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Publications and references

Calls for Submission of Manuscripts

Special issue on Spatial Decision Support for Forest Management and Policy Formulation

Aims and scope
Decision support systems for forest management have been steadily evolving since about 1980 in response to growing demand from forest managers for sophisticated analytical systems that can address the complexities of contemporary forest management issues such as adaptive management in the context of concerns for managing for forest ecosystem sustainability, integrity, and resilience while ensuring the provision of ecosystem services. In this same time frame, there has also been a steady shift in emphasis from stand-level to landscape-level decision support systems, in part driven by improved ecological understanding of, and appreciation for, the need to account for patterns and processes in forest management and planning. Accordingly, the Editors of Forests have commissioned a 2021 special issue on spatial decision support systems and their application to state-of-the-art landscape solutions for forest management and policy formulation.

Journal:  Forests
Deadline19 September 2021
More information at: 

Wildfire Management and Decision Support

Aim and Scope
The severity of forest fires has increased substantially worldwide. This severity is prone to increase as a consequence of global change, e.g. climate and socioeconomic change. This suggests the need for the development of a coherent wildfire risk management strategy. This poses a challenge to forest researchers and managers as this strategy calls for methods and tools to help integrate forest and fire management planning activities that are often carried out independently of each other. This Research Topic aims to bring together multidisciplinary expertise on wildfire management and forest ecosystem management to report state-of-the-art research that may help address this challenge. In this context, the Research Topic will focus on decision methods and tools that may support a) the characterization of wildfire regimes, b) the understanding of extreme wildfire events, c) the assessment of impacts of wildfire risk on the provision of ecosystem services, d) the enhancement of wildfire prevention, wildfire suppression, and post-fire restoration processes and e) the effectiveness of wildfire risk management strategies.

Deadlines for submission:
- Abstracts: 29 January 2021
- Manuscripts: 31 May 2021  

  • Shao, G., and K.M. Reynolds (eds.). 2006. Computer applications in sustainable forest management. New York: Springer.
  • Reynolds, K., A. Thomson, M. Köhl, S. Shannon, D. Ray, and K. Rennolls (eds.) 2007. Sustainable forestry in theory and practice. Wallingford, UK: CABI Publishing.
  • Reynolds, K.M., P.F. Hessburg, and P.S. Bourgeron (eds). 2014. Making Transparent Environmental Management Decisions: Applications of the Ecosystem Management Decision Support System. Berlin: Springer.
  • Laikcevic, M., N. Povak, and K.M. Reynolds. 2019. Introduction to R for Terrestrial Ecology. Berlin: Springer.
  • Strimbu BM, Qi C, Sessions J 2019. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices. Remote Sensing 11(16): 1877-1897
  • Maturbong B, Wing M, Strimbu BM, Burnett M. 2019. Forest inventory sensitivity to UAS-based image processing algorithms. Annals of Forest Research  62(1)
  • Fang R. and Strimbu B.M. 2019 Comparison of Mature Douglas-Firs’ Crown Structures Developed with Two Quantitative Structural Models Using TLS Point Clouds for Neighbouring Trees in a Natural Regime Stand Remote Sensing 11(14): 1661-1687 2018
  • Strimbu BM, Paun M, Popescu SC, Montes C. 2018. A scalar measure tracing tree species composition in space or time. Physica A: Statistical Mechanics and its Applications 512: 682-692
  • Strimbu, B. M., A. Amarioarei, and M. Paun. 2017. A parsimonious approach for modeling uncertainty within complex nonlinear relationships. Ecosphere 8(9):e01945. 10.1002/ecs2.1945