A Self-Calibrated Non-Parametric Time Series Analysis Approach for Assessing Insect Defoliation of Broad-Leaved Deciduous Nothofagus pumilio Forests

Roberto Chávez,Marcelo Dörner,Sergio Estay,Ronald Rocco,Álvaro Gutiérrez

doi:10.3390/rs11020204

Abstract

Folivorous insects cause some of the most ecologically and economically important disturbances in forests worldwide. For this reason, several approaches have been developed to exploit the temporal richness of available satellite time series data to detect and quantify insect forest defoliation. Current approaches rely on parametric functions to describe the natural annual phenological cycle of the forest, from which anomalies are calculated and used to assess defoliation. Quantification of the natural variability of the annual phenological baseline is limited in parametric approaches, which is critical to evaluating whether an observed anomaly is “true” defoliation or only part of the natural forest variability. We present here a fully self-calibrated, non-parametric approach to reconstruct the annual phenological baseline along with its confidence intervals using the historical frequency of a vegetation index (VI) density, accounting for the natural forest phenological variability. This baseline is used to calculate per pixel (1) a VI anomaly per date and (2) an anomaly probability flag indicating its probability of being a “true” anomaly. Our method can be self-calibrated when applied to deciduous forests, where the winter VI values are used as the leafless reference to calculate the VI loss (%). We tested our approach with dense time series from the MODIS enhanced vegetation index (EVI) to detect and map a massive outbreak of the native Ormiscodes amphimone caterpillars which occurred in 2015–2016 in Chilean Patagonia. By applying the anomaly probability band, we filtered out all pixels with a probability <0.9 of being “true” defoliation. Our method enabled a robust spatiotemporal assessment of the O. amphimone outbreak, showing severe defoliation (60–80% and >80%) over an area of 15,387 ha of Nothofagus pumilio forests in only 40 days (322 ha/day in average) with a total of 17,850 ha by the end of the summer. Our approach is useful for the further study of the apparent increasing frequency of insect outbreaks due to warming trends in Patagonian forests; its generality means it can be applied in deciduous broad-leaved forests elsewhere.

Highlights

Insect outbreaks are considered one of the major disturbances for temperate forests in North America and Europe, leading to extensive timber and carbon losses [1,2,3]
In order to overcome these limitations, we propose a flexible non-parametric approach based on probabilistic estimations of the annual phenological cycle, from which anomalies can be assessed in terms of the frequency distribution of historical records
We developed an algorithm in R to reconstruct the annual enhanced vegetation index (EVI) phenological cycle of N. pumilio forests using Moderate Resolution Imaging Spectroradiometer (MODIS) EVI time series for the period 2001–2015 and to calculate EVI anomalies for the 2015–2016 GS (Figure 3)

Summary

Introduction

Insect outbreaks are considered one of the major disturbances for temperate forests in North America and Europe, leading to extensive timber and carbon losses [1,2,3]. These natural events have had dramatic consequences for the forestry industry, and for the ecosystem and biodiversity conservation related to changes in the forest carbon cycle, composition, and structure [4,5]. In temperate forests in the southern tip of South America (Chilean and Argentinian Patagonia), massive insect outbreaks of the native moth Ormiscodes amphimone causing total defoliation of broad-leaved Nothofagus pumilio (Nothofagaceae) forests have recently been reported [11,12,13]. A major reason for this research gap is that collecting field data to assess the defoliation level of folivorous insect outbreaks in remote and vast areas such as Chilean Patagonia is challenging

Methods

Results

Conclusion