Monitoring Global Tree Mortality Patterns and Trends
Coming soon: Interactive map providing geo-referenced information on tree mortality events
This map will provide geo-referenced information on tree mortality events that have been documented in peer reviewed publications over the last ~50 years. In addition, we will provide a functionality that allows signalling of new mortality events via an online entry tool.
Global forest coverage can be affected by a variety of different factors, including large-scale deforestation, fire and pests. By contrast, climate change via increasing temperatures and reduced precipitation often has rather diffuse impacts on forest cover by killing individual trees. This type of mortality is likely to increase with ongoing climate change and has the potential to threaten global forest survival (Allen et al. 2010, 2015). At the same time, unusually high tree mortality rates are, at the global scale, one of the most robust indicators of global forest health (Trumbore et al. 2015).
A viable strategy to assess transitions from healthy to unhealthy forests can only be achieved by long-term observations and must be based on a thorough understanding of the background levels of forest disturbance and associated mortality. Identifying the underlying causes the physiological or anatomical mechanisms of mortality are therefore central elements in understanding and predicting forest condition under rapid environmental change (Hartmann et al. 2018b).
This Task Force aims to initiate a global effort to integrate existing data sources (national forest inventories, plot networks and remote-sensing approaches to assess changes in tree mortality patterns globally and to relate mortality occurrence to environmental factors.
Given the interdisciplinarity of tree and forest mortality, our initiative brings together scientists from multiple research areas, including:
- Physiological mechanisms of mortality
- Forest inventory
- Remote sensing
The ultimate goal of this Task Force is the establishment of a multidisciplinary global monitoring network of tree mortality patterns and trends. The long-term objectives will be to facilitate: (1) horizontal integration of existing field data sources for knowledge (gap) analyses and facilitation of data sharing, (2) interdisciplinary and international collaboration for a coordinated vertical integration of different data sources (satellite imagining, LiDAR, plot data), (3) identification of areas of rapid changes in forest cover that can be used as field research sites for determining causality and (4) derivation of mechanistic relationships from monitoring and field observation that can be used as predictors in global vegetation models to improve forecasting of vegetation dynamics under ongoing climate change.
The tools and techniques currently used to measure forest condition do not allow clearly assigning changes in fine-scale tree cover loss to specific causes. Although remote sensing approaches provide some useful proxies for forest condition globally (e.g., canopy cover, photosynthesis, and phenology), it remains unclear how trends detected from space correspond to other aspects such as individual tree vigour or mortality. A major gap remains in linking existing plot data to remote sensing pixels, especially with respect to detecting and attributing altered rates of tree mortality. Therefore, a horizontally integrated approach based on existing plot networks and national forest inventories will facilitate detection of mortality events and changes in mortality rates (Fig. 1). Gaps in the 'vertical flow' of information, i.e. across spatial scales and data types (satellites to field assessment) must be bridged by interdisciplinary communication and collaboration, allowing data sources to be shared and made freely available to the scientific community.
Figure 1 - Description: Strategy for a global monitoring network of tree mortality. Horizontal and vertical integration of data sources allow assessments of background mortality rates as well as mortality hotspots. Long-term monitoring provides information on both mortality trends and patterns. In mortality hotspots, intensive field observations and experiments identify mechanistic relationships that can be used in vegetation models for more realistic projections of future forest conditions.