Spatial and habitat variation in aphid, butterfly, moth and bird phenologies over the last half century

Resolving biology's dark matter: species richness, spatiotemporal distribution, and community composition of a dark taxon

BACKGROUND

Zoology's dark matter comprises hyperdiverse, poorly known taxa that are numerically dominant but largely unstudied, even in temperate regions where charismatic taxa are well understood. Dark taxa are everywhere, but high diversity, abundance, and small size have historically stymied their study. We demonstrate how entomological dark matter can be elucidated using high-throughput DNA barcoding ("megabarcoding"). We reveal the high abundance and diversity of scuttle flies (Diptera: Phoridae) in Sweden using 31,800 specimens from 37 sites across four seasonal periods. We investigate the number of scuttle fly species in Sweden and the environmental factors driving community changes across time and space.

RESULTS

Swedish scuttle fly diversity is much higher than previously known, with 549 putative specie) detected, compared to 374 previously recorded species. Hierarchical Modelling of Species Communities reveals that scuttle fly communities are highly structured by latitude and strongly driven by climatic factors. Large dissimilarities between sites and seasons are driven by turnover rather than nestedness. Climate change is predicted to significantly affect the 47% of species that show significant responses to mean annual temperature. Results were robust regardless of whether haplotype diversity or species-proxies were used as response variables. Additionally, species-level models of common taxa adequately predict overall species richness.

CONCLUSIONS

Understanding the bulk of the diversity around us is imperative during an era of biodiversity change. We show that dark insect taxa can be efficiently characterised and surveyed with megabarcoding. Undersampling of rare taxa and choice of operational taxonomic units do not alter the main ecological inferences, making it an opportune time to tackle zoology's dark matter.

Metabarcoding dietary analysis in the insectivorous bat Nyctalusleisleri and implications for conservation

In this study, we aim to uncover diet preferences for the insectivorous bat Nyctalusleisleri (Leisler's bat, the lesser noctule) and to provide recommendations for conservation of the species, based on the analysis of prey source habitats. Using a novel guano trap, we sampled bat faeces at selected roosts in a forest in Germany and tested two mitochondrial markers (COI and 16S) and three primer pairs for the metabarcoding of bat faecal pellets. We found a total of 17 arthropod prey orders comprising 358 species in N.leisleri guano. The most diverse orders were Lepidoptera (126 species), Diptera (86 species) and Coleoptera (48 species), followed by Hemiptera (28 species), Trichoptera (16 species), Neuroptera (15 species) and Ephemeroptera (10 species), with Lepidoptera species dominating in spring and Diptera in summer. Based on the ecological requirements of the most abundant arthropod species found in the bat guano, we propose some recommendations for the conservation of N.leisleri that are relevant for other insectivorous bat species.

Predicting the seasonal flight activity of Myzus persicae, the main aphid vector of Virus Yellows in sugar beet

BACKGROUND

Virus Yellows (VY), a disease caused by several aphid-borne viruses, is a major threat to the global sugar beet production. Following the ban of neonicotinoid-based seed treatments against aphids in Europe, increased efforts are needed to monitor and forecast aphid population spread during the sugar beet growing season. In particular, predicting aphid flight seasonal activity could allow anticipation of the timing and intensity of crop colonisation and contribute to the proper implementation of management methods. Forecasts should be made early enough to assess risk, but can be updated as the season progresses to refine management. Based on a long-term suction-trap dataset gathered between 1978 and 2014, we built and evaluated a set of models to predict the flight activity features of the main VY vector, Myzus persicae, at any location in the French sugar beet production area (c. 4 × 105  ha). Flight onset dates, length of flight period and cumulative abundance of flying aphids were predicted using climatic and land-use predictors as well as geographical position.

RESULTS

Our predictions outperformed current models published in the literature. The importance of the predictor variables varied according to the predicted flight feature but winter and early spring temperature always played a major role. Forecasts based on temperature were made more accurate by adding predictors related to aphid winter reservoirs. In addition, updating the model parameters to take advantage of new weather data acquired during the season improved the flight forecast.

CONCLUSION

Our models can be used as a tool for the mitigation in sugar beet crops. © 2023 Society of Chemical Industry.

From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring

Insect monitoring has gained global public attention in recent years in the context of insect decline and biodiversity loss. Monitoring methods that can collect samples over a long period of time and independently of human influences are of particular importance. While these passive collection methods, e.g. suction traps, provide standardized and comparable data sets, the time required to analyze the large number of samples and trapped specimens is high. Another challenge is the necessary high level of taxonomic expertise required for accurate specimen processing. These factors create a bottleneck in specimen processing. In this context, machine learning, image recognition and artificial intelligence have emerged as promising tools to address the shortcomings of manual identification and quantification in the analysis of such trap catches. Aphids are important agricultural pests that pose a significant risk to several important crops and cause high economic losses through feeding damage and transmission of plant viruses. It has been shown that long-term monitoring of migrating aphids using suction traps can be used to make, adjust and improve predictions of their abundance so that the risk of plant viruses spreading through aphids can be more accurately predicted. With the increasing demand for alternatives to conventional pesticide use in crop protection, the need for predictive models is growing, e.g. as a basis for resistance development and as a measure for resistance management. In this context, advancing climate change has a strong influence on the total abundance of migrating aphids as well as on the peak occurrences of aphids within a year. Using aphids as a model organism, we demonstrate the possibilities of systematic monitoring of insect pests and the potential of future technical developments in the subsequent automated identification of individuals through to the use of case data for intelligent forecasting models. Using aphids as an example, we show the potential for systematic monitoring of insect pests through technical developments in the automated identification of individuals from static images (i.e. advances in image recognition software). We discuss the potential applications with regard to the automatic processing of insect case data and the development of intelligent prediction models.

Prediction of the Current and Future Distribution of Tomato Leafminer in China Using the MaxEnt Model

Tomato leafminer (Tuta absoluta), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. The study and prediction of the current and future suitable habitats for tomato leafminer in China can provide an important reference for the monitoring, early warning, and prevention and control of the pest. Here, tomato leafminer's potential distributions in China under the current climate and four future climate models (SSP1-26, SSP2-45, SSP3-70, and SSP5-85) were predicted using the maximum entropy (MaxEnt) model with ArcGIS software, and the accuracy of the prediction results was tested. The areas under the receiver operating characteristic curves of the models were all greater than 0.8, and the test omission rate of the model simulation results basically agreed with the theoretical omission rate, suggesting that the prediction results had satisfactory accuracy and reliability. Under the current climatic conditions, the highly suitable habitats for tomato leafminer in China are mainly distributed in most of North China, most of East China, most of South China, most of Central China, most of Southwest China, some parts of Northeast China, and only a few parts of Northwest China. Annual mean temperature is the main environmental factor limiting the distribution. The suitable habitats for tomato leafminer will shift under different future climate models: Under SSP1-26, the highly suitable habitats will spread to the north and northeast and to the southeast coastal areas; under SSP2-45, the size of highly suitable habitats will grow from the present to 2080 and shrink from 2081 to 2100; under SSP3-70, the highly suitable habitats will spread northeastwards, but the highly suitable habitats in southeast coastal areas will shrink from 2081 to 2100 and turn into moderately suitable habitats. Under SSP5-85, the highly suitable habitats will spread northeastwards and northwestwards, with the size of highly suitable habitats gradually decreasing and the size of moderately suitable habitats increasing. Different climates will lead to different distributions of suitable habitats for tomato leafminer, with annual mean temperature, isothermality, and mean diurnal range as the main environmental influences.

Species diversity, relative abundance, and distribution of avifauna in different habitats within Lewi Mountain, Awi zone, Ethiopia

Almost all habitats on the planet are home to birds, from the lowest deserts to the highest mountains. Birds have proved to be excellent indicators of biodiversity or productivity as they are easily observed and are relatively well known compared to other animals. Although bird species are distributed across the globe, habitat destruction, fragmentation, and loss have adversely affected their survival and distribution. Therefore, this study is an attempt to prepare a baseline data on avifaunal diversity with their relative abundance and species richness in different habitats within Lewi Mountain Awi zone, Ethiopia from December 2018 to October 2020, including both the wet and dry seasons. The sampling sites were stratified based on land cover features, and transect count techniques were employed. The data were summarized per season and habitat type in the excel spreadsheet throughout the study period. In this study, one-way ANOVA was used to determine the effect of habitat type on species diversity and abundance. T-tests are also use to analyze bird populations among seasons. A total of 1591 individuals, 56 bird species belonging to 29 families and 12 orders were identified during the two seasons. The Wetland habitat had the highest species diversity index (H' = 3) with high evenness index (J = 0.88) during the dry season followed by the open shrubs habitat (H' = 2.97) with the highest evenness index (J = 0.95). The settlement had the lowest species diversity (H' = 2.17) and the lowest evenness index (J = 0.8) in the same season. During the wet season, disturbed forests recorded the highest Shannon-Weiner diversity index (H' = 3.2) with the highest evenness (J = 0.92) followed by Wetland habitat (H' = 2.97) with high evenness index (J = 0.87). During dry and wet seasons, the abundance of birds' species in different habitat types did not differ significantly (F = 1.91, p = 0.193, dƒ = 3) and (F = 1.579, p = 0.199, dƒ = 3), respectively. From all studied habitats, the overall mean abundance of bird species between dry and wet seasons was significantly different (F = 3642, P ≤ 0.001, dƒ = 1). In conclusion, settlement had the lowest species diversity and the lowest evenness index in the research area for the entire season. The habitats are important to the conservation of birds, so good habitat management is required, such as minimizing agricultural expansion and overgrazing, demarcating the forest habitats for wild species only, and creating awareness among local communities.

Forecasting land-cover change effects on waterbirds in Xiamen Bay, China: Determining prospective species winners and losers

Waterbirds are vital to coastal wetland ecosystem, and play significant roles in global biodiversity maintenance, cultural and educational services, etc. Waterbirds are particularly vulnerable to environmental change, particularly land-cover change, which has severely degraded their ecological niches. Accordingly, this study developed a waterbird-habitat preference index to quantify waterbird dependence on Xiamen Bay's habitats and a subsidiary waterbird-specific habitat suitability index to predict potential effects of future land-cover change on waterbirds. Results showed that the waterbird-habitat preference index ranged from -9.8 to 18.71, indicating that habitat selection varied greatly among different waterbird species, where tidal flats were the most popular waterbird habitat. Additionally, most waterbird species showed a preference for more than one habitat, which could be indicative of their diverse ecological demands. Effects on waterbirds varied greatly among the three different land-cover scenarios, where positive benefits were predicted under the ecological protection scenario (EPS), while the greatest negative effects were observed under the development and utilization scenario (DUS). Effects also varied among different waterbirds species. Those under the current trend scenario (CTS) (e.g., Tringa brevipes and Calidris ruficollis) could be at risk for species abundance loss (i.e., losers) while others (i.e., Egretta garzetta and Saundersilarus saundersi) could benefit from increased abundance (i.e., winners). Generally, migratory and traveling birds were much more vulnerable than resident birds. Spatially, conservation priority should be given to the Dadeng Waters and those waters adjacent to it (i.e., Tongan Bay and Anhai Bay) because of the highest waterbird loss risk in these areas under a conflict between an urgent need to protect waterbird biodiversity and intense present and future land-cover development. The intent of this study is to provide a useful tool to explore land-cover effects on waterbirds in similar coastal regions, which can provide important information on protection and restoration strategies.

The Distribution Pattern and Species Richness of Scorpionflies (Mecoptera: Panorpidae)

The uneven distribution of species diversity on earth, with mountainous regions housing half of the high species diversity areas, makes mountain ecosystems vital to biodiversity conservation. The Panorpidae are ecological indicators, ideal for studying the impact of climate change on potential insect distribution. This study examines the impact of environmental factors on the distribution of the Panorpidae and analyzes how their distribution has changed over three historical periods, the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and Current. The MaxEnt model is used to predict the potential distribution area of Panorpidae based on global distribution data. The results show that precipitation and elevation are the primary factors affecting species richness, and the suitable areas for Panorpidae are distributed in southeastern North America, Europe, and southeastern Asia. Throughout the three historical periods, there was an initial increase followed by a decrease in the area of suitable habitats. During the LGM period, there was a maximum range of suitable habitats for cool-adapted insects, such as scorpionflies. Under the scenarios of global warming, the suitable habitats for Panorpidae would shrink, posing a challenge to the conservation of biodiversity. The study provides insights into the potential geographic range of Panorpidae and helps understand the impact of climate change on their distribution.

Likelihood of Extreme Early Flight of Myzus persicae (Hemiptera: Aphididae) Across the UK

Myzus persicae (Sulzer, Hemiptera: Aphididae) is a major global crop pest; it is the primary aphid vector for many damaging viruses and has developed resistance to most insecticides. In temperate regions, the risk of widespread crop infection and yield loss is heightened following warm winters, which encourage rapid population growth and early flight. Estimates of the frequency and magnitude of warm winters are, therefore, helpful for understanding and managing this risk. However, it is difficult to quantify the statistical distribution of climate events, particularly extremes, because climate observations represent just a small sample of the possible climate variations in a region. The purpose of this study was to establish a large-scale relationship between temperature and M. persicae observations across the UK and apply this to a very large ensemble of climate model simulations, which better sample the variability in climate, to quantify the current likelihood of extreme early M. persicae flight across the UK. The timing of M. persicae flight was shown to be significantly related to January-February mean temperature, where a 1°C warmer/cooler temperature relates to about 12 d earlier/later flight. Climate model simulations predict 40% likelihood of experiencing a year with unprecedented early M. persicae flight during the next decade in the UK. Results from this method can help crop managers assess the long-term viability of crops and management practices across the UK and provide early warning information for targeting pest surveillance activities on the locations and timings at highest risk of early M. persicae flight.

rGAI: An R package for fitting the generalized abundance index to seasonal count data

The generalized abundance index (GAI) provides a useful tool for estimating relative population sizes and trends of seasonal invertebrates from species' count data and offers potential for inferring which external factors may influence phenology and demography through parametric descriptions of seasonal variation. We provide an R package that extends previous software with the ability to include covariates when fitting parametric GAI models, where seasonal variation is described by either a mixture of Normal distributions or a stopover model which provides estimates of life span. The package also generalizes the models to allow any number of broods/generations in the target population within a defined season. The option to perform bootstrapping, either parametrically or nonparametrically, is also provided. The new package allows models to be far more flexible when describing seasonal variation, which may be dependent on site-specific environmental factors or consist of many broods/generations which may overlap, as demonstrated by two case studies. Our open-source software, available at https://github.com/calliste-fagard-jenkin/rGAI, makes these extensions widely and freely available, allowing the complexity of GAI models used by ecologists and applied statisticians to increase accordingly.

Differences in phenology, daily timing of activity, and associations of temperature utilization with survival in three threatened butterflies

We used observational data collected during a mark-recapture study that generated a total of 7503 captures of 6108 unique individuals representing three endangered butterfly species to quantify inter-and intraindividual variation in temperature utilization and examine how activity patterns vary according to season, time of day, and ambient temperature. The Marsh Fritillary, the Apollo, and the Large Blue differed in utilized temperatures and phenology. Their daily activity patterns responded differently to temperature, in part depending on whether they were active in the beginning, middle or end of the season, in part reflecting interindividual variation and intraindividual flexibility, and in part owing to differences in ecology, morphology, and colouration. Activity temperatures varied over the season, and the Apollo and the Large Blue were primarily active at the highest available ambient temperatures (on the warmest days and during the warmest part of the day). The Marsh Fritillary was active early in the season and decreased activity during the highest temperatures. The relationship between individual lifespan and the average temperature was qualitatively different in the three species pointing to species-specific selection. Lifespan increased with an increasing range of utilized temperatures in all species, possibly reflecting that intra-individual flexibility comes with a general survival benefit.

Urbanization extends flight phenology and leads to local adaptation of seasonal plasticity in Lepidoptera

Cities represent novel environments with altered seasonality; they are warmer, which may accelerate growth, but light pollution can also lengthen days, misleading organisms that use daylength to predict seasonal change. Using long-term observational data, we show that urban populations of a butterfly and a moth have longer flight seasons than neighboring rural populations for six Nordic city regions. Next, using laboratory experiments, we show that the induction of diapause by daylength has evolved in urban populations in the direction predicted by urban warming. We thus show that the altered seasonality of urban environments can lead to corresponding evolutionary changes in the seasonal responses of urban populations, a pattern that may be repeated in other species.

Urbanization is gaining force globally, which challenges biodiversity, and it has recently also emerged as an agent of evolutionary change. Seasonal phenology and life cycle regulation are essential processes that urbanization is likely to alter through both the urban heat island effect (UHI) and artificial light at night (ALAN). However, how UHI and ALAN affect the evolution of seasonal adaptations has received little attention. Here, we test for the urban evolution of seasonal life-history plasticity, specifically changes in the photoperiodic induction of diapause in two lepidopterans, Pieris napi (Pieridae) and Chiasmia clathrata (Geometridae). We used long-term data from standardized monitoring and citizen science observation schemes to compare yearly phenological flight curves in six cities in Finland and Sweden to those of adjacent rural populations. This analysis showed for both species that flight seasons are longer and end later in most cities, suggesting a difference in the timing of diapause induction. Then, we used common garden experiments to test whether the evolution of the photoperiodic reaction norm for diapause could explain these phenological changes for a subset of these cities. These experiments demonstrated a genetic shift for both species in urban areas toward a lower daylength threshold for direct development, consistent with predictions based on the UHI but not ALAN. The correspondence of this genetic change to the results of our larger-scale observational analysis of in situ flight phenology indicates that it may be widespread. These findings suggest that seasonal life cycle regulation evolves in urban ectotherms and may contribute to ecoevolutionary dynamics in cities.

Climate and land-use changes drive biodiversity turnover in arthropod assemblages over 150 years

Long-term studies are essential to understand the impacts of global changes on the multiple facets of biological diversity. Here, we use distribution data for over 600 species of arthropods collected over 150 years from locations across Italy and test how multiple environmental stressors (climate, land use and human population density) influenced assemblage composition and functionality. By carefully reconstructing the temporal changes in these stressors, we explicitly tested how environmental changes can determine the observed changes in taxonomic and functional diversity. We found that rapid changes in precipitation destabilize the assemblages and maximize colonization and extinction rates, especially when coupled with changes in human population density (for taxonomy) or temperature (for functionality). Higher microclimatic heterogeneity increases the stability of biodiversity by reducing taxonomic and functional loss. Finally, changes in natural habitats increased colonization, influencing taxonomic nestedness and functional replacement. The integration of long-term datasets combining distributions, climate and traits may deepen our understanding of the processes underlying biodiversity responses to global-scale drivers.

Inter-sexual and inter-generation differences in dispersal of a bivoltine butterfly

In organisms with discrete generations such as most insects, life-history traits including dispersal abilities often vary between generations. In particular, density-dependent differences in dispersal of bi- and multivoltine species may be expected because subsequent generations are usually characterized by a drastic increase in individual abundance. We investigated the inter-sexual and inter-generation differences in dispersal of a bivoltine butterfly, Lycaena helle, testing the following hypotheses: (1) male emigration is higher in spring generation, as males are prone to leave their natal habitat patches when the density of mating partners is low; (2) female emigration is higher in summer generation, when it helps to reduce intraspecific competition between offspring. The outcome of our analyses of dispersal parameters showed that females of the summer generation emigrated from their natal patches considerably more often than those of the spring generation, whereas an opposite trend was detected in males. These findings offer a novel perspective for our understanding of the advantages of voltinism for metapopulation functioning. The spring generation dispersal mainly improves the random mating opportunities favoured by the increase in male emigration. In turn, the dispersal of females of the summer generation appears the key to long-term metapopulation persistence.

Effect of dietary supplementation of Emblica officinalis fruit pomace on methane emission, ruminal fermentation, nutrient utilization, and milk production performance in buffaloes

Effects of dietary supplementation of Emblica officinalis fruit (Indian gooseberry) pomace (EFP), a waste from fruit processing plants and rich in polyphenolic compounds, were investigated for ruminal fermentation, nutrient utilization, methane production, and milk production performance in buffaloes. An in vitro experiment was conducted using 0 to 50 g/kg of EFP (six treatments) to select an optimum dose for feeding of buffaloes. Organic matter (OM) degradability, total volatile fatty acid concentration, and acetate proportion decreased, but propionate proportion increased at the higher doses (> 30 g/kg). Methane production also decreased at the higher doses (≥ 20 g/kg). In the in vivo study, ten lactating buffaloes were randomly allotted into control and EFP groups (n = 5/group). The control group was fed a total mixed ration, whereas the EFP group was fed the control ration along with EFP at 20 g/kg of dry matter (DM) intake for 120 days. Feeding of EFP to buffaloes improved milk yield (P < 0.01) and milk production efficiency (P < 0.01). Concentration of milk protein tended (P = 0.071) to increase and that of solid not fat increased (P = 0.032) due to the EFP feeding. Yields (kg/day) of milk fat (P = 0.026), solid not fat (P = 0.011), and protein (P = 0.002) were greater in the EFP group than the control group. Somatic cell count in milk decreased (P = 0.032) due to EFP feeding. Digestibility of ether extract (P < 0.001) increased and OM (P = 0.051) tended to increase by EFP feeding. Methane production (g/d), yield (g/kg DM intake or g/kg digestible organic matter intake), and intensity (g/kg milk, g/kg milk fat, or g/kg milk protein), and methane conversion rate (percentage of gross energy intake) were lower (P < 0.01) in the EFP group than the control group. For milk fatty acid (FA) profiles, total saturated FA proportion tended to be greater (P = 0.057) in the EFP group than the control group, which was due to increased (P = 0.045) proportion of total short- and medium-chain FA (C4 to C14). Feed intake, digestibility of crude protein and fiber, and total n-6, n-3, mono-unsaturated FA, poly-unsaturated FA, and long-chain FA (C18 to C24) proportions were similar between the groups. This study suggests that feeding of EFP at 20 g/kg DM intake increases milk production and decreases methane production and intensity without impacting health of buffaloes and FA profiles of milk. This is a win-win situation for sustainable and cleaner buffalo production by improving milk production and decreasing environmental burdens of greenhouse gas emission and EFP residue disposal problems.

Identifying the Drivers of Spatial Taxonomic and Functional Beta-Diversity of British Breeding Birds

Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.

Prediction of Plant Phenological Shift under Climate Change in South Korea

Information on the phenological shift of plants can be used to detect climate change and predict changes in the ecosystem. In this study, the changes in first flowering dates (FFDs) of the plum tree (Prunus mume), Korean forsythia (Forsythia koreana), Korean rosebay (Rhododendron mucronulatum), cherry tree (Prunus yedoensis), and peach tree (Prunus persica) in Korea during 1920–2019 were investigated. In addition, the changes in the climatic factors (temperature and precipitation) and their relationship with the FFDs were analyzed. The changes in the temperature and precipitation during the January–February–March period and the phenological shifts of all research species during 1920–2019 indicate that warm and dry spring weather advances the FFDs. Moreover, the temperature has a greater impact on this phenological shift than precipitation. Earlier flowering species are more likely to advance their FFDs than later flowering species. Hence, the temporal asynchrony among plant species will become worse with climate change. In addition, the FFDs in 2100 were predicted based on representative concentration pathway (RCP) scenarios. The difference between the predicted FFDs of the RCP 4.5 and RCP 6.0 for 2100 was significant; the effectiveness of greenhouse gas policies will presumably determine the degree of the plant phenological shift in the future. Furthermore, we presented the predicted FFDs for 2100.

Extreme events are more likely to affect the breeding success of lesser kestrels than average climate change

Climate change is predicted to severely impact interactions between prey, predators and habitats. In Southern Europe, within the Mediterranean climate, herbaceous vegetation achieves its maximum growth in middle spring followed by a three-month dry summer, limiting prey availability for insectivorous birds. Lesser kestrels (Falco naumanni) breed in a time-window that matches the nestling-rearing period with the peak abundance of grasshoppers and forecasted climate change may impact reproductive success through changes in prey availability and abundance. We used Normalised Difference Vegetation Index (NDVI) as a surrogate of habitat quality and prey availability to investigate the impacts of forecasted climate change and extreme climatic events on lesser kestrel breeding performance. First, using 14 years of data from 15 colonies in Southwestern Iberia, we linked fledging success and climatic variables with NDVI, and secondly, based on these relationships and according to climatic scenarios for 2050 and 2070, forecasted NDVI and fledging success. Finally, we evaluated how fledging success was influenced by drought events since 2004. Despite predicting a decrease in vegetation greenness in lesser kestrel foraging areas during spring, we found no impacts of predicted gradual rise in temperature and decline in precipitation on their fledging success. Notwithstanding, we found a decrease of 12% in offspring survival associated with drought events, suggesting that a higher frequency of droughts might, in the future, jeopardize the recent recovery of the European population. Here, we show that extreme events, such as droughts, can have more significant impacts on species than gradual climatic changes, especially in regions like the Mediterranean Basin, a biodiversity and climate change hotspot.

Using value of information to prioritize research needs for migratory bird management under climate change: a case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non-governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision-making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (i) articulating alternative hypotheses; (ii) determining the magnitude of uncertainty regarding each hypothesis; (iii) evaluating the relevance of each hypothesis to acquisition decision-making; and (iv) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high-uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management-relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Are insects declining and at what rate? An analysis of standardised, systematic catches of aphid and moth abundances across Great Britain

Although we have known anecdotally that insects have been declining in Great Britain for more than 100 years, insect declines have only been statistically estimated over the last 20 years. Estimation of the rate of those declines is still hotly debated, fuelled by a lack of standardised, systematically collected data.More than 24 million individual moths and aphids collected from 112 light traps and 25 12.2 m suction-traps, respectively, were analysed using mixed models. Our objective was to estimate the long-term trends in both groups based on annual totals recorded every year between 1969 and 2016.The models showed that two paradigms existed: Over 47 years, long-term linear trends showed that moths had declined significantly by -31%, but short-term trends indicated that there were periods of significant decline and recovery in most decades since the 1960s. Conversely, despite aphid annual totals fluctuating widely, this group was in a steady state over the long-term, with a non-significant decline of -7.6%. Sensitivity analysis revealed that moth trends were not driven by a group of abundant species, but the sign of the overall aphid trends may have been driven by three of the most abundant species.The spatial extent of moth trends suggests that they are extremely heterogeneous. Uniquely, moth declines were different among several habitat types, with robust significant declines found in coastal, urban and woodland habitats, but notably not in agricultural, parkland and scrubland habitats. Conversely, aphid trends showed spatial synchrony extending to 338 km, albeit with local variation.

Predicting climate-driven shifts in the breeding phenology of Varied Tits (Sittiparus various) in South Korean forests

Phenological shifts of plants and animals due to climate change can vary among regions and species, requiring study of local ecosystems to understand specific impacts. The reproductive timing of insectivorous songbirds in temperate forests is tightly synchronized with peak prey abundance, and thus they can be susceptible to such shift in timing. We aimed to investigate the effect of future climate change on the egg-laying phenology of the Varied Tit (Sittiparus various), which is common and widely distributed in South Korean forests. We developed the predictive model by investigating their egg-laying dates in response to spring temperatures along geographical gradients, and our model indicated that the tits lay eggs earlier when the average of daily mean and daily maximum temperatures rise. We predicted future shifts in egg-laying dates based on the most recent climate change model published by the Intergovernmental Panel on Climate Change (IPCC), under a scenario with no climate change mitigation and under a scenario with moderate mitigation. Under this outcome, this species might be unable to adapt to rapid climate change due to asynchrony with prey species during the reproductive period. If no mitigation is undertaken, our model predicts that egg-laying dates will be advanced by more than 10 days compared to the present in 83.58% of South Korea. However, even moderate mitigation will arrest this phenomenon and maintain present egg-laying dates. These results demonstrate the first quantitative assessment for the effect of warming temperatures on the phenological response of insectivorous songbirds in South Korea.