Gloy Josias, Herzschuh Ulrike, Kruse Stefan
Polar Terrestrial Environmental Systems Research Group, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 14473 Potsdam, Germany.
Institute of Biology and Biochemistry, University of Potsdam, 14476 Potsdam, Germany.
Ecol Modell. 2023 Apr;478:110278. doi: 10.1016/j.ecolmodel.2023.110278.
With changing climate, the boreal forest could potentially migrate north and become threatened by droughts in the south. However, whether larches, the dominant tree species in eastern Siberia, can adapt to novel situations is largely unknown but is crucial for predicting future population dynamics. Exploring variable traits and trait adaptation through inheritance in an individual-based model can improve our understanding and help future projections. We updated the individual-based spatially explicit vegetation model LAVESI ( Vegetation Simulator), used for forest predictions in Eastern Siberia, with trait value variation and incorporated inheritance of parental values to their offspring. Forcing the model with both past and future climate projections, we simulated two areas - the expanding northern treeline and a southerly area experiencing drought. While the specific trait of 'seed weight' regulates migration, the abstract 'drought resistance' protects stands. We show that trait variation with inheritance leads to an increase in migration rate (∼ 3% area increase until 2100). The drought resistance simulations show that, under increasing stress, including adaptive traits leads to larger surviving populations (17% of threatened under RCP 4.5 (Representative Concentration Pathway)). We show that with the increase expected under the RCP 8.5 scenario vast areas (80% of the extrapolated area) of larch forest are threatened and could disappear due to drought as adaptation plays only a minor role under strong warming. We conclude that variable traits facilitate the availability of variants under environmental changes. Inheritance allows populations to adapt to environments and promote successful traits, which leads to populations that can spread faster and be more resilient, provided the changes are not too drastic in both time and magnitude. We show that trait variation and inheritance contribute to more accurate models that can improve our understanding of responses of boreal forests to global change.
随着气候的变化，北方森林可能会向北迁移，并受到南方干旱的威胁。然而，落叶松作为东西伯利亚的主要树种，是否能够适应新环境在很大程度上尚不清楚，但这对于预测未来种群动态至关重要。通过基于个体的模型探索可变性状以及性状通过遗传的适应性，可以增进我们的理解并有助于未来的预测。我们更新了用于东西伯利亚森林预测的基于个体的空间明确植被模型LAVESI（植被模拟器），纳入了性状值变异，并将亲代值遗传给后代。利用过去和未来的气候预测对该模型进行驱动，我们模拟了两个区域——不断扩张的北方林线和一个经历干旱的南方区域。“种子重量”这一特定性状调节迁移，而抽象的“抗旱性”则保护林分。我们表明，具有遗传的性状变异会导致迁移率增加（到2100年面积增加约3%）。抗旱性模拟表明，在压力不断增加的情况下，纳入适应性性状会导致更大的存活种群（在代表性浓度路径4.5（RCP 4.5）下，受威胁种群减少17%）。我们表明，在RCP 8.5情景下预计的升温情况下，大片落叶松林（推断面积的80%）受到威胁，并且可能因干旱而消失，因为在强烈变暖情况下适应作用仅占很小一部分。我们得出结论，可变性状有助于在环境变化下提供变异体。遗传使种群能够适应环境并促进成功性状，这导致种群能够更快扩散且更具恢复力，前提是变化在时间和幅度上都不太剧烈。我们表明，性状变异和遗传有助于建立更准确的模型，从而增进我们对北方森林对全球变化响应的理解。
