurtic, which agrees well with observations from the field. Predictions of the model suggest that for populations at the polewards edge of the current range an increase of 3-5 degrees C in daily maximum temperature may increase the proportion of long-distance dispersers (those characterized as comprising the top 0.1% of furthest dispersing individuals under local conditions experienced during the 1963-1990 period) by up to 70%.

Evidence for motor axon depolarization in Fabry disease.

To investigate the pathophysiology of neuropathy in Fabry disease, multiple nerve excitability properties of median motor axons in 20 patients with this disorder but without hyperkalemia were compared with 35 age-matched normal controls. In the patients, depolarizing threshold electrotonus was reduced (P < 0.0001) and superexcitability was reduced (P < 0.001), but late subexcitability was normal. These findings indicate that the axons were mildly depolarized, probably due to ischemia, and are consistent with the hypothesis that poor nerve perfusion in Fabry disease contributes to axonal damage.