2020
DOI: 10.1126/science.aba6880
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Forest microclimate dynamics drive plant responses to warming

Abstract: Climate warming is causing a shift in biological communities in favor of warm-affinity species (i.e., thermophilization). Species responses often lag behind climate warming, but the reasons for such lags remain largely unknown. Here, we analyzed multidecadal understory microclimate dynamics in European forests and show that thermophilization and the climatic lag in forest plant communities are primarily controlled by microclimate. Increasing tree canopy cover reduces warming rates inside forests, but loss of c… Show more

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Cited by 489 publications
(474 citation statements)
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References 53 publications
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“…We re-scaled the x-axis to show the stand age by adding each consecutive census year to the age of each plot at the initial inventory (rainy season of 2009), which we set as 5 years for the early stage, 20 years for intermediate and 60 years for advanced, although we acknowledge that these ages are averages and the real age of each stand may be 1-5 years older or younger. Fitted values and 95% confidence intervals for predicted values of models were obtained using parametric bootstrapping (n = 999) within the bootMer function in the lme4 package (Bates et al, 2015) and visualized within the R package ggplot2 (Wickham, 2016). For each response variable, we calculated the marginal (m) and the conditional (c) R 2 values using the r.squaredGLMM function in the MuMIn package (Bartoń, 2018).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…We re-scaled the x-axis to show the stand age by adding each consecutive census year to the age of each plot at the initial inventory (rainy season of 2009), which we set as 5 years for the early stage, 20 years for intermediate and 60 years for advanced, although we acknowledge that these ages are averages and the real age of each stand may be 1-5 years older or younger. Fitted values and 95% confidence intervals for predicted values of models were obtained using parametric bootstrapping (n = 999) within the bootMer function in the lme4 package (Bates et al, 2015) and visualized within the R package ggplot2 (Wickham, 2016). For each response variable, we calculated the marginal (m) and the conditional (c) R 2 values using the r.squaredGLMM function in the MuMIn package (Bartoń, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…This may attenuate the effect of drought, which could help explain the generally low dry season mortality rates observed in this study. A recent long-term study in European temperate forest showed that increasing canopy cover can reduce warming rates inside forests and can decouple local interior (microclimatic) conditions from regional (macroclimatic) ones outside forests, thereby buffering against global warming (Zellweger et al, 2020). On the other hand, canopy closure may also increase the influence of competition and density-dependent processes on plant dynamics (Callaway, 1997;Bhaskar, Dawson & Balvanera, 2014;Sanaphre-Villanueva et al, 2017).…”
Section: Discussionmentioning
confidence: 99%
“…Bioclimatic data is reliably modeled throughout the Páramo range at a 1 km 2 spatial resolution, which unfortunately overlooks micro-environmental drivers of the local-scale genetic adaptation (De La Harpe et al, 2017;Leroy et al, 2020). This is of particular importance at mountain/alpine ecosystems (Ramírez et al, 2014;Cortés and Wheeler, 2018), where microhabitats may serve as refugia (Zellweger et al, 2020), like across the treeline due to active landform processes (Bueno and Llambí, 2015;Arzac et al, 2019;Gentili et al, 2020). Populations may rely on specific smallscale habitat attributes that are likely to be overlooked by SDMs (Sinclair et al, 2010), such as topographic, geomorphic, and edaphic features, as well as the distribution of other taxae.g., competitors and facilitators (Yackulc et al, 2015).…”
Section: Climate Change May Constrain the Rapid Diversification Of Thmentioning
confidence: 99%
“…Even though hybrids could occupy intermediate niches, persistence of populations in alpine environments that face climate change is regarded as mostly mediated by local-scale (i.e., microhabitat) variation (Cortés et al, 2014;Cortés and Wheeler, 2018). For example, environmental heterogeneity may provide new suitable locations for migrants within only a few meters of their current locations (Scherrer and Körner, 2011), driving in this way plant responses to warming (Zellweger et al, 2020). More localized environmental data must then be gathered (Zellweger et al, 2019), since current climate repositories lack the resolution needed to describe the microhabitat heterogeneity.…”
Section: Perspectivesmentioning
confidence: 99%
“…Canopy closure may protect the understory vegetation from heat, and the microclimate under the canopy may be a more important driver for understory species dynamics than the underlying macroclimate (Zellweger et al 2020). This suggests that the common temperature data measured from the meteorological stations (at about a height of 2 m, relatively open surroundings) are not the best possible data to be used when modeling or predicting the effects of climate change on understory vegetation.…”
Section: Northern Boreal Forest Vegetation In the Future (Q4)mentioning
confidence: 99%