Abstract
The early growth stage is critical in the response of trees to climate change and variability. It is not clear, however, what climate metrics are best to define the early-growth sensitivity in assessing adaptation strategies of young forests to climate change. Using a combination of field experiments and modelling, we assessed the climate sensitivity of two promising afforestation species, Jatropha curcas L. and Moringa oleifera Lam., by analyzing their predicted climate–growth relationships in the initial two years after planting on degraded cropland in the semi-arid zone of Benin. The process-based WaNuLCAS model (version 4.3, World Agroforestry Centre, Bogor, Indonesia) was used to simulate aboveground biomass growth for each year in the climate record (1981–2016), either as the first or as the second year of tree growth. Linear mixed models related the annual biomass growth to climate indicators, and climate sensitivity indices quantified climate–growth relationships. In the first year, the length of dry spells had the strongest effect on tree growth. In the following year, the annual water deficit and length of dry season became the strongest predictors. Simulated rooting depths greater than those observed in the experiments enhanced biomass growth under extreme dry conditions and reduced sapling sensitivity to drought. Projected increases in aridity implied significant growth reduction, but a multi-species approach to afforestation using species that are able to develop deep-penetrating roots should increase the resilience of young forests to climate change. The results illustrate that process-based modelling, combined with field experiments, can be effective in assessing the climate–growth relationships of tree species.
Highlights
There is an increasing recognition of the roles of forests and trees in mitigation and adaptation strategies to global climate change [1,2]
We argue that well-calibrated tree–soil interaction models, simulating sapling growth responses for at least 30 years of weather data can help in (a) identifying the best predictors among a wide set of metrics that can be objectively derived from existing weather records; (b) evaluating where the years with experimental data are positioned within current climate variability according to the metrics with the highest predictive power identified in (a); and (c) using the results of (a) and (b) to assess the probability of success for given species at a given location under various location-specific climate change scenarios
The overall evaluation of the model indicated a good fit between the model estimates and empirical values for the key parameters, as evidenced by the satisfactory values of model efficiency (EF), coefficient of determination (CD), coefficient of residual mass (CRM), and maximum error (ME) (Figure 3)
Summary
There is an increasing recognition of the roles of forests and trees in mitigation and adaptation strategies to global climate change [1,2]. Trees are central to many climate change adaptation and mitigation strategies, they are vulnerable ( in their early growth), to variation in solar radiation, rainfall, and temperature as determinants of potential evapotranspiration (ET0) Changes in these climatic variables, temperature increases and precipitation shortages leading to higher frequencies of extreme weather events (i.e., severe drought and intense rainfall), are expected to affect tree growth and challenge the sustainable management of forests and tree plantations [8,9,10]. Tree growth sensitivity to drought may be substantial in West African semi-arid zones, where water availability is one of the most limiting factors of plant growth, e.g., [11], and where extreme drought events are projected to become more frequent [12,13,14] In this region, extreme drought events are associated with extended dry spells, low air humidity, high atmospheric evaporative demand, and high air temperatures [15], potentially increasing water stress in trees [13]. This information is urgently needed to explore species’ responses to past and current climate and evaluate the effects of climate change on tree growth [19]
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