Abstract
High levels of ‘Candidatus Phytoplasma pini’ have produced extensive forest mortality on Pinus halepensis Mill forests in eastern Spain. This has led to the widespread levels of forest mortality. We used archival Landsat imagery and shapes algorithm implemented in the Google Earth Engine to explore the potential of the LandTrendr algorithm and its outputs, together with field observations, to analyze and predict the health status in P. halepensis stands affected by ‘Candidatus Phytoplasma pini’ in Andalusia (south-eastern Spain). We found that the Landsat time series algorithm (LandTrendr) has captured both long- and short-duration trends and changes in spectral reflectance related to phytoplasma disturbance in the Aleppo pine forest stands investigated. The normalized burn ratio (NBR) trends were positively associated with environmental variables: Annual precipitation, mean temperature, soil depth, percent base saturation and aspect. Environmental variables were tested for their contributions to the mapping of changes in Aleppo pine cover in the study area, as an empirical modeling approach to disturbance mapping in forests of south-eastern Spain. The methodology outlined in this paper has produced valuable results that indicate new possibilities for the use in forest management of remote-sensing technologies based on spectral trajectories associated with pest-diseases defoliation. Given the likely increase in pest risks in the forests of southern Europe, accurate assessment and map of pest outbreaks on forests will become increasingly important, both for research and for practical applications in forest management.
Highlights
Worldwide, forest decline and tree mortality events due to climate change have increased since the mid-20th century [1], affecting thousands of hectares in Europe
This paper documents the use of the LandTrendr algorithm and Landsat multi-temporal analysis: 1) To study the feasibility of using the variability in the temporal spectral trajectories of the normalized burn ratio (NBR) index to map the current location of phytoplasma defoliation in Aleppo pine forests, and 2) to map the potential risk according to three levels of defoliation as a function of environmental variables
This paper documents the use of the LandTrendr algorithm and Landsat multi-temporal analysis: (1) To study the feasibility of using the variability in the temporal spectral trajectories of the NBR index to map the current location of phytoplasma defoliation in Aleppo pine forests, and (2) to map the potential risk according to three levels of defoliation as a function of environmental variables
Summary
Forest decline and tree mortality events due to climate change have increased since the mid-20th century [1], affecting thousands of hectares in Europe. In the south-western Mediterranean Basin, many coniferous forests have experienced recent large-scale tree mortality events, affecting Scots pine (Pinus sylvestris L.) [2]; black pine (Pinus nigra Arnold.) [3]; mixed conifer stands (Abies pinsapo Boiss.—Pinus spp.) [4] and maritime pine (Pinus pinaster Aiton.) [4], among others [5]. Pinus forest mortality linked to climatic factors has been documented in southern Spain [2,4,9] more-proximal exogenous factors, such as forest pests, and endogenous factors, such as stand density and environmental setting, are important [10]. The phytoplasma detected is widely dispersed in many different Aleppo pine forests in southern Spain, with important environmental and economic impacts
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
