Legacies of past climate conditions and historical management govern forest productivity and tree growth. Understanding how these processes interact and the timescales over which they influence tree growth is critical to assess forest vulnerability to climate change. Yet, few studies address this issue, likely because integrated long-term records of both growth and forest management are uncommon. We applied the stochastic antecedent modelling (SAM) framework to annual tree-ring widths from mixed forests to recover the ecological memory of tree growth. We quantified the effects of antecedent temperature and precipitation up to 4 years preceding the year of ring formation and integrated management effects with records of harvesting intensity from historical forest management archives. The SAM approach uncovered important time periods most influential to growth, typically the warmer and drier months or seasons, but variation among species and sites emerged. Silver fir responded primarily to past climate conditions (25–50 months prior to the year of ring formation), while European beech and Scots pine responded mostly to climate conditions during the year of ring formation and the previous year, although these responses varied among sites. Past management and climate interacted in such a way that harvesting promoted growth in young silver fir under wet and warm conditions and in old European beech under drier and cooler conditions. Our study shows that the ecological memory associated with climate legacies and historical forest management is species-specific and context-dependent, suggesting that both aspects are needed to properly evaluate forest functioning under climate change.
Inter-annual climate variability (hereafter climate variability) is increasing in many forested regions due to climate change. This variability could have larger near-term impacts on forests than decadal shifts in mean climate, but how forests will respond remains poorly resolved, particularly at broad scales. Individual trees, and even forest communities, often have traits and ecological strategies—the legacies of exposure to past variable conditions—that confer tolerance to subsequent climate variability. However, whether local legacies also shape global forest responses is unknown. Our objective was to assess how past and current climate variability influences global forest productivity. We hypothesized that forests exposed to large climate variability in the past would better tolerate current climate variability than forests for which past climate was relatively stable. We used historical (1950–1969) and contemporary (2000–2019) temperature, precipitation, and vapor pressure deficit (VPD) and the remotely sensed enhanced vegetation index (EVI) to quantify how historical and contemporary climate variability relate to patterns of contemporary forest productivity. Consistent with our hypothesis, forests exposed to large temperature variability in the past were more tolerant of contemporary temperature variability than forests where past temperatures were less variable. Forests were 19-fold times less sensitive to contemporary temperature variability where historical inter-annual temperature variability was 0.66 °C (two standard deviations) greater than the global average historical temperature variability. We also found that larger increases in temperature variability between the two study periods often eroded the tolerance conferred by the legacy effects of historical temperature variability. However, the hypothesis was not supported in the case of precipitation and VPD variability, potentially due to physiological tradeoffs inherent in how trees cope with dry conditions. We conclude that the sensitivity of forest productivity to imminent increases in temperature variability may be partially predictable based on the legacies of past conditions.
more » « less- NSF-PAR ID:
- 10370421
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research: Ecology
- Volume:
- 1
- Issue:
- 1
- ISSN:
- 2752-664X
- Page Range / eLocation ID:
- Article No. 011001
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Tree rings provide an invaluable long‐term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree‐ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3‐month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3‐month seasonal windows), with concave‐down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.
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Abstract Understanding the influences of global climate change on soil microbial communities is essential in evaluating the terrestrial biosphere's feedback to this alarming anthropogenic disturbance. However, little is known about how intra‐site historical climate variability can mediate the influences of current climate differences on community dissimilarity and assembly. To fill this gap, we examined and disentangled the interactive effects of historical climate variability and current climate differences on the soil bacterial community dissimilarity and stochasticity of community assembly among 143 sites from 28 forests across eastern China. We hypothesize that the relative importance of stochasticity and community dissimilarity are related to historical climate variability and that an increasing sum of intra‐site historical variability enhances stochasticity while reduces dissimilarity between two communities. To test our hypothesis, we statistically controlled for covariates between sites including differences in soil chemistry, plant diversity, spatial distance, and seasonal climate variations at annual timescales. We observed that an increase in inter‐site current climate differences led to a reduced impact of stochasticity in community assembly and a pronounced divergence between communities. In stark contrast, when communities were subjected to a high level of intra‐site historical climate fluctuation, the observed impact incurred from current climate differences was substantially weakened. Moreover, the influence of increased historical variability was consistent along the gradient of current temperature differences between sites. However, effects induced by historical fluctuation in precipitation were disproportional and only evident when small inter‐site differences were observed. Consequently, if the prior climate variability is ignored, especially regarding environmental factors like temperature, we assert that the influence current climate differentiation has on regulating community dissimilarity and assembly stochasticity will be underestimated. Together, our findings highlight the importance and need of explicitly controlling the mean and the historical variability of climate factors for the next “generation” of climate change experiments to come.
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Abstract Aim Previous work demonstrated the global variability of synchrony in tree growth within populations, that is, the covariance of the year‐to‐year variability in growth of individual neighbouring trees. However, there is a lack of knowledge about the causes of this variability and its trajectories through time. Here, we examine whether climate can explain variation in within‐population synchrony (WPS) across space but also through time and we develop models capable of explaining this variation. These models can be applied to the global tree cover under current and future climate change scenarios.
Location Global.
Time period 1901–2012.
Major taxa studied Trees.
Methods We estimated WPS values from a global tree‐ring width database consisting of annual growth increment measurements from multiple trees at 3,579 sites. We used generalized linear mixed effects models to infer the drivers of WPS variability and temporal trends of global WPS. We then predicted WPS values across the global extent of tree cover. Finally, we applied our model to predict future WPS based on the RCP 8.5 (2045–2065 period) emission scenario.
Results Areas with the highest WPS are characterized by a combination of environments with both high mean annual temperature (>10°C) and low precipitation (<300 mm). Average WPS across all temperate forests has decreased historically and will continue to decrease. Potential implications of these patterns include changes in forest dynamics, such as higher tree growth and productivity and an increase in carbon sequestration. In contrast, the WPS of tropical forests of Central and South America will increase in the near future owing to reduced annual precipitation.
Main conclusions Climate explains WPS variability in space and time. We suggest that WPS might have value as an integrative ecological measure of the level of environmental stress to which forests are subjected and therefore holds potential for diagnosing effects of global climate change on tree growth.
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Abstract Determining the drivers of shifting forest disturbance rates remains a pressing global change issue. Large‐scale forest dynamics are commonly assumed to be climate driven, but appropriately scaled disturbance histories are rarely available to assess how disturbance legacies alter subsequent disturbance rates and the climate sensitivity of disturbance. We compiled multiple tree ring‐based disturbance histories from primary
Picea abies forest fragments distributed throughout five European landscapes spanning the Bohemian Forest and the Carpathian Mountains. The regional chronology includes 11,595 tree cores, with ring dates spanning the years 1750–2000, collected from 560 inventory plots in 37 stands distributed across a 1,000 km geographic gradient, amounting to the largest disturbance chronology yet constructed in Europe. Decadal disturbance rates varied significantly through time and declined after 1920, resulting in widespread increases in canopy tree age. Approximately 75% of current canopy area recruited prior to 1900. Long‐term disturbance patterns were compared to an historical drought reconstruction, and further linked to spatial variation in stand structure and contemporary disturbance patterns derived from LANDSAT imagery. Historically, decadal Palmer drought severity index minima corresponded to higher rates of canopy removal. The severity of contemporary disturbances increased with each stand's estimated time since last major disturbance, increased with mean diameter, and declined with increasing within‐stand structural variability. Reconstructed spatial patterns suggest that high small‐scale structural variability has historically acted to reduce large‐scale susceptibility and climate sensitivity of disturbance. Reduced disturbance rates since 1920, a potential legacy of high 19th century disturbance rates, have contributed to a recent region‐wide increase in disturbance susceptibility. Increasingly common high‐severity disturbances throughout primaryPicea forests of Central Europe should be reinterpreted in light of both legacy effects (resulting in increased susceptibility) and climate change (resulting in increased exposure to extreme events).
