Monitoring aerial insect biodiversity: a radar perspective.

In the current biodiversity crisis, populations of many species have alarmingly declined, and insects are no exception to this general trend. Biodiversity monitoring has become an essential asset to detect biodiversity change but remains patchy and challenging for organisms that are small, inconspicuous or make (nocturnal) long-distance movements. Radars are powerful remote-sensing tools that can provide detailed information on intensity, timing, altitude and spatial scale of aerial movements and might therefore be particularly suited for monitoring aerial insects and their movements. Importantly, they can contribute to several essential biodiversity variables (EBVs) within a harmonized observation system. We review existing research using small-scale biological and weather surveillance radars for insect monitoring and outline how the derived measures and quantities can contribute to the EBVs 'species population', 'species traits', 'community composition' and 'ecosystem function'. Furthermore, we synthesize how ongoing and future methodological, analytical and technological advancements will greatly expand the use of radar for insect biodiversity monitoring and beyond. Owing to their long-term and regional-to-large-scale deployment, radar-based approaches can be a powerful asset in the biodiversity monitoring toolbox whose potential has yet to be fully tapped. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Continental-scale patterns in diel flight timing of high-altitude migratory insects.

Many insects depend on high-altitude, migratory movements during part of their life cycle. The daily timing of these migratory movements is not random, e.g. many insect species show peak migratory flight activity at dawn, noon or dusk. These insects provide essential ecosystem services such as pollination but also contribute to crop damage. Quantifying the diel timing of their migratory flight and its geographical and seasonal variation, are hence key towards effective conservation and pest management. Vertical-looking radars provide continuous and automated measurements of insect migration, but large-scale application has not been possible because of limited availability of suitable devices. Here, we quantify patterns in diel flight periodicity of migratory insects between 50 and 500 m above ground level during March-October 2021 using a network of 17 vertical-looking radars across Europe. Independent of the overall daily migratory movements and location, peak migratory movements occur around noon, during crepuscular evening and occasionally the morning. Relative daily proportions of insect migration intensity and traffic during the diel phases of crepuscular-morning, day, crepuscular-evening and night remain largely equal throughout May-September and across Europe. These findings highlight, extend, and generalize previous regional-scale findings on diel migratory insect movement patterns to the whole of temperate Europe. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Micro-evolutionary response of spring migration timing in a wild seabird.

In the context of rapid climate change, phenological advance is a key adaptation for which evidence is accumulating across taxa. Among vertebrates, phenotypic plasticity is known to underlie most of this phenological change, while evidence for micro-evolution is very limited and challenging to obtain. In this study, we quantified phenotypic and genetic trends in timing of spring migration using 8,032 dates of arrival at the breeding grounds obtained from observations on 1,715 individual common terns (Sterna hirundo) monitored across 27 years, and tested whether these trends were consistent with predictions of a micro-evolutionary response to selection. We observed a strong phenotypic advance of 9.3 days in arrival date, of which c. 5% was accounted for by an advance in breeding values. The Breeder's equation and Robertson's Secondary Theorem of Selection predicted qualitatively similar evolutionary responses to selection, and these theoretical predictions were largely consistent with our estimated genetic pattern. Overall, our study provides rare evidence for micro-evolution underlying (part of) an adaptive response to climate change in the wild, and illustrates how a combination of adaptive micro-evolution and phenotypic plasticity facilitated a shift towards earlier spring migration in this free-living population of common terns.

High individual repeatability of the migratory behaviour of a long-distance migratory seabird.

BACKGROUND: Understanding the evolution of migration requires knowledge of the patterns, sources, and consequences of variation in migratory behaviour, a need exacerbated by the fact that many migratory species show rapid population declines and require knowledge-based conservation measures. We therefore need detailed knowledge on the spatial and temporal distribution of individuals across their annual cycle, and quantify how the spatial and temporal components of migratory behaviour vary within and among individuals. METHODS: We tracked 138 migratory journeys undertaken by 64 adult common terns (Sterna hirundo) from a breeding colony in northwest Germany to identify the annual spatiotemporal distribution of these birds and to evaluate the individual repeatability of eleven traits describing their migratory behaviour. RESULTS: Birds left the breeding colony early September, then moved south along the East Atlantic Flyway. Wintering areas were reached mid-September and located at the west and south coasts of West Africa as well as the coasts of Namibia and South Africa. Birds left their wintering areas late March and reached the breeding colony mid-April. The timing, total duration and total distance of migration, as well as the location of individual wintering areas, were moderately to highly repeatable within individuals (repeatability indexes: 0.36-0.75, 0.65-0.66, 0.93-0.94, and 0.98-1.00, respectively), and repeatability estimates were not strongly affected by population-level inter-annual variation in migratory behaviour. CONCLUSIONS: We found large between-individual variation in common tern annual spatiotemporal distribution and strong individual repeatability of several aspects of their migratory behaviour.

Climatic drivers of (changes in) bat migration phenology at Bracken Cave (USA).

Climate change is drastically changing the timing of biological events across the globe. Changes in the phenology of seasonal migrations between the breeding and wintering grounds have been observed across biological taxa, including birds, mammals, and insects. For birds, strong links have been shown between changes in migration phenology and changes in weather conditions at the wintering, stopover, and breeding areas. For other animal taxa, the current understanding of, and evidence for, climate (change) influences on migration still remains rather limited, mainly due to the lack of long-term phenology datasets. Bracken Cave in Texas (USA) holds one of the largest bat colonies of the world. Using weather radar data, a unique 23-year (1995-2017) long time series was recently produced of the spring and autumn migration phenology of Brazilian free-tailed bats (Tadarida brasiliensis) at Bracken Cave. Here, we analyse these migration phenology time series in combination with gridded temperature, precipitation, and wind data across Mexico and southern USA, to identify the climatic drivers of (changes in) bat migration phenology. Perhaps surprisingly, our extensive spatiotemporal search did not find temperature to influence either spring or autumn migration. Instead, spring migration phenology seems to be predominantly driven by wind conditions at likely wintering or spring stopover areas during the migration period. Autumn migration phenology, on the other hand, seems to be dominated by precipitation to the east and north-east of Bracken Cave. Long-term changes towards more frequent migration and favourable wind conditions have, furthermore, allowed spring migration to occur 16 days earlier. Our results illustrate how some of the remaining knowledge gaps on the influence of climate (change) on bat migration and abundance can be addressed using weather radar analyses.

Weather at the winter and stopover areas determines spring migration onset, progress, and advancements in Afro-Palearctic migrant birds.

Climate change causes changes in the timing of life cycle events across all trophic groups. Spring phenology has mostly advanced, but large, unexplained, variations are present between and within species. Each spring, migratory birds travel tens to tens of thousands of kilometers from their wintering to their breeding grounds. For most populations, large uncertainties remain on their exact locations outside the breeding area, and the time spent there or during migration. Assessing climate (change) effects on avian migration phenology has consequently been difficult due to spatial and temporal uncertainties in the weather potentially affecting migration timing. Here, we show for six trans-Saharan long-distance migrants that weather at the wintering and stopover grounds almost entirely (∼80%) explains interannual variation in spring migration phenology. Importantly, our spatiotemporal approach also allows for the systematic exclusion of influences at other locations and times. While increased spring temperatures did contribute strongly to the observed spring migration advancements over the 55-y study period, improvements in wind conditions, especially in the Maghreb and Mediterranean, have allowed even stronger advancements. Flexibility in spring migration timing of long-distance migrants to exogenous factors has been consistently underestimated due to mismatches in space, scale, time, and weather variable type.

Autumn bird migration phenology: A potpourri of wind, precipitation and temperature effects.

Climate change has caused a clear and univocal trend towards advancement in spring phenology. Changes in autumn phenology are much more diverse, with advancement, delays, and 'no change' all occurring frequently. For migratory birds, patterns in autumn migration phenology trends have been identified based on ecological and life-history traits. Explaining interspecific variation has nevertheless been challenging, and the underlying mechanisms have remained elusive. Radar studies on non-species-specific autumn migration intensity have repeatedly suggested that there are strong links with weather. In long-term species-specific studies, the variance in autumn migration phenology explained by weather has, nevertheless, been rather low, or a relationship was even lacking entirely. We performed a spatially explicit time window analysis of weather effects on mean autumn passage of four trans-Saharan and six intra-European passerines to gain insights into this apparent contradiction. We analysed data from standardized daily captures at the Heligoland island constant-effort site (Germany), in combination with gridded daily temperature, precipitation and wind data over a 55-year period (1960-2014), across northern Europe. Weather variables at the breeding and stopover grounds explained up to 80% of the species-specific interannual variability in autumn passage. Overall, wind conditions were most important. For intra-European migrants, wind was even twice as important as either temperature or precipitation, and the pattern also held in terms of relative contributions of each climate variable to the temporal trends in autumn phenology. For the trans-Saharan migrants, however, the pattern of relative trend contributions was completely reversed. Temperature and precipitation had strong trend contributions, while wind conditions had only a minor impact because they did not show any strong temporal trends. As such, understanding species-specific effects of climate on autumn phenology not only provides unique insights into each species' ecology but also how these effects shape the observed interspecific heterogeneity in autumn phenological trends.

The influence of weather on avian spring migration phenology: What, where and when?

Over the past decades, spring arrival and passage of most short- and medium-distance migrating birds in the Northern Hemisphere have advanced. Changes in spring temperature at the passage or arrival area have been most frequently shown to be related to these changes in spring migration phenology. In most studies, preliminary assumptions are made on both the spatial location and the specific time frame of the weather influencing spring migration phenology. We performed a spatially explicit time-window analysis of the effect of weather on mean spring passage dates of nine short- and medium-distance passerines. We analysed data from standardized daily captures at the Helgoland (Germany) constant-effort site, in combination with gridded daily temperature, precipitation and wind data from the NCEP data set over a 55-year period (1960-2014), across the whole of West Europe and North Africa. Although we allowed for a time window of any length at any location, nevertheless incorporating various measures to avoid spurious correlations, time windows at the likely wintering or spring stopover grounds were almost exclusively selected as the best predicting variables (96%-100% of identified variables). The weather variables at the wintering and stopover grounds explain up to 77% of the interannual variability in spring passage. Yet, the response of spring migration phenology to weather at the winter or stopover areas does not fully explain the observed trends. Spring migration phenology is, hence, strongly driven by weather at the wintering and stopover grounds, but additional mechanisms are needed to fully explain the advancement of spring migration. Our results also clearly show that previously illustrated correlations, or the lack thereof, between spring migration phenology and weather at the passage or arrival location are due to spatio-temporal correlations in the weather data. This spatial mismatch might have led to false conclusions, especially the further away the wintering or stopover sites are.

Challenging a 15-year-old claim: The North Atlantic Oscillation index as a predictor of spring migration phenology of birds.

Many migrant bird species that breed in the Northern Hemisphere show advancement in spring arrival dates. The North Atlantic Oscillation (NAO) index is one of the climatic variables that have been most often investigated and shown to be correlated with these changes in spring arrival. Although the NAO is often claimed to be a good predictor or even to have a marked effect on interannual changes in spring migration phenology of Northern Hemisphere breeding birds, the results on relations between spring migration phenology and NAO show a large variety, ranging from no, over weak, to a strong association. Several factors, such as geographic location, migration phase, and the NAO index time window, have been suggested to partly explain these observed differences in association. A combination of a literature meta-analysis, and a meta-analysis and sliding time window analysis of a dataset of 23 short- and long-distance migrants from the constant-effort trapping garden at Helgoland, Germany, however, paints a completely different picture. We found a statistically significant overall effect size of the NAO on spring migration phenology (coefficient = -0.14, SE = 0.054), but this on average only explains 0%-6% of the variance in spring migration phenology across all species. As such, the value and biological meaning of the NAO as a general predictor or explanatory variable for climate change effects on migration phenology of birds, seems highly questionable. We found little to no definite support for previously suggested factors, such as geographic location, migration phenology phase, or the NAO time window, to explain the heterogeneity in correlation differences. We, however, did find compelling evidence that the lack of accounting for trends in both time series has led to strongly inflated (spurious) correlations in many studies (coefficient = -0.13, SE = 0.019).