{"title":"The effect of climate change on the health and productivity of Australia’s temperate eucalypt forests","authors":"T. Wardlaw","doi":"10.1080/00049158.2021.2013639","DOIUrl":null,"url":null,"abstract":"The release of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC 2021) is a galvanising moment globally for concerted action to stem climate change. The report provides stronger evidence of previously identified changes to Earth systems as a result of anthropogenic greenhouse-gas emissions. If current trends for rising emissions continue beyond mid-century, the global mean temperature will be 3.3–5.7 degrees warmer by the end of this century compared with the period 1850–1900. Warming across Australia is predicted to be higher than the global average (Australian Academy of Science 2021). The Sixth Assessment Report (IPCC 2021) also gives greater prominence to extreme events, particularly heatwaves, fire weather and compound events (heatwaves coupled with droughts). Although temperature increases drive most of the extreme events that will affect temperate eucalypt forests, a trend of increasing aridity across southern Australia due to climate change (CSIRO and Bureau of Meteorology 2020) has amplified these compound events (Matusick et al. 2018) and fire risk (van Oldenborgh et al. 2021). Despite more confident predictions of future climate states under different emissions scenarios, the impacts of climate change on the productivity of temperate eucalypt forest remain uncertain. This is because of a lack of understanding about how changing temperature and moisture conditions will affect tree establishment, growth rates and mortality due to extreme events and disturbances (e.g. fire, pests and diseases). There is also considerable uncertainty about the effects of increasing atmospheric concentrations of carbon dioxide (CO2). Roxburgh et al. (2004) concluded that existing simulation models used in Australia have insufficient capability to predict the consequences of climate change for Australia’s forests. Haverd et al. (2013) made considerable advances in reducing the uncertainty of continent-scale predictions of net primary productivity by using multiple observation types to constrain BIOS2 model predictions. Two models, CABALA and 3-PG, have been used extensively in Australia to predict forest productivity under simulated future climates (Pinkard, Bruce et al. 2014; Battaglia and Bruce 2017; Wang et al. 2021). Calibration studies show that both 3-PG (Potithep and Yasuoka 2011) and CABALA (Battaglia et al. 2004; Battaglia et al. 2011) can accurately predict forest productivity when growing conditions can be defined, although 3-PG underpredicts productivity in temperate eucalypt forests, particularly the most productive of these (Haverd et al. 2013; Volkova et al. 2015). Predictions of productivity in future climates under different emissions scenarios made using CABALA and 3-PG vary widely, however, because of uncertainties surrounding climate projections, responses to higher concentrations of atmospheric CO2 (Battaglia and Bruce 2017; Wang et al. 2021) and mortality from drought (Pinkard, Bruce et al. 2014). Models need to evolve to enable more confident predictions of productivity in Australian temperate eucalypt forests under future climate scenarios. Our understanding of the key environmental drivers of productivity in eucalypt native forests has progressed in the last decade. Using independent methods, growth rates of eucalypt forests have been found to have a consistent relationship with temperature – a convex parabola with the vertex corresponding to the temperature optimum at which maximum growth occurs. Bowman et al. (2014), using an inventory approach, found an optimum (mean annual) temperature for diameter growth rates of 11°C in eucalypt forests growing on mesic sites in temperate and subtropical regions of Australia. Using data from a network of eddy covariance towers in eucalypt forests and woodlands, Bennett et al. (2021) found that temperature optima for gross primary productivity (GPP) in southern Australia ranged between 15°C and 23°C and were directly related to the historical climate of the site. There is great potential to make more use of Australia’s network of eddy covariance sites in temperate eucalypt forests (potentially extending them to eucalypt plantations) to provide observational data that could be used to constrain growth model predictions (sensu Haverd et al. 2013) and to fieldtest model parameters (sensu Potithep and Yasuoka 2011). Most eucalypt forests have some capacity to maintain productivity with a certain amount of warming because their optimum temperatures for GPP are above their longterm average temperatures (Bennett et al. 2021) and they have potential to acclimate to short-term (seasonal) temperature fluctuations (Zhu et al. 2018; Zhu et al. 2021). However, eucalypt forests are unable to maintain productivity during more extreme warming events, such as heatwaves. Our understanding of how eucalypt forests respond to heatwaves has advanced considerably in the last five years, and three main patterns of response have been seen:","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/00049158.2021.2013639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The release of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC 2021) is a galvanising moment globally for concerted action to stem climate change. The report provides stronger evidence of previously identified changes to Earth systems as a result of anthropogenic greenhouse-gas emissions. If current trends for rising emissions continue beyond mid-century, the global mean temperature will be 3.3–5.7 degrees warmer by the end of this century compared with the period 1850–1900. Warming across Australia is predicted to be higher than the global average (Australian Academy of Science 2021). The Sixth Assessment Report (IPCC 2021) also gives greater prominence to extreme events, particularly heatwaves, fire weather and compound events (heatwaves coupled with droughts). Although temperature increases drive most of the extreme events that will affect temperate eucalypt forests, a trend of increasing aridity across southern Australia due to climate change (CSIRO and Bureau of Meteorology 2020) has amplified these compound events (Matusick et al. 2018) and fire risk (van Oldenborgh et al. 2021). Despite more confident predictions of future climate states under different emissions scenarios, the impacts of climate change on the productivity of temperate eucalypt forest remain uncertain. This is because of a lack of understanding about how changing temperature and moisture conditions will affect tree establishment, growth rates and mortality due to extreme events and disturbances (e.g. fire, pests and diseases). There is also considerable uncertainty about the effects of increasing atmospheric concentrations of carbon dioxide (CO2). Roxburgh et al. (2004) concluded that existing simulation models used in Australia have insufficient capability to predict the consequences of climate change for Australia’s forests. Haverd et al. (2013) made considerable advances in reducing the uncertainty of continent-scale predictions of net primary productivity by using multiple observation types to constrain BIOS2 model predictions. Two models, CABALA and 3-PG, have been used extensively in Australia to predict forest productivity under simulated future climates (Pinkard, Bruce et al. 2014; Battaglia and Bruce 2017; Wang et al. 2021). Calibration studies show that both 3-PG (Potithep and Yasuoka 2011) and CABALA (Battaglia et al. 2004; Battaglia et al. 2011) can accurately predict forest productivity when growing conditions can be defined, although 3-PG underpredicts productivity in temperate eucalypt forests, particularly the most productive of these (Haverd et al. 2013; Volkova et al. 2015). Predictions of productivity in future climates under different emissions scenarios made using CABALA and 3-PG vary widely, however, because of uncertainties surrounding climate projections, responses to higher concentrations of atmospheric CO2 (Battaglia and Bruce 2017; Wang et al. 2021) and mortality from drought (Pinkard, Bruce et al. 2014). Models need to evolve to enable more confident predictions of productivity in Australian temperate eucalypt forests under future climate scenarios. Our understanding of the key environmental drivers of productivity in eucalypt native forests has progressed in the last decade. Using independent methods, growth rates of eucalypt forests have been found to have a consistent relationship with temperature – a convex parabola with the vertex corresponding to the temperature optimum at which maximum growth occurs. Bowman et al. (2014), using an inventory approach, found an optimum (mean annual) temperature for diameter growth rates of 11°C in eucalypt forests growing on mesic sites in temperate and subtropical regions of Australia. Using data from a network of eddy covariance towers in eucalypt forests and woodlands, Bennett et al. (2021) found that temperature optima for gross primary productivity (GPP) in southern Australia ranged between 15°C and 23°C and were directly related to the historical climate of the site. There is great potential to make more use of Australia’s network of eddy covariance sites in temperate eucalypt forests (potentially extending them to eucalypt plantations) to provide observational data that could be used to constrain growth model predictions (sensu Haverd et al. 2013) and to fieldtest model parameters (sensu Potithep and Yasuoka 2011). Most eucalypt forests have some capacity to maintain productivity with a certain amount of warming because their optimum temperatures for GPP are above their longterm average temperatures (Bennett et al. 2021) and they have potential to acclimate to short-term (seasonal) temperature fluctuations (Zhu et al. 2018; Zhu et al. 2021). However, eucalypt forests are unable to maintain productivity during more extreme warming events, such as heatwaves. Our understanding of how eucalypt forests respond to heatwaves has advanced considerably in the last five years, and three main patterns of response have been seen:
政府间气候变化专门委员会第六次评估报告(IPCC 2021)的发布是全球采取一致行动遏制气候变化的一个鼓舞人心的时刻。该报告提供了更有力的证据,证明先前确定的人为温室气体排放对地球系统造成的变化。如果目前排放量上升的趋势持续到本世纪中叶以后,到本世纪末,全球平均气温将比1850-1900年期间高出3.3-5.7度。预计澳大利亚的变暖程度将高于全球平均水平(澳大利亚科学院2021年)。第六次评估报告(IPCC 2021)还更加突出了极端事件,特别是热浪、火灾天气和复合事件(热浪与干旱相结合)。尽管温度升高驱动了大多数将影响温带桉树森林的极端事件,但由于气候变化(CSIRO和气象局2020年),澳大利亚南部干旱加剧的趋势放大了这些复合事件(Matusick等人2018年)和火灾风险(van Oldenborgh等人2021年)。尽管对不同排放情景下的未来气候状态有了更有信心的预测,但气候变化对温带桉树林生产力的影响仍然不确定。这是因为缺乏对温度和湿度条件变化将如何影响树木生长、生长速度和由于极端事件和干扰(例如火灾、虫害和疾病)造成的死亡率的了解。大气中二氧化碳浓度增加的影响也存在相当大的不确定性。Roxburgh等人(2004)得出结论,澳大利亚使用的现有模拟模型在预测气候变化对澳大利亚森林的影响方面能力不足。Haverd等人(2013)通过使用多种观测类型来约束BIOS2模型预测,在降低大陆尺度净初级生产力预测的不确定性方面取得了相当大的进展。CABALA和3-PG两个模型已在澳大利亚广泛用于预测模拟未来气候下的森林生产力(Pinkard, Bruce et al. 2014;Battaglia and Bruce 2017;Wang et al. 2021)。校准研究表明,3-PG (Potithep and Yasuoka 2011)和CABALA (Battaglia et al. 2004;Battaglia et al. 2011)可以在生长条件可以确定的情况下准确预测森林生产力,尽管3-PG低估了温带桉树森林的生产力,特别是其中最多产的桉树森林(Haverd et al. 2013;Volkova et al. 2015)。然而,由于气候预测的不确定性、对大气二氧化碳浓度升高的响应(Battaglia and Bruce 2017;Wang et al. 2021)和干旱死亡率(Pinkard, Bruce et al. 2014)。模型需要不断发展,以便在未来气候情景下对澳大利亚温带桉树森林的生产力作出更有信心的预测。我们对桉树原生森林生产力的关键环境驱动因素的理解在过去十年中取得了进展。使用独立的方法,桉树森林的生长率已经发现与温度有一致的关系-一个凸抛物线,顶点对应于最大生长的最佳温度。Bowman等人(2014年)使用清查方法发现,在澳大利亚温带和亚热带地区的中型地点生长的桉树林中,直径增长率为11°C的最佳(年平均)温度。Bennett等人(2021)利用桉树林和林地涡度相关塔网络的数据发现,澳大利亚南部总初级生产力(GPP)的最佳温度范围在15°C至23°C之间,与该地点的历史气候直接相关。在温带桉树林中,有很大的潜力可以更多地利用澳大利亚的涡流相关站点网络(可能将其扩展到桉树种植园),以提供可用于约束生长模型预测的观测数据(sensu Haverd et al. 2013),并对模型参数进行实地测试(sensu Potithep和Yasuoka 2011)。大多数桉树林有一定的能力在一定程度的变暖下保持生产力,因为它们的GPP最佳温度高于其长期平均温度(Bennett等人,2021),并且它们有可能适应短期(季节性)温度波动(Zhu等人,2018;Zhu et al. 2021)。然而,桉树林无法在更极端的变暖事件中保持生产力,例如热浪。在过去的五年中,我们对桉树森林如何应对热浪的理解有了很大的进步,已经看到了三种主要的响应模式: