Over the last 30 years forest health became a popular issue together with the concern about acid rain, air pollution, and climate change. Terms like forest decline, and the German ‘Waldsterben' (forest death) and ‘Neuartigen Waldscha ¨den' (new type of forest damage) became frequent in scientiﬁc literature as well as in popular media. This concern resulted in an unprecedent effort to study and monitor forest health. Since then the situation has evolved and now forest health diagnosis and monitoring is relevant to a much broader area of interest, including recent (e.g., climate ﬂuctuation and change, biodiversity, sustainable resource management) and ‘traditional' issues (e.g., pests, diseases, forest ﬁre). Broadly, forest health diagnosis, monitoring, and evaluation aims to identify forest health problems, track forest health status through time and identify its relationship with environmental (biotic and abiotic) factors. It embraces a variety of activities and involves several topics and scientiﬁc disciplines. Forest health diagnosis, monitoring and evaluation is addressed here in terms of (1) deﬁnitions, factors affecting forest health and most known forest health declines in the world, (2) methods of diagnosis, monitoring, and evaluation, and (3) relevance and applications.
[...] Recent deﬁnitions of forest health as well as the criteria and indicators for sustainable forest management (SFM) consider key words such as ‘long-term sustainability,' ‘resilience,' ‘maintenance' of ‘ecosystems structure and functions,' ‘multiple beneﬁts and products.' Overall, this suggests that the health of individual trees is somewhat different from the health of the forest: although the detection of individual unhealthy trees is important as they may be signaling the occurrence of problems that may become serious in the future, it is important to consider that death of trees is as important as birth and growth to the vitality of forests. [...]
[...] In general terms, health assessment at the ecosystem level needs to consider resilience, vigor, and organization of the ecosystem as well as the presence of stressors that may exceed the tolerance limit of the system. Resilience, vigor, and organization can be interpreted in operational terms as diversity, integrity of the physical, biotic, and trophic networks, productivity, equilibrium between demand and supply of essential resources, resistance to catastrophic change, and ability to recover. Also, the occurrence of endangered species has to be considered. [...]
[...] While they were started in relation to air pollution and within that framework as a contribution to international conventions and legal mandates, now the area for application is much broader. A ﬁrst advance was to place more emphasis on traditional damaging agents. More recently, forest health monitoring has been included in program related to issues such as biodiversity, carbon sequestration, long-term ecological research, and international processes dealing with SFM and long-term resource management. For the above reasons, forest health diagnosis, monitoring, and evaluation is an area of concern for [...]
[...] Methods in Forest Health Diagnosis, Monitoring, and Evaluation Diagnosis Identifying whether the forest of concern is healthy or not and, if unhealthy, what could be the cause of the observed unhealthy condition can be a difﬁcult task. Acute injury on trees is easy to diagnose; on the other hand, nonacute, subtle effects on trees and/or ecosystems can be difﬁcult either to identify in the ﬁeld or to ascribe to a particular cause. In many cases, different factors may interact; depending on the case, an accurate diagnosis needs careful examination of the various potential causal agents and the use of diagnostic criteria and tests. [...]
[...] Evaluation Evaluation approaches and limitations- Evaluation of data generated by forest health monitoring is usually driven by the monitoring approach adopted, the technique used, and the indicator adopted. Usually, data are evaluated in order to identify spatial and/or temporal trends and/or to identify cause-and-effect relationships. Data analysis is subjected to the nature and properties of the data (determined by the sampling design adopted, the metric of the indicator used, and by the frequency distribution of the observations), the comparability of the data (both in space and time) and by the reference adopted, i.e., the deﬁnition of what is to be considered ‘healthy' or ‘normal.' While the data issues can be managed from a technical point of view, the question about ‘health' thresholds is controversial. [...]
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