Climate change is expected to affect forests ' growth and functioning and to increase their vulnerability to stressors such as prolonged drought and pest outbreaks. Identifying vulnerable forest stands and predicting tree decline is critical for timely management interventions to preserve forests integrity and associated ecosystem services. This study combined dendrochronological and isotopic analyses with satellite remote sensing to detect early warning signs of forest decline in a Pinus pinea L. stand in southern Italy affected by one of the first outbreak of the pine parasite Toumeyella parvicornis reported in Italy. Furthermore, through a comparative study of the analysis techniques, this research aimed to identify the most effective data processing strategies for detecting tree dieback of this species. Satellite analysis revealed a gradual decline in vegetation indices (NDVI, EVI, EVI2) of the stand from 2015 onwards, which coincided with the onset of defoliation due to the pest outbreak. The decline in defoliation intensified in 2020, leading to a severe tree carbon deficit and subsequent mortality of the pine stand in 2023. In comparison, indices such as EVI and EVI2 have been shown to be more sensitive than NDVI in detecting changes in canopy cover. The inclusion of the NDMI index provided important information on the moisture dynamics of the stand. Dendrochronological analyses complemented remote sensing data: a strong decrease in growth was observed from 2020 onwards, undemanding a tipping point for the Pinus pinea stand, which led to tree mortality in 2023. The study highlighted the higher sensitivity of detrended chronologies such as BAI and TRW-I in detecting signs of forest dieback compared to raw tree -ring data. Moreover, intrinsic water use efficiency (WUEi) analysis provided insight into the eco-physiological dynamics underlying pine tree decline, revealing lower tree water retention induced by defoliation. Finally, correlations between growth and WUEi data with meteorological variables highlighted how defoliation increased the vulnerability of trees to the effects of climate, influencing their ability to recover after the pest attack. In conclusion, the combination of these analysis methods provided a detailed and comprehensive overview of tree species dieback due to new invasive pest. Our findings providing valuable insights into the eco-physiological dynamics and early detection of signs of tree decline, useful for planning effective forest management strategies to counteract the diffusion of Toumeyella parvicornis across Italy and Europe.
Impact of Toumeyella parvicornis outbreak in Pinus pinea L. forest of Southern Italy: First detection using a dendrochronological, isotopic and remote sensing analysis
Niccoli F.
;Kabala J. P.;Battipaglia G.
2024
Abstract
Climate change is expected to affect forests ' growth and functioning and to increase their vulnerability to stressors such as prolonged drought and pest outbreaks. Identifying vulnerable forest stands and predicting tree decline is critical for timely management interventions to preserve forests integrity and associated ecosystem services. This study combined dendrochronological and isotopic analyses with satellite remote sensing to detect early warning signs of forest decline in a Pinus pinea L. stand in southern Italy affected by one of the first outbreak of the pine parasite Toumeyella parvicornis reported in Italy. Furthermore, through a comparative study of the analysis techniques, this research aimed to identify the most effective data processing strategies for detecting tree dieback of this species. Satellite analysis revealed a gradual decline in vegetation indices (NDVI, EVI, EVI2) of the stand from 2015 onwards, which coincided with the onset of defoliation due to the pest outbreak. The decline in defoliation intensified in 2020, leading to a severe tree carbon deficit and subsequent mortality of the pine stand in 2023. In comparison, indices such as EVI and EVI2 have been shown to be more sensitive than NDVI in detecting changes in canopy cover. The inclusion of the NDMI index provided important information on the moisture dynamics of the stand. Dendrochronological analyses complemented remote sensing data: a strong decrease in growth was observed from 2020 onwards, undemanding a tipping point for the Pinus pinea stand, which led to tree mortality in 2023. The study highlighted the higher sensitivity of detrended chronologies such as BAI and TRW-I in detecting signs of forest dieback compared to raw tree -ring data. Moreover, intrinsic water use efficiency (WUEi) analysis provided insight into the eco-physiological dynamics underlying pine tree decline, revealing lower tree water retention induced by defoliation. Finally, correlations between growth and WUEi data with meteorological variables highlighted how defoliation increased the vulnerability of trees to the effects of climate, influencing their ability to recover after the pest attack. In conclusion, the combination of these analysis methods provided a detailed and comprehensive overview of tree species dieback due to new invasive pest. Our findings providing valuable insights into the eco-physiological dynamics and early detection of signs of tree decline, useful for planning effective forest management strategies to counteract the diffusion of Toumeyella parvicornis across Italy and Europe.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
