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Climate change on Eucalyptus plantations and adaptive measures for sustainable forestry development across Brazil [1]

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Date: 2022-11-15

Eucalyptus sp. is the most widely planted forest genus worldwide, with 25 million planted hectares (FAO, 2021, Martins et al., 2022). Brazil is the world's largest Eucalyptus producer, with around 7.6 million planted hectares, constituting about ∼7 % of industrial Brazil’s Gross Domestic Product (IBÁ, 2019), with average productivity at 36 m³ ha-1 year-1 (Elli et al., 2020a, Elli et al., 2020b, IBGE, 2020). Primary products from Brazilian Eucalyptus plantations, e.g., pulp, paper, and lumber, as well as secondary products, e.g., furniture, flooring, and frames, are exported to several countries, underscoring the importance of Brazilian plantations for the international market.

Currently, most Eucalyptus plantations in Brazil are located (Fig. 1) in the Southeast, in Minas Gerais (26 %), and São Paulo (13 %), the Center-West, in Mato Grosso do Sul (15 %), the South, in Paraná (9 %) and Rio Grande do Sul (∼8 %), and the Northeast, in Bahia (8 %) (IBGE, 2020). Despite having fewer planted areas, the North (<5 %) has increased Eucalyptus plantations given expansion into new agricultural and forestry frontiers. Furthermore, the following pure species are mainly used for Brazilian plantations (ordered in terms of importance) (Correia et al., 2019, IBÁ, 2019, Gonçalves et al., 2013): Eucalyptus grandis (W. Hill ex Maiden), Corymbia citriodora (Hook.) KD Hill & LAS Johnson) (formerly known as E. citriodora – basionym), E. urophylla (ST Blake), E. saligna (Sm.), E. globulus (Labill.), E. camaldulensis (Dehnh.), and hybrids E. urophylla × E. grandis, E. urophylla × E. camaldulensis, E. grandis × E. camaldulensis and E. urophylla × E. globulus (Binkley et al., 2017, Elli et al., 2019, Freitas et al., 2020, Hakamada et al., 2020, Martins et al., 2014). These aforementioned species or hybrids are preferred due to their favorable characteristics, like wood quality, fast growth times, short rotation cycles (<7 years), high productivity, capacity for adapting to different soils and climatic conditions, and ease of management (Costa et al., 2018, Costa and Streck, 2018, Elli et al., 2019, Elli et al., 2020b; Flores et al., 2016; Gonçalves et al., 2013; Martins et al., 2014, Martins et al., 2022). These positive characteristics contribute to reducing demand for native Brazilian species that would otherwise be used for furniture or energy production, or in industrial products in general (Abreu et al., 2022, Binkley et al., 2017, Gonçalves et al., 2013, Martins et al., 2022).

Even with significant advances in the form of clone adaptations, improved management practices, soil preparation and fertilization, and pest and disease control, Eucalyptus development and productivity are strongly affected by climate variability (Binkley et al., 2017, Elli et al., 2020a, Elli et al., 2020b, Gonçalves et al., 2017, Hubbard et al., 2020, Martins et al., 2022). Water deficits (Abreu et al., 2022, Elli et al., 2020a, Elli et al., 2020b, Freitas et al., 2021, Martins et al., 2022, Scolforo et al., 2019), and extreme temperatures outside of appropriate thresholds (from 8.5 ºC to ∼40 ºC) (Freitas et al., 2017, Martins and Streck, 2007), are the main causes of reduced Eucalyptus productivity in Brazil. There is even greater concern about potential impacts of climate change on development, growth, and productivity patterns (Battaglia and Bruce, 2017, Costa and Streck, 2018, Elli et al., 2020a, Ellsworth et al., 2017, Resquin et al., 2020), and on suitable areas for Eucalyptus plantations. These impacts may occur due to projected air temperature increases for most of Brazil (up to 5 ºC) (Chou et al., 2014, Llopart et al., 2020, Lyra et al., 2018, Martins et al., 2020, Torres and Marengo, 2014), and heterogeneous (different) changes to precipitation patterns, i.e., reduced rainfall at lower latitudes, and increased rainfall at higher latitudes (IPCC, 2013, Llopart et al., 2020, Santos et al., 2017, Tavares et al., 2018, Torres et al., 2021).

High temperatures negatively influence the formation of molecular (proteins and DNA), and supramolecular (membranes and chromosomes) structures, and cause physiological stress, limiting the carbon balance of plants (Fagundes et al., 2021, Rawal et al., 2015, Ruelland and Zachowski, 2010). Furthermore, high temperatures increase vapor pressure deficits, leading to increased potential evapotranspiration (Abreu et al., 2015, Elli et al., 2020a, Hubbard et al., 2020). By contrast, reduced precipitation limits water availability for Eucalyptus, since water supplies may be less than the evapotranspiration losses (Abreu et al., 2015, Elli et al., 2020a, Hubbard et al., 2020, Martins et al., 2022). If these projections come to pass, even slowly and gradually, they may result in changes to physiological, morphological, and anatomical patterns, which when amplified over time, could lead to mortality, changes in species distribution, and unviability for Eucalyptus plantations (Booth, 2013, Booth, 2017, Booth, 2018, Elli et al., 2020a, Martins et al., 2022). These threats may be even more pronounced in Brazil, where Eucalyptus plantations are expanding into less suitable locations, with more intense water deficits and higher temperatures (Correa et al., 2020, Elli et al., 2020a, Elli et al., 2020b, Gonçalves et al., 2013, Martins et al., 2022).

For these reasons, mapping areas with suitable climatic potential for Eucalyptus plantations under future climate scenarios is essential for reducing vulnerabilities to the Brazilian forestry sector, for defining safer strategies for forestry planning, and silvicultural practices, and guiding effective adaptive measures to cope with climate change threats. By combining outputs from Earth System models (ESMs) (Elli et al., 2020a, Martins et al., 2022, Reis et al., 2021, Santos et al., 2017) with agroclimatic zoning (AZ) (Martins et al., 2020, Tavares et al., 2018), researchers can map regions with suitable climatic conditions to certain Eucalyptus species plantations under current and future climates. The ESMs from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) (Taylor et al., 2012), are currently the most widely used models for projecting future climate scenarios (Elli et al., 2020a, Fagundes et al., 2021, Martins et al., 2022, Reis et al., 2021, Silva et al., 2021, Torres et al., 2021), even after the newest version of the CMIP (CMIP6) was made available. Preliminary analyses between CMIP5 and CMIP6, even when using a new generation of forcing scenarios, showed that there were no substantial changes for South America and Brazil (Almazroui et al., 2021, Ortega et al., 2021), indicating that ESMs from CMIP5 are reliable, and can be used until the CMIP6 database is fully available and evaluated. Furthermore, studies using multi-ESM ensembles have been used to cover a range of possible outcomes, reducing uncertainties in future climate projections (Elli et al., 2020a, Martins et al., 2022, Reis et al., 2021, Torres et al., 2021).

Although AZ provides useful information for forestry planning, management, decision-making, and designing suitable areas for plantations under future climate conditions, reducing possible economic losses from planting in unsuitable areas, its application has been practically restricted to agricultural crops, like cotton (Assad et al., 2013), coffee (Sediyama et al., 2001, Tavares et al., 2018), sugar cane (Silva et al., 2021), olive (Martins et al., 2020, Santos et al., 2017), maize (Ramirez-Cabral, 2017), wheat (Santi et al., 2017), and soybeans (Minuzzi and José, 2018). Studies on forest species are still scarce. The studies that have been carried out, have only considered water availability limitations, and have disregarded thermal limitations (or vice versa) (Martins et al., 2022, Pirovani et al., 2018, Rody et al., 2012, Wrege et al., 2016, Wrege et al., 2017). In other words, these studies have not entirely employed appropriate AZ techniques, since they have not considered the combined effects of temperature and water availability projections. Furthermore, the few studies that do exists on forest species may have been somewhat limited since i) they were performed at local scales (microscale) (Correa et al., 2020, Gomes et al., 2021), ii) they considered future climate scenarios that are completely outdated or unused, e.g., ESMs from CMIP Phase 3, and/or iii) do not use a multi-ESM ensemble approach (Campanharo et al., 2011, Pirovani et al., 2018, Rody et al., 2012, Wrege et al., 2016, Wrege et al., 2017), and therefore, may have a high degree of uncertainty for future projections.

In order to provide useful and reliable information so that the forestry planning and management sectors, and decision-makers can adapt to climate change AZ must: i) analyze changes in the suitability areas for Eucalyptus plantations using a macroscale approach, and ii) evaluate the spatiotemporal patterns on changes in air temperature, precipitation, water availability, and other AZ input variables. Given the scarcity of studies of this nature, combined with the possible impacts caused by projected climate change in Brazil, three practical questions still remain unanswered when using a macroscale approach: i) what are the spatiotemporal patterns of changes in air temperature, precipitation, and water availability for each continental grid point in Brazil?; ii) what are their effects on the suitability classes of Brazilian Eucalyptus plantations?; and iii) what would be the most effective adaptive measures, in the event of negative impacts or restrictions to Eucalyptus plantations?

Given the aforementioned situation, and to answer these questions, this study assessed and identified climate change impacts on suitable areas for planting the main Eucalyptus species/hybrids in Brazil throughout the 21st century, using multi-ESM ensembles, via an AZ method that combined water and thermal limitations, analyzed the spatiotemporal patterns of changes in climatic variables that impact Eucalyptus plantations in Brazil, and outlined adaptive measures to deal with these impacts along the entire productive chain.

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[1] Url: https://www.sciencedirect.com/science/article/abs/pii/S0926669022010214/

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