Evolutionary ecology of masting: mechanisms, models, and climate change

The importance of masting for ecosystem processes is well established; now we need to understand its evolutionary and physiological drivers.Synchronous interannual variation in reproduction is driven by a combination of environmental variation, weather cues, and resource dynamics. These three major...

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Veröffentlicht in:Trends in ecology & evolution (Amsterdam) 2024-09, Vol.39 (9), p.851-862
Hauptverfasser: Bogdziewicz, Michal, Kelly, Dave, Ascoli, Davide, Caignard, Thomas, Chianucci, Francesco, Crone, Elizabeth E., Fleurot, Emilie, Foest, Jessie J., Gratzer, Georg, Hagiwara, Tomika, Han, Qingmin, Journé, Valentin, Keurinck, Léa, Kondrat, Katarzyna, McClory, Ryan, LaMontagne, Jalene M., Mundo, Ignacio A., Nussbaumer, Anita, Oberklammer, Iris, Ohno, Misuzu, Pearse, Ian S., Pesendorfer, Mario B., Resente, Giulia, Satake, Akiko, Shibata, Mitsue, Snell, Rebecca S., Szymkowiak, Jakub, Touzot, Laura, Zwolak, Rafal, Zywiec, Magdalena, Hacket-Pain, Andrew J.
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container_title Trends in ecology & evolution (Amsterdam)
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creator Bogdziewicz, Michal
Kelly, Dave
Ascoli, Davide
Caignard, Thomas
Chianucci, Francesco
Crone, Elizabeth E.
Fleurot, Emilie
Foest, Jessie J.
Gratzer, Georg
Hagiwara, Tomika
Han, Qingmin
Journé, Valentin
Keurinck, Léa
Kondrat, Katarzyna
McClory, Ryan
LaMontagne, Jalene M.
Mundo, Ignacio A.
Nussbaumer, Anita
Oberklammer, Iris
Ohno, Misuzu
Pearse, Ian S.
Pesendorfer, Mario B.
Resente, Giulia
Satake, Akiko
Shibata, Mitsue
Snell, Rebecca S.
Szymkowiak, Jakub
Touzot, Laura
Zwolak, Rafal
Zywiec, Magdalena
Hacket-Pain, Andrew J.
description The importance of masting for ecosystem processes is well established; now we need to understand its evolutionary and physiological drivers.Synchronous interannual variation in reproduction is driven by a combination of environmental variation, weather cues, and resource dynamics. These three major masting drivers, which span both proximate and ultimate factors, are not mutually exclusive and likely apply in all species, with varying importance.Masting improves plant fitness via well-documented density-dependent processes, but the costs of masting remain stubbornly understudied, preventing the integration required to fully understand masting variation across species.Improved understanding of masting drivers and links between weather variation and seed production will improve conservation outcomes, ecological forecasts, and guide management under climate change. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding
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These three major masting drivers, which span both proximate and ultimate factors, are not mutually exclusive and likely apply in all species, with varying importance.Masting improves plant fitness via well-documented density-dependent processes, but the costs of masting remain stubbornly understudied, preventing the integration required to fully understand masting variation across species.Improved understanding of masting drivers and links between weather variation and seed production will improve conservation outcomes, ecological forecasts, and guide management under climate change. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. 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All rights reserved.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c462t-8110bef0dce4a64577d5afc5dd3d7e73e65b3397d9acb7ba41d79e9606aec2133</cites><orcidid>0000-0002-6777-9034 ; 0000-0001-6763-3601 ; 0000-0001-7324-7002</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0169534724001174$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38862358$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://cnrs.hal.science/hal-04778439$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Bogdziewicz, Michal</creatorcontrib><creatorcontrib>Kelly, Dave</creatorcontrib><creatorcontrib>Ascoli, Davide</creatorcontrib><creatorcontrib>Caignard, Thomas</creatorcontrib><creatorcontrib>Chianucci, Francesco</creatorcontrib><creatorcontrib>Crone, Elizabeth E.</creatorcontrib><creatorcontrib>Fleurot, Emilie</creatorcontrib><creatorcontrib>Foest, Jessie J.</creatorcontrib><creatorcontrib>Gratzer, Georg</creatorcontrib><creatorcontrib>Hagiwara, Tomika</creatorcontrib><creatorcontrib>Han, Qingmin</creatorcontrib><creatorcontrib>Journé, Valentin</creatorcontrib><creatorcontrib>Keurinck, Léa</creatorcontrib><creatorcontrib>Kondrat, Katarzyna</creatorcontrib><creatorcontrib>McClory, Ryan</creatorcontrib><creatorcontrib>LaMontagne, Jalene M.</creatorcontrib><creatorcontrib>Mundo, Ignacio A.</creatorcontrib><creatorcontrib>Nussbaumer, Anita</creatorcontrib><creatorcontrib>Oberklammer, Iris</creatorcontrib><creatorcontrib>Ohno, Misuzu</creatorcontrib><creatorcontrib>Pearse, Ian S.</creatorcontrib><creatorcontrib>Pesendorfer, Mario B.</creatorcontrib><creatorcontrib>Resente, Giulia</creatorcontrib><creatorcontrib>Satake, Akiko</creatorcontrib><creatorcontrib>Shibata, Mitsue</creatorcontrib><creatorcontrib>Snell, Rebecca S.</creatorcontrib><creatorcontrib>Szymkowiak, Jakub</creatorcontrib><creatorcontrib>Touzot, Laura</creatorcontrib><creatorcontrib>Zwolak, Rafal</creatorcontrib><creatorcontrib>Zywiec, Magdalena</creatorcontrib><creatorcontrib>Hacket-Pain, Andrew J.</creatorcontrib><title>Evolutionary ecology of masting: mechanisms, models, and climate change</title><title>Trends in ecology &amp; evolution (Amsterdam)</title><addtitle>Trends Ecol Evol</addtitle><description>The importance of masting for ecosystem processes is well established; now we need to understand its evolutionary and physiological drivers.Synchronous interannual variation in reproduction is driven by a combination of environmental variation, weather cues, and resource dynamics. 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This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. 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This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question. Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>38862358</pmid><doi>10.1016/j.tree.2024.05.006</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-6777-9034</orcidid><orcidid>https://orcid.org/0000-0001-6763-3601</orcidid><orcidid>https://orcid.org/0000-0001-7324-7002</orcidid><oa>free_for_read</oa></addata></record>
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1872-8383
1872-8383
language eng
recordid cdi_hal_primary_oai_HAL_hal_04778439v1
source Elsevier ScienceDirect Journals
subjects climate
climate change
economies of scale
environmental factors
environmental prediction
evolution
Life Sciences
masting
plant adaptation
plant demography
plant reproduction
pollination
prediction
satiety
species
weather
title Evolutionary ecology of masting: mechanisms, models, and climate change
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