Shifts in migration phenology under climate change: temperature vs. abundance effects in birds

Koleček, Jaroslav; Adamík, Peter; Reif, Jiří

doi:10.1007/s10584-020-02668-8

Cited by 44 publications

(31 citation statements)

References 69 publications

(101 reference statements)

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“…Some bird species might be able to adjust the timing of their breeding to the more rapid spring advancement 48 . This is particularly the case for residents or short-distance migrants, species with more flexible phenology than the long-distance migrants 49 . Such species may even benefit from warmer springs, as our data imply for the short-distance migrants (Fig.…”

Section: Discussionmentioning

confidence: 99%

The influence of climate variability on demographic rates of avian Afro-palearctic migrants

Telenský

Klvaňa

Jelínek

et al. 2020

Sci Rep

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Climate is an important driver of changes in animal population size, but its effect on the underlying demographic rates remains insufficiently understood. This is particularly true for avian long-distance migrants which are exposed to different climatic factors at different phases of their annual cycle. To fill this knowledge gap, we used data collected by a national-wide bird ringing scheme for eight migratory species wintering in sub-Saharan Africa and investigated the impact of climate variability on their breeding productivity and adult survival. While temperature at the breeding grounds could relate to the breeding productivity either positively (higher food availability in warmer springs) or negatively (food scarcity in warmer springs due to trophic mismatch), water availability at the non-breeding should limit the adult survival and the breeding productivity. Consistent with the prediction of the trophic mismatch hypothesis, we found that warmer springs at the breeding grounds were linked with lower breeding productivity, explaining 29% of temporal variance across all species. Higher water availability at the sub-Saharan non-breeding grounds was related to higher adult survival (18% temporal variance explained) but did not carry-over to breeding productivity. Our results show that climate variability at both breeding and non-breeding grounds shapes different demographic rates of long-distance migrants.

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Section: Discussionmentioning

confidence: 99%

The influence of climate variability on demographic rates of avian Afro-palearctic migrants

Telenský

Klvaňa

Jelínek

et al. 2020

Sci Rep

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“…The resulting shifts in species' distributions, species' interactions, and biological community assembly and structure, increase the likelihood of local and global extinctions (Raxworthy et al 2008, Pecl et al 2017, Brambilla et al 2020). To date, several studies have documented observed impacts of climate change on species' distributions, abundance, phenology, and body size (e.g., Rosenzweig et al 2008, Koleček et al 2020 or predicted future impacts of climate change on species, such as extinction risk (e.g., Thomas et al 2004, Li et al 2013. The field of conservation biogeography has presented practical methods for incorporating climate change within conservation planning and assessments to inform forward-thinking conservation management (Carvalho et al 2011, Blair et al 2012, Crossman et al 2012.…”

Section: Introductionmentioning

confidence: 99%

Species distribution modeling to inform transboundary species conservation and management under climate change: promise and pitfalls

Blair¹,

Lê²,

Xu³

2022

Frontiers of Biogeography

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Spatially explicit biogeographic models are among the most used methods in conservation biogeography, with correlative species distribution models (SDMs) being the most popular among them. SDMs can identify the potential for species' and community range shifts under climate change, and thus can inspire, inform, and guide complex and adaptive conservation management planning efforts such as collaborative transboundary conservation frameworks. However, SDMs are rarely developed collaboratively, which would be ideal for conservation applications of such models. Further, SDMs that are applied to conservation often do not follow best practices of the field, which are particularly important for applications in climate change contexts for which model extrapolation into potentially novel climates is necessary. Thus, while there is substantial promise, particularly among machine-learning based SDM approaches, there are also many pitfalls to consider when applying SDMs to conservation, and especially in the context of transboundary management under climate change. Here, we summarize these pitfalls and the key steps to mitigate them and maximize the promise of applying SDMs to facilitate transboundary conservation planning under climate change. We argue that conservation modeling capacity must be elevated among practitioners such that they can easily implement best practices when using SDMs, especially regarding: 1) avoiding model overcomplexity, 2) addressing input data bias, and 3) accounting for uncertainty in model extrapolations and projections. While our discussion centers mainly on the pitfalls and opportunities of applying the most popular correlative SDM algorithm, Maxent, our suggestions can also be generalized to a range of other SDM tools. Overall, improved training in, tools for, and implementation of best practices in biogeographic models such as SDMs hold great promise to 3 facilitate and help guide complex, transboundary collaborations for long-term planning of conservation under climate change. Highlights:• As global changes including climate change continue, we will have to increasingly work across borders to achieve biodiversity conservation goals and to do better science.• Conservation biogeography methods, especially species distribution models (SDMs), hold great promise to inform transboundary conservation under climate change.• We outline the key SDM pitfalls that are most relevant to applications of climate change and steps to avoid them, such as improving practitioner-modeler capacity to follow SDM best practices.• We argue that, especially in transboundary conservation contexts, SDMs should be collaboratively developed from the outset with all of the stakeholders for whom the model will be relevant.• Borders often exemplify complex sociopolitical contexts and histories between countries; thus, conservation scientists, practitioners, and managers, including conservation biogeographers, have an obligation to understand those contexts and know how they relate to our work and the goals of conservation.

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“…Long-distance migrants have also experienced stronger population declines over recent decades 10,11 . In contrast, shorter distance migrants seem to have higher exibility in adjusting their arrival dates, and long-term studies have shown that bird populations that match the pace of changing climate and underlying resources can even have positive population trajectories 12 .…”

Section: Introductionmentioning

confidence: 99%

Reduced Breeding Success Suggests Trophic Mismatch Despite Timely Arrival in an Alpine Songbird

Sander

Chamberlain

Mermillon

et al. 2021

Preprint

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A steady advance in the onset of spring is one of the most prominent footprints of climate warming and requires organisms, including migratory birds, to adapt their annual routines. As lower trophic levels typically adapt faster than higher trophic levels, observations of reduced fitness due to trophic mismatches are becoming more frequent, especially in long-distance migratory birds. We aimed to identify key phenological events, and quantify potential mismatches and their consequences in a migratory songbird population of the Northern wheatear (Oenanthe oenanthe) breeding at high elevations in the European Alps.We used light-level geolocators to track wheatears, and collected information on individual breeding activity and breeding success as well as environmental conditions during the reproductive season. In addition, we used citizen science data and remote sensed images to quantify longer term phenological trends.Snow melt and green-up showed an exceptionally early spring in the study region in 2020, preceded by a relatively average year in 2019. Yet, tracked individuals arrived well before the snowmelt in 2020 and clutch initiation dates across the population were earlier in 2020 compared to 2019. However, this shift lagged behind the advance in environmental conditions. While hatching success was similar in both years, fledging success and overall nest success was significantly reduced in 2020.Our results show that, despite the timely arrival at the breeding grounds, wheatears did not advance breeding activities in synchrony with environmental conditions during the exceptionally early year in 2020. The reduced fledging success suggests a trophic mismatch. However, the underlying mechanisms for hatchling mortality and nest failure remain unknown. Earlier reproductive seasons are expected to become more frequent in the future. We show that the negative effects of changing seasons in Alpine migratory birds might be similar to birds breeding at high latitudes, despite their shorter migratory distance.

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Shifts in migration phenology under climate change: temperature vs. abundance effects in birds

Cited by 44 publications

References 69 publications

The influence of climate variability on demographic rates of avian Afro-palearctic migrants

The influence of climate variability on demographic rates of avian Afro-palearctic migrants

Species distribution modeling to inform transboundary species conservation and management under climate change: promise and pitfalls

Reduced Breeding Success Suggests Trophic Mismatch Despite Timely Arrival in an Alpine Songbird

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