Knowledge gaps and future research directions in migration ecology for the conservation of migratory songbirds

Knowledge gaps and future research directions in migration ecology for the conservation of migratory songbirds | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 26 February 2025 V1 Latest version Share on Knowledge gaps and future research directions in migration ecology for the conservation of migratory songbirds Authors : Daniel Bloche 0009-0007-4448-8553 [email protected] , Heiko Schmaljohann , and Nir Sapir 0000-0002-2477-0515 Authors Info & Affiliations https://doi.org/10.22541/au.174056619.92482562/v1 426 views 263 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract To achieve a comprehensive understanding of species ecology towards the effective conservation of migratory species, migration ecology needs to be considered because it significantly influences population dynamics. For this, it is essential to explore how species react to the complex interplay of intrinsic and extrinsic conditions to optimize their migratory journey, including landing and departure decisions. Nocturnal migratory songbirds, which often migrate alone and alternate migratory endurance flights with stopovers, provide an excellent group for studying such individual decisions. We identified five significant knowledge gaps in the migration ecology of songbirds to guide future research: 1) Inferring stopover functions from landing decisions; 2) assessing the consequences of migration distance on the decision-making process; 3) measuring how predation danger affects the decision-making process; 4) studying the consequences of habitat properties on the decision-making process in anthropogenically modified landscapes; and 5) exploring when and where bird mortality occurs during migration. To address these gaps by studying songbird decisions in flight and at stopovers, we propose novel frameworks that integrate methods applied at different scales and discuss promising future directions to stimulate research for achieving a holistic understanding of migration and advancing the conservation of threatened migratory species. Knowledge gaps and future research directions in migration ecology for the conservation of migratory songbirds Daniel A. F. Bloche * (0009-0007-4448-8553) - Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Haifa, Israel, [email protected] Heiko Schmaljohann # (0000-0002-0886-4319) - Institute of Biology and Environmental Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany, [email protected] Nir Sapir # (0000-0002-2477-0515) - Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Haifa, Israel, [email protected] * corresponding author # shared last senior authors Short Title: Knowledge gaps in songbird migration ecology Keywords: migration ecology, stopover, landing, departure, decision-making process, predation, anthropogenic effects, time and energy considerations, mortality Type of Article: Perspective Number of Words: Abstract: 195, Main text: 6399, Box 1: 209 Number of References: 198 Number of figures, tables, and text boxes: Figures: 5, Text boxes: 1 Statement of authorship All authors developed the conceptual framework of this perspective. Daniel A. F. Bloche wrote the first draft of the manuscript, and all authors contributed substantially to revisions. Data accessibility statement This perspective is based on an extensive literature review and no data was generated or used. Abstract To achieve a comprehensive understanding of species ecology towards the effective conservation of migratory species, migration ecology needs to be considered because it significantly influences population dynamics. For this, it is essential to explore how species react to the complex interplay of intrinsic and extrinsic conditions to optimize their migratory journey, including landing and departure decisions. Nocturnal migratory songbirds, which often migrate alone and alternate migratory endurance flights with stopovers, provide an excellent group for studying such individual decisions. We identified five significant knowledge gaps in the migration ecology of songbirds to guide future research: 1) Inferring stopover functions from landing decisions; 2) assessing the consequences of migration distance on the decision-making process; 3) measuring how predation danger affects the decision-making process; 4) studying the consequences of habitat properties on the decision-making process in anthropogenically modified landscapes; and 5) exploring when and where bird mortality occurs during migration. To address these gaps by studying songbird decisions in flight and at stopovers, we propose novel frameworks that integrate methods applied at different scales and discuss promising future directions to stimulate research for achieving a holistic understanding of migration and advancing the conservation of threatened migratory species. Introduction Migration evolved as an adaptation to seasonality in a variety of taxa, including birds, mammals, fish, and insects (Alerstam et al. 2003; Newton 2024b). Bird migration is particularly well developed, with a continuum of migration strategies, including partial, short-, medium- and long-distance migration across more than 10,000 kilometres (Lundberg 1988; Newton 2024b) . Since migration has a profound ecological significance on migratory populations, endogenously controlled migration programs have evolved through physiological and behavioural adaptations, to overcome the challenges of migration (Alerstam et al. 2003). For instance, time- and energy-related selection forces have probably contributed to the adaptations characterizing long-distance migrants, including morphological properties with aerodynamic consequences (Kelsey et al. 2021; Mönkkönen 1995) , migration speed optimization (Nilsson et al. 2013; Schmaljohann 2019) , and specific life-history traits, such as clutch size (Böhning-Gaese et al. 2000). Migration programs and routes are constantly developing in response to varying environmental conditions (Dufour et al. 2021; Ozarowska et al. 2016; Tøttrup et al. 2008) which, in the face of current global change, may occur at such a high pace that evolutionary adaptations are not sufficient to prevent population declines (Both et al. 2006; Drent et al. 2003; Van Gils et al. 2016; Romano et al. 2023; Studds et al. 2017). Migrants in general, and songbirds in particular, regularly alternate between migratory endurance flights and stopover periods that allow the birds to recover, rest, and fuel (Linscott & Senner 2021; Moore 2018; Schmaljohann et al. 2022) . Balancing fitness costs related to flight and stopover is a continuous trade-off (Schmaljohann et al. 2022), and migrants need to decide whether to remain in one state (flight or stopover) or change to the other state at any given time throughout the migration journey. Consequently, migrating birds need to decide whether to 1) land, i.e. interrupt the migratory endurance flight, or 2) depart, i.e. resume the migratory endurance flight. During their migratory flight, birds need to decide when and where to land, and during stopover, they must decide which night and what time of night and direction to depart (Packmor et al. 2020). These migratory trade-off decisions determine the duration of both stopover and flight (Schmaljohann et al. 2022) and hence, the overall duration of migration (Schmaljohann 2018; Schmaljohann & Both 2017) . Optimal migratory decisions evolved to minimize different possible selection pressures: the total duration of migration, energy expenditure or predation danger (Alerstam 2011; Alerstam & Lindström 1990; Hedenström 2008). This emphasizes the critical importance of understanding the decision-making processes related to the scheduling of stopover and flight periods and factors affecting them for basic and applied research. In general, the endogenous migration program and routes are shaped by intrinsic, fixed inter- and intra-specific differences, such as migration distance (Müller et al. 2016; Packmor et al. 2020; Rüppel et al. 2023b) and presence of ecological barriers like desert belts, mountain ranges and oceans for landbirds or, analogously land masses for seabirds (Alerstam et al. 2003; Chernetsov & Markovets 2022; Schmaljohann & Eikenaar 2017; Zinßmeister et al. 2022), as well as birds’ sex (Morbey & Ydenberg 2001; Tøttrup & Thorup 2008) and age (Dwyer Heise & Moore 2003; Schmaljohann et al. 2016). Yet, in concert with the endogenous migration program, dynamic intrinsic and extrinsic conditions that change along the migratory journey have critical direct (Shochat et al. 2002) and indirect (Alerstam & Lindström 1990; Schmaljohann & Dierschke 2005) fitness consequences, modifying bird decisions (Jenni & Schaub 2003; Müller et al. 2016; Fig. 1). Dynamic intrinsic conditions include, among others, fuel load (Alerstam & Lindström 1990; Schmaljohann & Eikenaar 2017), physiological stress (Hegemann et al. 2018b), hormone levels (Goymann et al. 2017), and immune state (Brust et al. 2022). Examples of dynamic extrinsic conditions are progression of the season (Eikenaar et al. 2016), weather conditions (Rüppel et al. 2023a; Shamoun-Baranes et al. 2017), competition (Kelly et al. 2002; Moore & Kerlinger 1987; Zimin et al. 2023), and predation danger (Schmaljohann & Dierschke 2005), as well as the stopover habitat type and quality (Ktitorov et al. 2008). Depending on the conditions responsible for a bird’s decision to interrupt the migratory endurance flight, there are multiple functions that the bird may require from the stopover period, with fuelling presumed to be the key function. Additional functions include physiological recovery and avoidance of adverse weather conditions (Linscott & Senner 2021; Schmaljohann et al. 2022). As nocturnal migratory songbirds mainly migrate on their own (Box 1) and alternate migratory endurance flights with stopover periods on the ground, they are an excellent group in which to study individual decisions during migration. However, five significant knowledge gaps in songbird migration ecology prevent us from fully interpreting the significance of stopover and its functions. Because most studies investigating migrant decisions have focussed on the departure process (Schmaljohann et al. 2022), we almost completely lack an understanding of the reasoning behind landing decisions, making it challenging to infer the functions required from a stopover ( Knowledge Gap 1 ). Consequently, it remains unclear whether potential mismatches between the functions required by the songbirds and the functions that stopover sites are able to provide are a significant driver of the decline in migratory populations, and particularly in long-distance migrants (Bairlein 2016). The consequences of the migration distance on bird decisions ( Knowledge Gap 2 ) are therefore critically important for migrant evolution, ecology, and conservation. Generally, long-distance migrants were found to optimize their decisions by minimizing the duration of migration, likely affecting their landing and departure decision (Müller et al. 2016; Packmor et al. 2020; Rüppel et al. 2023b). Yet, the understanding of bird decision-making processes has been hampered so far by methodological limitations, such as the confounding effects of migration distance and the crossing of wide ecological barriers, i.e. barriers longer than the typical distance of a single migratory endurance flight leg. Understanding how variation in predation danger affects bird decisions is crucial since it may have direct fitness costs (Alerstam & Lindström 1990). Nevertheless, these decisions are rarely studied ( Knowledge Gap 3 ). Analogously, selection of stopover sites with habitats that do not fulfil a required stopover function can also lead to fitness costs (Shochat et al. 2002). Yet, we only poorly understand how anthropogenically modified habitats affect bird decisions ( Knowledge Gap 4 ), hampering our ability to develop effective conservation measures along migratory flyways, where anthropogenic habitat alterations affect migratory bird populations and their fitness (Rosenberg et al. 2019; Sala et al. 2000; Studds et al. 2017). An additional and critical knowledge gap is when and where bird mortality takes place during migration ( Knowledge Gap 5 ). As mortality is generally high during migration (Newton 2024a), understanding mortality in detail, both during migratory endurance flights and during stopover periods, is essential for minimizing devastating consequences for migrant bird populations over vast geographic areas. Here, we discuss these five knowledge gaps (Fig. 1) in our understanding of the ways fixed and dynamic, intrinsic and extrinsic conditions affect the migratory decision-making process of songbirds and the consequences of these decisions. We discuss novel research frameworks that can be adapted across different migratory flyways and taxa, to advance animal migration research. Furthermore, we propose promising future directions to stimulate and inspire researchers towards gaining a deeper understanding of bird migration, which is essential for developing and applying effective conservation measures. Inferring stopover functions from landing decisions (Knowledge Gap 1) Landing decisions are understudied due to technical limitations of identifying the timing of landing events and assessing an individual’s intrinsic condition immediately after landing. Only studies that overcome these challenges may shed light on landing decisions, to understand why a specific migrant interrupts its migratory endurance flight, and consequently, infer the functions required from stopping-over (Schmaljohann et al. 2022). How to identify the timing and location of landing events Landing events can be identified using several methods, such as radar or bird tracking. When attaching transmitters or data-loggers to birds, negative effects on birds’ survival and flight performance increase with the relative load of the device (Brlík et al. 2020) and the sum of the masses of the individual bird and the device (Tomotani et al. 2019). The widely accepted maximum threshold for device load is up to 3-5% of a bird’s body mass (Casper 2009). For large birds, such as many raptors and seabirds, the relatively large GPS-transmitters that often weigh several tens of grams, provide accurate spatiotemporal information about the bird’s movements, including the timing of landing events (Jiguet et al. 2021; Shamoun-Baranes et al. 2017). For smaller birds (<25 g), such as many songbirds, multisensory geolocation, which integrates physiological and extrinsic measurements in the tracking device, offers a potential alternative (Lisovski et al. 2020; Rhyne et al. 2024) providing relatively high spatiotemporal resolution (10–60 km) with hourly location estimates using the barometric data (Nussbaumer et al. 2023; Rhyne et al. 2024). Yet, resolution depends on additional factors like the bird’s behaviour (Lisovski et al. 2012; Rhyne et al. 2024). Integrated activity tracker can further improve the precision of distinguishing flight and stopover periods (Briedis et al. 2020). Importantly, one has to be aware that archival data loggers, for GPS or multisensory geolocation, need to be retrieved after migration, which is rarely possible for studies conducted primarily at stopover sites. This limitation of archival data loggers can be addressed with automated radio-telemetry receiver stations and uniquely coded, light-weight radio-transmitters. Radio-telemetry systems, such as the Motus (Taylor et al. 2017), ATLAS (Beardsworth et al. 2022) and Marburger (Gottwald et al. 2023) networks, can track local and regional movements of even smaller songbirds (<8 g) and enable near real-time tracking at higher spatiotemporal resolution (every few seconds) than light-level geolocation. Of note, the spatial extent and density of the array of receiver stations, as well as the time settings of the burst interval, i.e., how often the transmitter emits a signal per time unit, determine the spatiotemporal properties of bird locations (Taylor et al. 2017). To study landing decisions, the songbirds must be tagged before landing, and the array of receiver stations needs to extend over a range of several hundred kilometres, which is the typical distance of a single migratory endurance flight leg in songbirds (Gómez et al. 2017). Furthermore, it needs to be sufficiently dense, i.e. one station every 10-20 km (Taylor et al. 2017), to capture the landing event. Consequently, the ability to study songbird landing with radio-telemetry is currently limited to areas where such prerequisites are fulfilled, for instance, in the north-eastern parts of North America (Marchand et al. 2020; Woodworth et al. 2015). Importantly, tracking individuals using transmitters and data loggers provides only a limited view, representing the behaviour of just a few individuals from the selected species (see below, Knowledge Gap 2). Using radar to simultaneously characterize the migratory movements of many individual birds within a large air volume would overcome this limitation. Nevertheless, this comes at the expense of having information on the properties of each individual, including its species, sex and age, as well as its intrinsic fuel loads, immune state and morphology (Schmaljohann 2020). Data from weather radars can be used to quantify and identify regional-scale patterns of migration over an area of about 100-200 km, and when using a network of radars, the scale can increase to entire continents (Buler & Dawson 2014; Van Doren & Horton 2018; Nilsson et al. 2018; Schekler et al. 2022). Recently, the large-scale modelling of bird migration based on weather radar data across Europe revealed migration waves and facilitated the identification of the timing and location of landing and departure events (Nussbaumer et al. 2021). Additionally, novel advances in the analysis of specialized “bird radars” (e.g. BirdScan MR1) now allow identification of landing events of single birds, helping to study the factors affecting these decisions (Werber & Sapir 2025). Integrating multisensory tracking devices and ringing data to study the intrinsic conditions, potentially determining the landing decisions While it is plausible to examine if landing events detected by radar or tracking resulted from changes in dynamic extrinsic conditions, such as weather (Shamoun-Baranes et al. 2017), assessing an individual’s intrinsic condition immediately after landing remains a major challenge. On-board physiological loggers in multisensory devices could be instrumental in addressing this challenge as these collect physiological measurements (e.g., heart rate or activity), while simultaneously tracking migratory movements aloft and on the ground (Briedis et al. 2020; Sapir et al. 2011). Nevertheless, there are some limitations on the use of such multisensory devices, including their heavier mass (Lisovski et al. 2018; Robinson et al. 2010). A different approach is to integrate landing data recorded by radar with the dynamic intrinsic conditions of songbirds through trapping, particularly through standardized trapping protocols (Busse & Meissner 2015; Hüppop & Hüppop 2011). Studies across different migratory flyways found significant correlations between nightly migration intensity recorded by radar and the number of songbirds ringed on the following day (Komenda-Zehnder et al. 2010; Peckford & Taylor 2008; Williams et al. 1981). Based on this relationship, we suggest that the intrinsic condition of individual birds trapped in the early mornings following radar-detected landing events likely reflect the condition of landing songbirds. Using this approach, the dynamic intrinsic condition covariates of trapped birds, i.e., their fuel load (Labocha & Hayes 2012) or oxidative status (Ferretti et al. 2020), could be identified to examine if these factors affected bird landing decisions. Inferring stopover functions Comprehensive and integrative research frameworks, as suggested above, are expected to provide novel insights regarding the intrinsic and extrinsic conditions responsible for songbirds’ landing decisions and consequently, the functions required from stopover (Schmaljohann et al. 2022). Despite the lack of previous studies on landing decisions, we can formulate testable predictions to guide future research: For example, we predict that a songbird’s landing probability increases with deteriorating weather over the course of the night, suggesting that avoidance of migration in unfavourable weather conditions is the main function of stopover (Rüppel et al. 2023a; Schmaljohann et al. 2022; Shamoun-Baranes et al. 2017). Under these conditions, we also expect that landing decisions are largely independent of the time within the night and the individuals’ fuel load (Schmaljohann & Eikenaar 2017). Analogously, we predict landing probability to be generally low on days when the weather changes to more favourable conditions, promoting birds to continue their migration (Rüppel et al. 2023a; Schmaljohann et al. 2022; Shamoun-Baranes et al. 2017). Consequently, songbirds that land under these favourable conditions likely do so only shortly before sunrise, and with relatively low fuel loads, suggesting fuelling or physiological recovery are the main functions of their stopover (Alerstam & Lindström 1990; Schmaljohann et al. 2022). These two general examples of how to identify the functions of stopover are simplifications because they do not include the complex context dependency of the decision-making process. For instance, male songbirds have a general urge to arrive early, or earlier than male competitors, to the breeding ground, a phenomenon known as protandry (Morbey & Ydenberg 2001). Therefore, their landing decisions might be less affected by specific hindering conditions, such as body condition or unfavourable weather, compared to females. This is because, in light of their evolutionary pressures, males are probably more prone to risk-taking than females (Schmaljohann et al. 2022). Assessing the consequences of migration distance on the decision-making process (Knowledge Gap 2) Long-distance migrants are currently dramatically declining (Bairlein 2016). One factor contributing to their rapid decline is likely the time constraints in their annual cycle. Their extended migration leaves less time for other stages, such as breeding and moulting, compared to short-distance migrants (Kiat et al. 2019; Wingfield 2008), making them more vulnerable to environmental changes (Both et al. 2006; Drent et al. 2003). Consequently, it is crucial to understand if migration distance affects the decision to land and depart during migration (Alerstam & Lindström 1990; Packmor et al. 2020). Notably, comparing migratory decisions across songbirds with different migration distance has been hampered so far by two major limitations in previous studies: confounding effects of migration distance and the crossing of wide ecological barriers, and low sample size in the number of species considered per migration strategy, precluding generalization. To describe these methodological limitations in the literature, we undertook a quantitative literature review, searching in two databases, Web of Science and Google Scholar, for studies from 2000 until 2024 with the following keywords in the topic: (“songbird” AND “stopover”) AND (“departure” OR “landing” OR “duration”) AND (“strategy” OR “distance” OR “short-distance” OR “medium-distance” OR “long-distance”). Using these filters, we found 20 studies comparing songbird decisions in relation to migration distance (Table S1). Most studies (15 of 20) were from the Atlantic American or Western Eurasian-African Flyways (Fig. 4), including only a few species per migration strategy (Fig. 3). Confounding effects of migration distance and the crossing of wide ecological barriers It is still unknown whether the properties of the songbirds’ decision characterized in previous studies were due to the presence of wide ecological barriers or migration distance. This is because these two factors are confounded, such that in most studies to date (15 of 20), only long-distance migrants crossed a wide ecological barrier, like the Mediterranean Sea, the Saharo-Arabian desert belt or the Gulf of Mexico (Fig. 3A) . Presumably, the existence of such wide ecological barriers presents strong selective forces on migratory traits, such as energy accumulation before departure for the cross-barrier flight (Schmaljohann & Eikenaar 2017; Zinßmeister et al. 2022), aerodynamic properties (Corman et al. 2014), and mortality during migration (Klaassen et al. 2014), in contrast to smaller ecological barriers en route , e.g. parts of the North Sea, Baltic Sea or Lake Erie. To avoid this confounding effect, we suggest focusing on sites in which long-distance and short-distance migrants can be selected that both cross the same wide ecological barrier. Such sites can be found in migration systems that have been underrepresented in previous studies, e.g. in Southern Europe and the Mediterranean, where only trans-Saharan migrants can be selected, in the Southeast of the United States, where only trans-Gulf migrants can be selected, in the Japanese islands for migrants that must cross the sea to over-winter on the mainland, or in proximity to mountain ranges of the Tibetan Plateau along the Central Asian Flyway (see Fig. 4). Alternatively, one may select sites along migratory flyways without “wide” ecological barriers (Bozó et al. 2020; Collet & Heim 2022). When studying migratory species in these suggested systems, species will only differ in their migration distance but not in the presence or absence of a wide ecological barrier en route , helping to disentangle the specific effects of migration distance and barrier crossing on the landing and departure decisions. Low sample size Previous studies comparing the behaviour of short- and long-distance migrants considered only very few species, i.e. one to six species, per migration strategy (Fig. 3B), precluding statistically sound conclusions regarding the generality of findings related to migration-distance. Consequently, future studies should include a larger number (≥6) of species from each migration strategy to allow for statistically rigorous assessments of migratory decisions that might depend on species-specific strategies; a comparative approach that accounts for shared ancestry among species should also be considered. Furthermore, it may be beneficial to consider migration distance as a continuous rather than categorical variable in the analysis. While most studies from the Eurasian-African and American Flyways use categorical classifications (e.g. Dossman et al. 2016; Packmor et al. 2020), studies from the East Asian-Australasian Flyway (Collet & Heim 2022; Heim et al. 2018; Wobker et al. 2021) consider the migration distance as a continuous variable, since the classification into distinct migration strategies is less clear in this flyway (see Box 1). Notably, additional species-specific traits, such as diurnal versus nocturnal migrants (Michalik et al. 2020), moult strategy (Kiat et al. 2019), and territoriality at the wintering grounds (Leisler et al. 1983), could influence species’ time constraints and thus may further affect songbird migratory decisions. This emphasises the need to carefully consider specific study species in the context of migration strategy. Why bird decisions are expected to vary in relation of migration distance Generally, long-distance migrants are expected to make decisions to optimize time-minimization, which is supported by their faster migration speed (Nilsson et al. 2014), and shorter stopover duration (Müller et al. 2016; Packmor et al. 2020; Rüppel et al. 2023b), compared to short-distance migrants. Therefore, long-distance migrants’ decisions are expected to be less sensitive to e.g. weather conditions (Nilsson et al. 2014; Packmor et al. 2020). Along the same lines, due to long-distance migrants’ general time-constraints, we expect fewer sex-specific differences in their timing of landing and departure. Importantly, we would like to note that the migration distance, which is currently regarded as a fixed intrinsic factor, could actually be regarded as a dynamic factor since the remaining migratory distance and possibly the migratory history of the individual might be more important for migratory decisions along the flyway (Schmaljohann et al. 2017). We suggest considering this interesting aspect in future research, to understand if migration distance is a fixed or dynamic factor. Measuring how predation danger affects the decision-making process (Knowledge Gap 3) Minimizing the risk of predation is likely a significant optimization criterion during migration (Alerstam 2011; Alerstam & Lindström 1990). Mortality due to predation results from a complex interplay of, among others, predation danger at the specific stopover site with escape performance and anti-predation behaviour of the individual bird (Lank & Ydenberg 2003). In response to predation danger, migrants may adjust their migratory pathways (Butler et al. 2003), stopover site selection (Hope et al. 2020; Lindström 1989; Sabal et al. 2021), and movement properties (Cimprich et al. 2005). Intriguingly, it is still unknown whether variation in predation danger at a stopover site, e.g. changes in the density of migrating raptors, affects songbirds’ migratory decisions, such as landing or departure. How to study the effects of predation danger To study effects of predation danger on decisions of free-flying birds, we emphasize the need to specifically select study sites with high temporal variation in predation danger. Some examples of dynamic predator pressures are Levant Sparrowhawks ( Accipiter brevipes ) with their passage peaking over only a few days in the Middle East (Shirihai et al. 2000), Chinese Sparrowhawks ( Accipiter soloensis ) and Japanese Sparrowhawks ( Accipiter gularis ) that gather at stopover sites on the Thai-Malay Peninsula, an en route land bridge, (Pierce et al. 2021), and Broad-winged Hawks ( Buteo platypterus ) that pass in dense flocks in the span of less than two weeks (Bednarz et al. 1990) during their migration through Central America (Careau et al. 2006). These natural migration phenologies create short periods of increased predation danger along flyways used by migrating songbirds, the raptors’ prey (see Fig. 4). Alternatively, experimental approaches using artificial predator-like devices that mimic predator attacks could be a feasible way to study the response of free-flying birds while controlling for the natural variation of predation danger (Storms et al. 2024). Ideally, future studies should utilize both natural and experimental variation to explore how this dynamic extrinsic condition may affect different aspects of songbirds’ stopover ecology, including departure and landing decisions. Predicted effects of predation danger Indeed, high predation danger may increase the propensity to depart or relocate to reduce mortality risks (Hope et al. 2020). Additional aspects could include reduced energy accumulation rates due to lower foraging intensity, which is an expected indirect response to predation to avoid predation (Schmaljohann & Dierschke 2005) . Furthermore, the response to predation danger is likely context dependent and may vary between short- and long-distance migrants since the latter might prioritize energy accumulation over anti-predation behaviour (McCabe & Olsen 2015). Studying the consequences of habitat properties on the decision-making process in anthropogenically modified landscapes (Knowledge Gap 4) Large-scale anthropogenic habitat alterations take place along substantial portions of migratory flyways (Sala et al. 2000), including the expansion of urban and agricultural areas, the increase of nitrogen deposition, and the introduction of pollutants and invasive species. These human-induced disturbances affect ecosystems in general, and migratory birds in particular, with massive negative impacts on their fitness and population viability (Rosenberg et al. 2019; Studds et al. 2017). Yet little is known about how migration, including behavioural decisions for landing and departing, are influenced by such changes and how these challenges may impact the successful completion of migration. Species-specific habitat-use during stopover (Bairlein 1983; Heim et al. 2018; Ktitorov et al. 2008; Moore et al. 2005; Petit 2000; Sapir et al. 2004; Woodrey 2000) suggests some processes of habitat selection prior to and during landfall. However, we lack fundamental knowledge on the consequences of altered habitat properties for songbirds’ stopover habitat selection, landing and departure decisions. Stopover habitat selection likely depends on the individual-specific required stopover function, which are often unknown (Schmaljohann et al. 2022) and hence, the crucial link between stopover functions and habitat properties remains understudied and unintegrated into conservation planning. We need to urgently fill these knowledge gaps to formulate effective transboundary conservation measures. Studying stopover habitat selection at different spatial scales As stopover habitat selection takes places at different spatial scales, addressing this knowledge gap requires using comprehensive methods at multiple scales (Fig. 5). Some songbirds may pre-select stopover sites prior to their landfall, using e.g. visual and acoustic cues (Chernetsov 2006). Such landing propensities across landscapes can be assessed on a large scale by identifying stopover sites disproportionately selected using radar-derived stopover-to-passage ratios (Cohen et al. 2020; McLaren et al. 2018). Importantly, fine-tuned habitat choices are performed through small-scale movements after landing (Chernetsov 2006; Schmaljohann & Eikenaar 2017). Radio-telemetry can generally identify the specific timing and direction of landscape-scale relocation movements and songbirds’ departure (Seewagen et al. 2010; Taylor et al. 2017). With trilateration (Tran et al. 2024) and reverse GPS methods (Beardsworth et al. 2022), the low spatial resolution of radio-telemetry may be sufficiently improved to also study small-scale habitat selection. Additionally, some studies used the variation in radio-telemetry signal strength to identify periods of activity (Aborn et al. 2004; Morbey et al. 2018). Future studies could use the variation in signal strength to identify specific stopover behaviour, e.g. foraging, exploratory flights, or resting (Schofield et al. 2018), ideally after calibration with field observations of tagged songbirds. This approach, as an alternative to using the landing decisions (described above), could help inferring stopover functions from the songbirds’ behaviour, providing novel insights on how stopover functions may relate to habitat properties. To further advance our understanding of the impacts of habitat properties, experimental approaches can study consequences of specific environmental features under controlled conditions, e.g. with habitat manipulation (Sapir et al. 2004) or translocation of individual songbirds (Cohen et al. 2012; Dayananda et al. 2021; Fig. 5). Challenges of stopover habitat selection in anthropogenically modified landscapes Songbirds’ habitat preferences and selection likely depend on required stopover functions. While migrants presumably choose food-rich habitats to fuel (Bairlein 2002; Cohen et al. 2012), they might prefer habitats that offer shelter from unfavourable weather conditions (Clipp et al. 2020; Moore et al. 1990), low predation danger (Alerstam & Lindström 1990; McCabe & Olsen 2015), or the possibility to recover from the preceding flight (Aborn et al. 2004; Maggini et al. 2020). Previous studies suggest that habitat selection of food-rich versus food-poor habitats depends on the density of songbirds stopping-over (Shochat et al. 2002) and the predation danger at the stopover site (Alerstam & Lindström 1990; McCabe & Olsen 2015). Moreover, individuals that are more sensitive to time and energy costs, such as lean songbirds stopping after crossing ecological barriers (Cohen et al. 2012), or birds with long migration distances (Alerstam & Lindström 1990), must likely select suitable habitats faster than other, less strained individuals, potentially leading to suboptimal habitat selection (Shochat et al. 2002). We predict that optimal stopover habitat selection is particularly challenging in anthropogenically modified landscapes where ongoing changes towards urbanization and agricultural intensification take place (Fig. 5). Moreover, anthropogenic pollutants, such as pesticides (Eng et al. 2019), electromagnetic noise (Engels et al. 2014), and artificial light at night (Cabrera-Cruz et al. 2018), are known to influence bird behaviour and spatial distribution leading to suboptimal habitat selection (Van Doren et al. 2017; Horton et al. 2023; McLaren et al. 2018). Nevertheless, suitable stopover habitats for songbirds may also be provided by certain anthropogenically modified habitats such as urban parks (Seewagen et al. 2010; Seewagen & Slayton 2008) and agricultural land (Blount et al. 2021; Fontanilles et al. 2024; Wenny et al. 2011; Wilcoxen et al. 2018). Habitat quality, and hence, the utilization by songbirds, seems to differ depending on the size of the habitat fragments (Matthews & Rodewald 2010) and in the cases of agricultural lands, between agricultural practices and crop types (Blount et al. 2021; Dänhardt et al. 2010). However, stopover ecology in urban habitats and the impact of farming practices on migratory songbirds is poorly documented (Dänhardt et al. 2010; Seewagen et al. 2010). Consequently, understanding whether stopover sites in anthropogenically modified landscapes are suitable to provide the required stopover functions or whether they significantly reduce the overall stopover quality are major challenges for formulating effective conservation efforts at stopover sites. Exploring when and where bird mortality occurs during migration (Knowledge Gap 5) Future migration ecology research should assess ultimate fitness costs of the landing and departure decisions, both immediate (mortality during stopover) and at a later time (mortality at later migratory stages or reduced reproductive success) (Schmaljohann et al. 2022). Here, a central knowledge gap is when and where songbird mortality takes place during migration. From mark-recapture models of songbirds (Sillett & Holmes 2002) and tracking studies of raptors (Klaassen et al. 2014; Sergio et al. 2019b) and shorebirds (Loonstra et al. 2019), we know that mortality is higher during migration compared to the other annual cycle stages. The recent review on bird mortality by Newton (2024a) indicates that this is particularly true during spring migration, for juvenile individuals, and for species that cross wide ecological barriers en route . Importantly, whether mortality during migration occurs during endurance flights or during stopover, as well as the factors affecting mortality risk, are, to the best of our knowledge, still unknown. Challenges in detecting songbird mortality during stopover Ring recoveries and tracking data have been used in previous studies to determine mortality rates (Newton 2024a). While mark-recapture models of ring birds can be a feasible method to compare mortality between different annual cycle stages (Sillett & Holmes 2002), it is impossible to differentiate between mortality events during migratory endurance flights from those during stopover periods. Tracking methods with high spatiotemporal resolution, such as GPS-tracking, allow detailed exploration of mortality events during specific periods of the annual cycle (Sergio et al. 2019b), including migratory flight and stopover periods. By taking into account tracking device failures from “true” mortality events (Sergio et al. 2019a), high-resolution tracking data can indicate mortality events (Klaassen et al. 2014) and differentiate them from relocation events (Turjeman et al. 2021; Yanco et al. 2025). However, studying the mortality of small songbirds is limited since most high-resolution tracking devices are too heavy to be attached to them (see Knowledge Gap 1; Newton 2024a). New developments of remote data download using the Global System for Mobile Communication may enable future use of lighter data loggers for mortality studies (Morganti et al. 2024; Wild et al. 2023). Nevertheless, at the current state, the receivers of this network are lacking over vast oceanic and land areas, reducing the likelihood to record mortality events during long-distance migrations (Newton 2024a). How to detect mortality events during stopover Since detecting mortality events during endurance flights is very challenging, we propose focusing on mortality during stopover periods. Automated radio-telemetry can provide a feasible solution to identify small songbirds’ mortality, as demonstrated at specific wintering sites (González et al. 2021). Specifically, strategic and dense placement of receiver stations around stopover sites could advance mortality studies (Mitchell et al. 2024). If the spatiotemporal resolution of the radio-telemetry data is high enough, e.g. using reverse GPS methods (Beardsworth et al. 2022), local mortality events at stopover sites could additionally be identified from radio signals (i.e. when the signal is stationary over a sufficiently long period). The reliability of identifying mortality events with radio-telemetry should be verified by visual monitoring of tagged individuals or later ground-search (Lees et al. 2019; McIntyre et al. 2006). Amplified mortality at stopover sites We predict that stopover periods have the highest mortality rate during migration, particularly during the initial settling phase at an unfamiliar stopover site (Chernetsov 2006). This is because suboptimal decisions during stopover may lead to mortality directly (e.g., predation) or indirectly through effects on fuelling. Nevertheless, songbirds may additionally die during the migratory flight due to orientation or navigation errors, sudden adverse weather, predation (Newton 2007), or collisions with anthropogenic structures such as wind turbines (Erickson et al. 2014), powerlines (Bernardino et al. 2018) or illuminated anthropogenic structures (Loss et al. 2015). Whether anthropogenic structures pose a particular high mortality risk while the songbirds fly low above the ground during their landing and departure, presents an important knowledge gap. To stimulate future research, we propose testable predictions, connected to the abovementioned knowledge gaps: 1) Mortality rates among individuals likely vary based on their reasons for landing, as the difficulty and consequences of fulfilling different stopover functions may differ. Fuelling, for example, can be particularly challenging at unfamiliar stopover sites (Shochat et al. 2002), whereas temporary shelters to rest and recover can be found even within hostile ecological barriers (Maggini & Bairlein 2011; Schmaljohann et al. 2007). 2) Since short-distance migrants are likely less prone to risk-taking than long-distance migrants (Alerstam & Lindström 1990), they may experience lower stopover mortality. 3) Migratory songbirds are likely more vulnerable to predation during stopover than during nocturnal endurance flight, during which they avoid many diurnal predators (Komal et al. 2017). 4) Mortality may also vary across stopover habitat types, particularly between natural and anthropogenically modified habitats (González et al. 2021). Stopover sites that fail to provide critical functions, such as fuelling (Shochat et al. 2002) or predator shelter (Lank & Ydenberg 2003), may lead to higher mortality. Future directions in stopover research To formulate and achieve effective conservation measures for mitigating further population declines in migratory species (Bairlein 2016; Gilroy et al. 2016), it is crucial to address the abovementioned knowledge gaps in migration ecology research using a full annual cycle approach. Above, we suggest future directions and testable hypotheses within and beyond the mentioned knowledge gaps, emphasizing integrative research perspectives to achieve a holistic understanding of stopover ecology and bird migration in general, thereby assisting conservation of migratory birds. Anthropogenic environmental changes, such as land-use and climate change, are major drivers of biodiversity decline in general (Jaureguiberry et al. 2022; Sala et al. 2000) and due to their effects on migratory birds, constitute an on-going and lasting risk to the viability of their populations (Both et al. 2006; Drent et al. 2003; Van Gils et al. 2016; Romano et al. 2023; Studds et al. 2017). In response to these changes, particularly those induced by climate change, migrants adapt or adjust their phenological pattern at their wintering grounds, en route , and at the breeding grounds (Dufour et al. 2021; Ozarowska et al. 2016; Tøttrup et al. 2008). However, long-distance migrants in particular have difficulty avoiding the temporal mismatch of food abundance and food requirement for their offspring, which potentially leads to population declines (Both et al. 2006; Drent et al. 2003). Furthermore, climate change and habitat destruction cause the loss of important stopover habitats, e.g. at coastal shorelines due to sea-level rise or coastal development, leading to further population declines in migratory shorebirds (Iwamura et al. 2013; Studds et al. 2017). Climate change can also increase the extent of ecological barriers, such as in the case of the Saharo-Arabian desert belt, which has expanded in recent decades (Thomas & Nigam 2018). Changes in wind patterns potentially affect route selection (Becciu et al. 2020), and extreme weather events can have strong negative impacts on the migrants’ movement, physiological state and survival. Therefore, an in-depth exploration of these possible consequences is both important and timely. To advance our understanding of bird migration in general and stopover ecology in particular, integrative approaches at various spatiotemporal scales are essential (Bairlein 2003). These could combine individual- and population-based tracking technologies at different scales (Robinson et al. 2010), for example radar and ringing data (Komenda-Zehnder et al. 2010; Peckford & Taylor 2008; Williams et al. 1981), as well as use of tracking systems with physiological sensors (Bowlin et al. 2005; Macías-Torres et al. 2022; Rattenborg et al. 2016). Furthermore, an integrative approach combining field studies with free-flying birds and indoor studies with captured birds in laboratories has been underdeveloped so far (Bairlein et al. 2015). This approach is crucial to gain insights regarding the influence of various dynamic intrinsic and extrinsic conditions (Bairlein 2003). Field and indoor experiments can substantially promote our understanding of an individual’s response to dynamic factors by manipulating specific factors such as habitat characteristics (Lehnardt & Sapir 2024; Sapir et al. 2004), predation danger (Fransson & Weber 1997; Storms et al. 2024), temperature (Klinner & Schmaljohann 2020), intrinsic body condition (Ferretti et al. 2019), or immune status (Hegemann et al. 2018b). Moreover, global habitat degradation and loss of connectivity emphasize the importance of studying entire migratory flyways and networks over the full annual cycle (Linscott & Senner 2021; Wright et al. 2018). Future research should therefore focus on scaling-up our mechanistic understanding from the level of single habitats to entire migration systems (Bairlein 2003), individuals to ecological communities (DeSimone et al. 2024), and migratory processes to the full annual cycle (Marra et al. 2018; Smith & Moore 2003). Migratory species, and especially long-distance migratory birds, are rapidly declining (Bairlein 2016; Gilroy et al. 2016; Satterfield et al. 2020), likely as a consequence of several anthropogenic drivers that cause worldwide biodiversity declines (Jaureguiberry et al. 2022; Sala et al. 2000). These declines hamper seasonal ecosystem services, like ecosystem resilience, biomass production, seed dispersal, pest control, pollination, economic benefits, cultural values, and recreation, provided by migrants across their annual cycle (Whelan et al. 2008). Addressing the abovementioned knowledge gaps is essential for better understanding migratory birds’ evolutionary adaptions to different selection forces and their response to intrinsic and extrinsic conditions. This will furthermore facilitate effective conservation measures to protect and restore migratory populations of various species across the globe. 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Avian Biol. , 2023, 1–12.Zinßmeister, D., Troupin, D. & Sapir, N. (2022). Autumn migrating passerines at a desert edge: Do birds depart for migration after reaching a threshold fuel load or vary it according to the rate of fuel deposition? Front. Ecol. Evol. , 10, 1–12.de Zwaan, D.R., Huang, A., McCallum, Q., Owen, K., Lamont, M. & Easton, W. (2022). Mass gain and stopover dynamics among migrating songbirds are linked to seasonal, environmental, and life-history effects. Ornithology , 139, 1–16. Text Boxes Box 1: Differences between major flyways The major migratory flyways connect breeding and wintering ranges within and between continents. Importantly, geographic settings create different properties with respect to environmental conditions that are encountered along the route, including the presence and extent of ecological barriers (Alerstam et al. 2003; Newton 2024b; Fig. 4). Consequently, the significance of ecological barriers varies markedly between flyways. In some flyways, such as the Eurasian-African Flyway, certain barriers extend across the entire width of possible routes, requiring specific groups of migrants, e.g. trans-Saharan migrants (Schmaljohann et al. 2007), to cross them. In contrast, along flyways like the East Asian-Australasian Flyway, barriers may be more geographically fragmented or allow for alternative routes, making it more challenging to clearly identify migrants based on whether they cross a barrier or not (Yong et al. 2021). In general, nocturnal migratory songbirds do not follow conspecifics but are rather guided by their endogenous migration program. While this is particularly true for many species of the Eurasian-African and East Asian-Australasian Flyways that do not utter flight calls (Cramp 1977), and hence are less influenced by conspecifics during active migration, American migrants commonly call during migratory flights (Larkin & Szafoni 2008) and may show a stronger collective behaviour (Flack et al. 2022). Fig. 1: Simplified migration route of short- (dashed line, e.g. Rüppell’s Warbler, Curruca ruppeli ) and long-distance (solid line, e.g. Common Redstart, Phoenicurus phoenicurus ) migrants including some potential stopover sites, indicated by circles. The diagram shows how fixed intrinsic, and dynamic intrinsic and extrinsic conditions influence the major migratory trade-off decisions of songbirds: landing (i.e. when to interrupt the migratory endurance flight) and departure (i.e. when to resume migration from a stopover). Here, we illustrate five significant knowledge gaps in migration ecology research: 1) Inferring stopover functions from landing decisions; 2) assessing the consequences of migration distance on the decision-making process; 3) measuring how predation danger affects the decision-making process; 4) studying the consequences of habitat properties on the decision-making process in anthropogenically modified landscapes; and 5) exploring when and where bird mortality occurs during migration. Fig. 2: Suggested framework to explore the reasons, i.e. intrinsic and extrinsic conditions, responsible for landing events, which is crucial for identifying the functions required from stopover. While it is plausible to examine if detected landing events resulted from changes in dynamic extrinsic conditions, such as weather, assessing the individuals’ intrinsic condition immediately after landing remains a major challenge. We suggest two integrative approaches to simultaneously identify landing events and intrinsic condition, e.g. fuel load, stress level, or migration distance.: 1) Landing events can be detected by regional-scale radar. If radar data correlates with standardized ringing data, the birds’ intrinsic conditions from morning captures can help identify factors driving landing decisions. 2) Alternatively, both landing events and intrinsic conditions can be identified on the individual-level, using multisensory tracking devices. Yet, there are still limitations for small songbirds. Fig. 3: Biases in migration studies. Histograms from the 20 studies comparing songbird decisions in relation to migration distance, found in our quantitative literature review (Table S1), illustrating two important methodological limitations: A) The number of studies in which both short- and long-distance, neither short- nor long-distance (“none”), or only long-distance migrants crossed a wide ecological barrier demonstrate the confounding effect of migration distance and barrier crossing in most studies involving migrants to date. B) The number of species studied per migration strategy, with shorter migration distance in light blue and longer migration distance in dark blue demonstrates the lack of generalizability in most studies to date. Fig. 4: Sites of previous studies comparing bird decisions between migration strategies (blue points with capital letters). Ecological barriers are shown in yellow for deserts, grey for mountain ranges and blue for oceans. Site A: depicts Kalamazoo and Long-Point, studied by Calvert et al. (2012), Dossman et a l. (2016) and VanTol et al . (2021); Site B: Iona Island and Block Island, studied by Cooper-Mullin & McWilliams (2022) and de Zwaan et al. (2022); Site C: Helgoland, the German North Sea Coast and Falsterbo, studied by Brust et al . (2023), Eikenaar et al . (2023), Hegemann et al. (2018a), Hegemann et al . (2018b), Klinner & Schmaljohann (2020), Müller et al . (2018), Packmor et al. (2020), Rüppel et al . (2023b), Schmaljohann & Klinner (2018) and Sjöberg et al . (2017); Site D: Ponza, studied by Ferretti et al . (2019) and Ferretti et al . (2020); and Site E: Muraviovka Park, studied by Bozó et al . (2020) and Collet & Heim (2022). To illustrate the confounding effect of migration distance and barrier crossing in many previous studies such that most long-distance migrants crossed a wide ecological barrier, we show simplified migration routes of the study species, in light purple for short-distance migrants and in dark purple for long-distance migrants. For study site A: routes of the American Redstart ( Setophaga ruticilla; Norris et al. 2006) and Yellow-rumped Warbler ( Setophaga coronate ; Billerman et al. 2022); and for site C: routes of the Northern Wheatear ( Oenanthe oenanthe; Schmaljohann et al. 2012) and Eurasian Blackbird ( Turdus merula; Main 2002). Study species from previous studies in which no such confounding effect was evident are shown in light green for short-distance migrants and in dark green for long-distance migrants. For study site D: routes of the Garden Warbler ( Sylvia borin; Billerman et al. 2022) and Greater Whitethroat ( Curruca communis; Briedis et al. 2025), where both species crossed a wide barrier; and for site E: routes of the Yellow-breasted Bunting ( Emberiza aureola; Heim et al. 2024) and Yellow-throated Bunting ( Emberiza elegans; Heim et al. 2023), where none of the species crossed a wide barrier. To address confounding effects, we suggest strategic sites to focus future studies (orange points with lowercase letters) and exemplary study species. Site a: an area along the Pacific American Flyway, e.g. Point Reyes, comparing the Swainson’s Thrush ( Catharus ustulatus ) and the American Robin ( Turdus migratorius ), where none of the species cross a wide barrier. Additionally, we suggest sites where both species can be specifically selected such that they both cross a wide barrier. Site b: depicts an area along the Atlantic American Flyway at the Gulf Coast, selecting two trans-Gulf migrants such as the Blackpoll Warbler ( Setophaga striata ) and the Prothonotary Warbler ( Protonotaria citrea ); site c: in Southern Europe along the Eurasian-African Flyway, e.g. Eilat, selecting two trans-Saharan migrants such as the Willow Warbler ( Phylloscopus trochilus ) and the Eastern Bonelli’s Warbler ( Phylloscopus orientalis ); site d: along the Central Asian Flyway, e.g. Dzhanybek, selecting two trans-mountain migrants, the Greenish Warbler ( Phylloscopus trochiloides ) and the Booted Warbler ( Iduna caligata ); and site e: on the Japanese Islands, e.g. Tobetsu, selecting two migrants leaving Japan before the winter such as the Eastern Yellow Wagtail ( Motacilla tschutschensis ) and the Asian Brown Flycatcher ( Muscicapa dauurica ). Suggested areas to study the effects of predation danger on bird decisions are shown with a Sparrowhawk icon inside a pink circle. These areas are characterized by high temporal variation in the density of avian predators during migration seasons, allowing exploration of how this variation affects bird decisions; see more details in Knowledge Gap 3. Fig. 5: Schematic description of our proposed framework to study the species-specific effects and consequences of anthropogenically modified stopover habitat properties on songbirds’ migratory decisions to land or depart. Comprehensive approaches (blue circles) can explore large-scale landing propensities across landscape types recorded in radar data, combined with individual tracking studies identifying arrival, relocation movements, departure, and the birds’ activity, a proxy for behaviour, which in turn may be indicative for the function of stopover. An exemplary approach to quantify birds’ activity using variation in radio-telemetry signal strength is shown in the graph, where constant signal strength indicates birds’ inactivity, i.e. resting behaviour. Integrating these comprehensive studies with habitat manipulation or translocation experiments could advance study of specific environmental features under controlled conditions and the selection of different habitat types (orange circle). This is particularly crucial in anthropogenically modified landscapes with ongoing changes and challenges for migratory birds, such as urbanization, agricultural intensification and introduction of pollutants, like electromagnetic noise and pesticide, indicated in dark yellow. Information & Authors Information Version history V1 Version 1 26 February 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords anthropogenic effects decision-making process departure landing migration ecology mortality predation stopover time and energy considerations Authors Affiliations Daniel Bloche 0009-0007-4448-8553 [email protected] University of Haifa View all articles by this author Heiko Schmaljohann Carl von Ossietzky Universitat Oldenburg View all articles by this author Nir Sapir 0000-0002-2477-0515 University of Haifa Department of Evolutionary and Environmental Biology View all articles by this author Metrics & Citations Metrics Article Usage 426 views 263 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Daniel Bloche, Heiko Schmaljohann, Nir Sapir. Knowledge gaps and future research directions in migration ecology for the conservation of migratory songbirds. Authorea . 26 February 2025. 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