scholarly journals What Are Intermediate-Severity Forest Disturbances and Why Are They Important?

Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 579 ◽  
Author(s):  
Justin Hart ◽  
Jonathan Kleinman
Keyword(s):  
Forest Ecosystem ◽  
Forest Disturbance ◽  
Spatial Extent ◽  
Ecosystem Change ◽  
Forest Disturbances ◽  
Height Ratio ◽  
Catastrophic Events ◽  
Canopy Opening ◽  
Disturbance Processes

The classification of discrete forest disturbance events is usually based on the spatial extent, magnitude, and frequency of the disturbance. Based on these characteristics, disturbances are placed into one of three broad categories, gap-scale, intermediate-severity, or catastrophic disturbance, along the disturbance classification gradient. We contend that our understanding of disturbance processes near the endpoints of the disturbance classification gradient far exceeds that of intermediate-severity events. We hypothesize that intermediate-severity disturbances are more common, and that they are more important drivers of forest ecosystem change than is commonly recognized. Here, we provide a review of intermediate-severity disturbances that includes proposed criteria for categorizing disturbances on the classification gradient. We propose that the canopy opening diameter to height ratio (D:H) be used to delineate gap-scale from intermediate-severity events and that the threshold between intermediate and catastrophic events be based on the influence of residual trees on the composition of the regeneration layer. We also provide examples of intermediate-severity disturbance agents, return intervals for these events, and recommendations for incorporating natural intermediate-severity disturbance patterns in silvicultural systems.

scholarly journals Gangguan Hutan di KPH Kuningan Divisi Regional Jawa Barat dan Banten

2019 ◽  
Vol 10 (3) ◽  
pp. 159-165
Author(s):  
Ati Dwi Nurhayati ◽  
Liana Arhami
Keyword(s):  
Forest Fires ◽  
Forest Disturbance ◽  
Forest Products ◽  
Forest Disturbances ◽  
Community Based ◽  
Forest Protection ◽  
Pests And Diseases ◽  
Legal Remedies ◽  
Preventive Actions ◽  
And Control

Forest protection is an effort to prevent and control the destruction of forests, forest areas, and forest products caused by human actions, livestock, fires, pests and diseases. The aims of this research are to identify the types of forest disturbance especially those caused by humans and physically, analyze the factors causing forest disturbance, and analyze efforts to control forest disturbance at KPH Kuningan. Forest disturbances that occurred in the KPH Kuningan during 2010-2014 included: timber theft, forest fires, forest encroachment, and natural disasters. The background of forest disturbance in the Kuningan KPH is mainly due to the socio-economic conditions of the community around the forest that are still low. Strategic actions taken to prevent forest disturbance at the KPH Kuningan are to take pre-emptive actions in the form of counseling and establish good relations between officers and the community through social communication and Community Based Forest Management (PHBM), preventive actions in the form of patrols and safeguards against forest potential, and repressive actions in the form of legal remedies against the perpetrators. Key words: cause of forest disturbance, type of forest disturbance, forest disturbance control

Phenology Modelling and Forest Disturbance Mapping with Sentinel-2 time series in Austria

2020 ◽  
Author(s):  
Markus Löw ◽  
Koukal Tatjana
Keyword(s):  
Time Series ◽  
Bark Beetle ◽  
Forest Ecosystems ◽  
Forest Disturbance ◽  
Spatial Scales ◽  
Data Access ◽  
Forest Monitoring ◽  
Forest Disturbances ◽  
Disturbance Dynamics ◽  
Sentinel 2

Abstract Background Worldwide, forests provide natural resources and ecosystem services. However, forest ecosystems are threatened by increasing forest disturbance dynamics, caused by direct human activities or an altering natural environment. It is decisive to trace the intra- to trans-annual dynamics of these forest ecosystems. National to local forest communities request detailed area-wide maps that delineate forest disturbance dynamics at various spatial scales. Methods We developed a remote sensing based time series analysis (TSA) framework that comprises data access, data management, image pre-processing, and an advanced but flexible TSA. The data basis is a dense time series of multispectral Sentinel-2 images with a spatial resolution of 10 metres. We use a dynamic Savitzky-Golay-filtering approach to reconstruct robust but sensitive phenology courses. Deviations from the latter are further used to derive spatiotemporal information on forest disturbances. In a first case study, we apply the TSA to map forest disturbances directly or indirectly linked to recurring bark beetle infestation in Northern Austria. Finally, we use zonal statistics on different spatial scales to provide aggregated information on the extent of forest disturbances between 2018 and 2019.Results and Conclusion The outcomes are a) individual phenology models and deduced phenology metrics for each 10 metres by 10 metres forest pixel in Austria and b) forest disturbance maps useful to investigate the occurrence, development and extent of bark beetle infestation. The phenology modelling results provide area-wide consistent data, also useful for downstream analyses (e.g. forest type classification). Results of the forest disturbance detection demonstrate that the TSA is capable to systematically delineate disturbed forest areas. Information derived from such a forest monitoring tool is highly relevant for various stakeholders in the forestry sector, either for forest management purposes or for decision-making processes on different levels.

scholarly journals Characterizing over Four Decades of Forest Disturbance in Minnesota, USA

Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 362 ◽  
Author(s):  
Jody Vogeler ◽  
Robert Slesak ◽  
Patrick Fekety ◽  
Michael Falkowski
Keyword(s):  
Time Series ◽  
Spatial Information ◽  
Forest Disturbance ◽  
Temporal Trends ◽  
Land Protection ◽  
Commission Errors ◽  
Protection Information ◽  
Disturbed Forest ◽  
Agent Of Change

Spatial information about disturbance driven patterns of forest structure and ages across landscapes provide a valuable resource for all land management efforts including cross-ownership collaborative forest treatments and restoration. While disturbance events in general are known to impact stand characteristics, the agent of change may also influence recovery and the supply of ecosystem services. Our study utilizes the full extent of the Landsat archive to identify the timing, extent, magnitude, and agent, of the most recent fast disturbance event for all forested lands within Minnesota, USA. To account for the differences in the Landsat sensors through time, specifically the coarser spatial, spectral, and radiometric resolutions of the early MSS sensors, we employed a two-step approach, first harmonizing spectral indices across the Landsat sensors, then applying a segmentation algorithm to fit temporal trends to the time series to identify abrupt forest disturbance events. We further incorporated spectral, topographic, and land protection information in our classification of the agent of change for all disturbance patches. After allowing two years for the time series to stabilize, we were able to identify the most recent fast disturbance events across Minnesota from 1974–2018 with a change versus no-change validation accuracy of 97.2% ± 1.9%, and higher omission (14.9% ± 9.3%) than commission errors (1.6% ± 1.9%) for the identification of change patches. Our classification of the agent of change exhibited an overall accuracy of 96.5% ± 1.9% with classes including non-disturbed forest, land conversion, fire, flooding, harvest, wind/weather, and other rare natural events. Individual class errors varied, but all class user and producer accuracies were above 78%. The unmatched nature of the Landsat archive for providing comparable forest attribute and change information across more than four decades highlights the value of the totality of the Landsat program to the larger geospatial, ecological research, and forest management communities.

Forest Disturbance Mapping with Sentinel-2 Time Series in Austria

2021 ◽  
Author(s):  
Markus Löw ◽  
Tatjana Koukal
Keyword(s):  
Time Series ◽  
Forest Management ◽  
Time Series Analysis ◽  
Bark Beetle ◽  
Management Practices ◽  
Forest Ecosystems ◽  
Forest Disturbance ◽  
Spatial Scales ◽  
Forest Disturbances ◽  
Sentinel 2

<p>Worldwide, forests provide natural resources and ecosystem services. However, forest ecosystems are threatened by increasing forest disturbance dynamics, caused by direct human activities or by altering environmental conditions. It is decisive to reconstruct and trace the intra- to transannual dynamics of forest ecosystems. Therefore, the monitoring of large and small scale vegetation changes such as those caused by natural events (e.g., pest infestation, higher mortality due to altering site conditions) or forest management practices (e.g., thinning or selective timber extraction) becomes more and more crucial. National to local forest authorities and other stakeholders request detailed area-wide maps that delineate forest disturbance dynamics at various spatial scales.</p><p>We developed a time series analysis (TSA) framework that comprises data download, data management, image preprocessing and an advanced but flexible TSA. We use dense Sentinel-2 time series and a dynamic Savitzky–Golay-filtering approach to model robust but sensitive phenology courses. Deviations from the phenology models are used to derive detailed spatiotemporal information on forest disturbances. In a first case study, we apply the TSA to map forest disturbances directly or indirectly linked to recurring bark beetle infestation in Northern Austria.</p><p>In addition to spatiotemporal disturbance maps, we produce zonal statistics on different spatial scales that provide aggregated information on the extent of forest disturbances between 2018 and 2019. The outcomes are (a) area-wide consistent data of individual phenology models and deduced phenology metrics for Austrian forests and (b) operational forest disturbance maps, useful to investigate and monitor forest disturbances, for example to facilitate sustainable forest management.</p><p>At a forest stand level, we reconstruct the origin date of forest disturbances (FDD – Forest Disturbance Date). Theses FDD outputs show the spatiotemporal patterns and the development of damages and indicate that most dynamics are caused by recurring and spreading bark beetle infestation. The validation results based on field data confirm a high detection rate and show that the derived temporal information is reliable. In total, 23400 hectares, i.e., on average 2.8% of the forest area in the study area, are found to be affected by forest disturbance. The zonal statistic maps point out hotspots of significant forest disturbances, where adequate forest management measures are highly needed. Furthermore, this study highlights the TSA’s potential to also depict and monitor minor human impacts on forests, such as thinning, selective timber extraction or other moderate forest management practices.</p><p><strong>Keywords:  </strong><em>forest disturbance; forest monitoring; bark beetle infestation; forest management; time series analysis; phenology modelling; remote sensing; satellite imagery; Sentinel-2</em></p>

Boreal forest ecosystem dynamics. I. A new spatial model

2000 ◽  
Vol 30 (6) ◽  
pp. 998-1009 ◽  
Author(s):  
John Yarie
Keyword(s):  
Forest Ecosystem ◽  
Picea Glauca ◽  
Forest Growth ◽  
Ecosystem Dynamics ◽  
Spatial Context ◽  
Ecosystem Functions ◽  
Individual Tree ◽  
Microbial Efficiency ◽  
State Factor

Modeling the biology of forest ecosystems has been devoted to a combination of theoretical and empirical approaches representing the function of a forest ecosystem generally within an undefined spatial context. Moving to a large spatial context will require the use of theoretical representations of critical ecosystem functions that can be represented on an individual cell basis. A Spatial Alaskan Forest Ecosystem Dynamics (SAFED) model was developed that is based on the nitrogen productivity concept for forest growth, litter fall quality, and microbial efficiency for forest floor decomposition. Climate and ecosystem disturbances were handled as restricted stochastic processes. The restriction was based on known state-factor relationships. The state factors are used to describe a broad-scale classification of the landscape to define basic limitations for the randomly derived driving variables used in the model. The model has been programed as ARC/INFO macro language within the GRID package. The current version of the model has been verified as functional from an individual tree basis (1-m2 cell size) within an old-growth white spruce (Picea glauca (Moench) Voss) forest found in interior Alaska.

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