How Do Climate Change Experiments Alter Plot-Scale Climate?
To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compi...
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Published in: | Ecology letters Vol. 22; no. 4; pp. 748 - 763 |
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Main Authors: | , , , , , , , , , |
Format: | Journal Article |
Language: | English |
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Goddard Space Flight Center
Wiley
01-04-2019
Blackwell Publishing Ltd |
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Abstract | To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs.unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6° Celsius degrees (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1°Celsius degrees (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2° Celsius degrees (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design,and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses. |
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AbstractList | To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6
C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1
C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2
C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses. To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot‐scale climate data from 15 active‐warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 ∘C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 ∘C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2 ∘C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non‐temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species’ responses. To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot‐scale climate data from 15 active‐warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 ∘C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 ∘C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2 ∘C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non‐temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species’ responses. Abstract To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot‐scale climate data from 15 active‐warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 C (47% of target) on average, for infrared studies with feedback control ( n = 3) vs. by 2.2 C (80% of target) on average for infrared with constant wattage designs ( n = 2). Warming treatments produce non‐temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species’ responses. Drought sensitivity is known to affect plant species distribution. However, since every stage of plant life cyclehas its own water requirements, plant performance and productivity is largely influenced by the timing of waterstress. Variation in drought sensitivity between stages might explain recently observed changes in tree agestructure along environmental gradients as well as species-specific responses to drought, yet it has poorly beentaken into account in species distribution models (SDMs). In this paper we discuss how plant responses to wateravailability during various life stages influence species distribution and abundance. We define the role of wateravailability at the stage of gametophyte, zygote, seed and seedling and explain the nature of drought-relatedinjuries. Moreover, we review examples that illustrate how plants adjust their phenology to cope with waterstress at early stages of plant life cycle. We also discuss possible ways forward of incorporating the effect of wateravailability on different stages of the reproductive cycle into correlative and process-based plant species distributionmodels (SDMs) in order to improve the accuracy of their predictions To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs.unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6° Celsius degrees (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1°Celsius degrees (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2° Celsius degrees (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design,and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses. |
Audience | PUBLIC |
Author | Panetta, A. M. Ettinger, A. K. Johnston, M. R. Vitasse, Y. Cook, B. I. Ellison, A. M. Rollinson, C. R. Wolkovich, E. M. Chuine, I. Dukes, J. S. |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30687988$$D View this record in MEDLINE/PubMed https://hal.science/hal-02392279$$DView record in HAL |
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Keywords | Warming Experiment feedback target temperature spring phenology active-warming budburst global warming microclimate structural control direct and indirect effects soil moisture hidden treatment warming experiment Species distribution models Life cycle Species distribution Water availability Drought |
Language | English |
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Snippet | To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation.... Abstract To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and... Drought sensitivity is known to affect plant species distribution. However, since every stage of plant life cyclehas its own water requirements, plant... |
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SubjectTerms | active‐warming Biodiversity and Ecology budburst Case studies Climate change Climatic data Data retrieval Design of experiments direct and indirect effects Drying Environmental Sciences Experimental design Experiments feedback Feedback control Field tests Global Changes global warming hidden treatment Masks Meteorology And Climatology microclimate Sensitivity analysis soil moisture Soil temperature spring phenology structural control target temperature Temperature effects warming experiment |
Title | How Do Climate Change Experiments Alter Plot-Scale Climate? |
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