Cumulative Drought Stress Leads to a Loss of Growth Resilience and Explains Higher Mortality in Planted than in Naturally Regenerated Pinus pinaster Stands

The assessment of the long-term impacts of drought on tree growth decline using tree-ring analyses may be used to test if plantations are more vulnerable to warming after successive droughts, leading to a “cumulative stress” effect. We selected 76 Pinus pinaster trees (declining and non-declining trees), and basal area increments over the last 20 years (BAI20) were calculated to build the chronologies for the stand types and vigor classes. Resistance, recovery and resilience indices were calculated. Pearson correlations, analyses and Partial Least-Squares regression were used to analyze the relationships among the response and environmental variables. We found a negative and significant relationship between mean temperature for May and June of the current year and growth in the naturally regenerated stands. This negative effect on growth under warm spring conditions was more noticeable in plantations than in naturally regenerated stands. A negative trend along time was found for the resilience index in planted stands. Evapotranspiration, maximum temperature and annual radiation showed significant and negative correlations with the growth of declining trees from planted stands, indicating they are susceptible to drought stress. Declining trees in planted stands showed a loss of growth resilience, specifically a negative trend after successive droughts

Climate change may threaten the southernmost Pinus nigra subsp. salzmannii (Dunal) Franco populations: an ensemble niche-based approach

We used Species Distribution Modeling to predict the probability of Iberian pine (Pinus nigra subsp. salzmannii [Dunal] Franco) occurrences in southern Spain in response to environmental variables and to forecast the effects of climate change on their predicted geographical distribution. The ensemble modeling approach “biomod2” was used, together with present Iberian pine data, to predict the current potential distribution based on bioclimatic explanatory variables (200 m resolution) and to forecast future suitability by studying three periods (2040, 2070, and 2100), considering the Global Circulation Models BCM2, CNCM3, and ECHAM5, and the regional model EGMAM, for different scenarios (SRAB1, SRA2, SRB1). Model evaluation was performed using Kappa, True Skills Statistic (TSS), and Area Under the Curve (AUC) values. The biomod2 approach highlighted the average number of days with a minimum temperature equal to or below 0°C, annual precipitation, and aridity index as the most important variables to describe the P. nigra occurrence probability. Model performances were generally satisfactory and the highest AUC values and high stability of the results were given by GAM and GLM, but MaxEnt and the SRE model were scarcely accurate according to all our statistics. The ensemble Species Distribution Modeling of P. nigra in Andalusia predicted the highest probability of species occurrence in the eastern areas, Sierra de Cazorla being the area with the highest occurrence of P. nigra in Andalusia. In the future habitat, the general probability of P. nigra occurrence in Andalusia will decrease widely; the species is expected to lose habitat suitability at moderate altitudes and its occurrence probability will have decreased by nearly 70% on average by 2100, affected by the selected scenario. Populations in Sierra de Cazorla are those most suitable for P. nigra growth, even under the most pessimistic scenarios. It is likely that the natural southern populations of P. nigra will be very sensitive to changes in climate

Climate change may threaten the southernmost Pinus nigra subsp. salzmannii (Dunal) Franco populations: an ensemble niche-based approach

We used Species Distribution Modeling to predict the probability of Iberian pine (Pinus nigra subsp. salzmannii [Dunal] Franco) occurrences in southern Spain in response to environmental variables and to forecast the effects of climate change on their predicted geographical distribution. The ensemble modeling approach “biomod2” was used, together with present Iberian pine data, to predict the current potential distribution based on bioclimatic explanatory variables (200 m resolution) and to forecast future suitability by studying three periods (2040, 2070, and 2100), considering the Global Circulation Models BCM2, CNCM3, and ECHAM5, and the regional model EGMAM, for different scenarios (SRAB1, SRA2, SRB1). Model evaluation was performed using Kappa, True Skills Statistic (TSS), and Area Under the Curve (AUC) values. The biomod2 approach highlighted the average number of days with a minimum temperature equal to or below 0°C, annual precipitation, and aridity index as the most important variables to describe the P. nigra occurrence probability. Model performances were generally satisfactory and the highest AUC values and high stability of the results were given by GAM and GLM, but MaxEnt and the SRE model were scarcely accurate according to all our statistics. The ensemble Species Distribution Modeling of P. nigra in Andalusia predicted the highest probability of species occurrence in the eastern areas, Sierra de Cazorla being the area with the highest occurrence of P. nigra in Andalusia. In the future habitat, the general probability of P. nigra occurrence in Andalusia will decrease widely; the species is expected to lose habitat suitability at moderate altitudes and its occurrence probability will have decreased by nearly 70% on average by 2100, affected by the selected scenario. Populations in Sierra de Cazorla are those most suitable for P. nigra growth, even under the most pessimistic scenarios. It is likely that the natural southern populations of P. nigra will be very sensitive to changes in climate

Modelling Current and Future Potential Habitats for Plantations of Eucalyptus grandis Hill ex Maiden and E. dunnii Maiden in Uruguay.

ABSTRACT.Eucalyptus grandis and E. dunnii have high productive potential in the South of Brazil, Uruguay, and central Argentina. This is based on the similarity of the climate and soil of these areas, which form an eco-region called Campos. However, previous results show that these species have dierences in their distribution caused by the prioritization of Uruguayan soils for forestry, explained by the particular conditions of each site. In this study, the site variables (climate, soil, and topography) that better explain the distribution of both species were identified, and prediction models of current and future distribution were adjusted for dierent climate change scenarios (years 2050 and 2070). The distribution of E. grandis was associated with soil parameters, whereas for E. dunnii a greater eect of the climatic variables was observed. The ensemble biomod2 model was the most precise with regard to predicting the habitat for both species with respect to the simple models evaluated. For E. dunnii, the average values of the AUC, Kappa, and TSS index were 0.98, 0.88, and 0.77, respectively. For E. grandis, their values were 0.97, 0.86, and 0.80, respectively. In the projections of climatic change, the distribution of E. grandis occurrence remains practically unchanged, even in the scenarios of temperature increase. However, current distribution of E. dunnii shows high susceptibility in a scenario of increased temperature, to the point that most of the area currently planted may be at risk. Our results might be useful to political government and foresters for decision making in terms of future planted areas.© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)