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68 results for “forest resilience”

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dryad32/100

Mexican mixed-species forest shows resilience to high-intensity fire

In the aftermath of a high-intensity wildfire in La Michilía Biosphere Reserve, Mexico, an initial study suggested a shift from an oak-pine forest to a grass-savanna ecosystem. We conducted repeated measurements on sixty permanent plots 1, 5, 10, and 20 years after the original wildfire at paired burned and unburned study sites to capture spatial and temporal dynamics in forest composition and structure. We found that the burned site regained most pre-wildfire characteristics two decades after the wildfire. The ongoing regeneration in the burned site suggests that despite the remaining differences, the site is approaching a complete recovery, with forest characteristics analogous to the unburned site. Our findings indicate that the combination of seeders' wildfire resistance and resprouters' post-wildfire sprouting strategies in mixed-species forests provide high resilience to high-intensity wildfire. Moreover, protecting La Michilía as a biosphere reserve and heightened public awareness of the natural environment likely played an indispensable role in facilitating the recovery of the post-wildfire ecosystem.

opencc-zeroNov 2023View details →

zenodo32/100

Code to run the analyses of "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Barrere et al. (2024).

Repository containing the code to run the model and statistical analyses of the paper "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Julien Barrere, Björn Reineking, Maxime Jeaunatre and Georges Kunstler, accepted by Functional Ecology in 2024. The code requires prior installation of the <a href="https://github.com/gowachin/matreex">matreex</a> R package, developped by Maxime Jeaunatre (INRAE), and of the ```targets``` package. The data folder, required to run the code, can be made available upon request to julienbarrere3@gmail.com Once the packages are installed and the data folder is placer in the main folder, just run ```targets::tar_make()``` from R and the script will download the other packages required and run the analyses. A version of this code is also available in the github <a href="https://github.com/jbarrere3/FunDiv_ipm">repository</a>

opencc-by-4.0Nov 2023View details →

dryad32/100

Restoration priorities for Caatinga dry forests: landscape resilience, connectivity and biodiversity value

1. Restoration actions can halt biodiversity loss and rescue its services. However, in order to be effective, priority areas for restoration should be chosen based on objective large-scale restoration planning. Here, a multi-criteria graph theory (GT) framework is proposed to indicate priority areas for active restoration, based on landscape resilience, landscape connectivity, and biodiversity conservation value, focusing on threatened endemic plant species. 2. We applied this GT framework to 10,406 catchment basins of the Brazilian Caatinga, the largest seasonally dry tropical forest of the New World. Vegetation cover and within-catchment connectivity were used to identify catchments of intermediate landscape resilience, which in principle offer more effective opportunities for restoration. Then, such catchments were independently classified into (i) three classes according their value for between-catchment connectivity and (ii) three classes of biodiversity conservation value, based on richness of threatened, endemic plant species. By the integration of landscape resilience, landscape connectivity and biodiversity conservation values, three priority classes for restoration were generated. 3. The multi-criteria framework generated several restoration priority cut-offs. Prioritization based on landscape resilience selected 36% of the Caatinga catchments as high priority for restoration. By independently adding landscape connectivity and biodiversity conservation value, only 12% and 3% of the catchments, respectively, were considered high priority. By combining all three criteria, 9% of the catchments were selected as high priority and less than 1% as top priority for restoration. 4. Synthesis and applications: The multicriteria GT framework for restoration prioritization, which maximizes the effectiveness of restoration actions, landscape connectivity for climate change adaptation and conservation of threatened species, can be applied worldwide under different budged limitations and spatial scales, being useful for private, state, and federal initiatives.

opencc-zeroFeb 2022View details →

dryad32/100

Targeted grazing and mechanical thinning enhance forest stand resilience under a narrow range of wildfire scenarios

Increasing wildfire activity has spurred ecological resilience-based management that aims to reduce the vulnerability of forest stands to wildfire by reducing the probability of crown fire. Targeted grazing is increasingly being used to build forest resilience to wildfire, either on its own or in combination with treatments like mechanical thinning; however, it is unclear how effective this method is at altering the probability of crown fire in forest stands. We use crown fire simulation models to quantify to what extent targeted grazing, mechanical thinning targeting the vertical fuel stratum, and a combination of both treatments alter eastern ponderosa pine savanna stand resilience to wildfire by modelling their relative impacts on fuel stratum gap and subsequent crown fire occurrence under six different wildfire risk scenarios generated by altering wind and fuel moisture conditions. We then model changes in the probability of crown fire occurrence resulting from treatments across 75 field-sampled sites in the Pine Ridge region of Nebraska relative to predicted crown fire occurrence when sites are left untreated. We find that mechanical (vertical) thinning has the potential to alter the probability of crown fire in ponderosa pine stands to a much greater extent than targeted grazing. Combining both approaches had a slightly higher probability of reducing crown fire risk across the greatest range of wildfire risk scenarios. Across 75 sample sites, targeted grazing was only predicted to prevented crown fire occurrence at 2 sites expected to experience crown fire under observed stand conditions across all six of our wildfire risk scenarios. In contrast, targeted grazing combined with mechanical thinning was predicted to prevent crown fire at approximately half of the sites expected to experience crown fire under observed conditions under mild and moderate wildfire risk scenarios. Thus, targeted grazing should be combined with mechanical thinning to best enhance forest resilience to wildfire. No combination of targeted grazing or mechanical thinning was able to alter the probability of crown fire under wildfire risk scenarios most conducive wildfire, confirming that relying solely on vertical thinning and targeted grazing is unlikely to sufficiently enhance resilience of forest stands to future wildfire conditions.

opencc-zeroFeb 2022View details →

dryad32/100

Monitoring resistance and resilience using carbon trajectories: analysis of forest management-disturbance interactions

A changing climate is altering ecosystem carbon dynamics with consequences for natural systems and human economies, but there are few tools available for land managers to meaningfully incorporate carbon trajectories into planning efforts. To address uncertainties wrought by rapidly changing conditions, many practitioners adopt resistance and resilience as ecosystem management goals, but these concepts have proven difficult to monitor across landscapes. Here, we address the growing need to understand and plan for ecosystem carbon with concepts of resistance and resilience. Using time series of carbon fixation (n=103), we evaluate forest management treatments and their relative impacts on resistance and resilience in the context of an expansive and severe natural disturbance. Using subalpine spruce-fir forest with a known management history as a study system, we match metrics of ecosystem productivity (net primary production, g·C·m2·y-1) with site-level forest structural measurements to evaluate (1) whether past management efforts impacted forest resistance and resilience during a spruce beetle (Dendroctonus rufipennis) outbreak, and (2) how forest structure and physiography contribute to anomalies in carbon trajectories. Our analyses have several important implications. First, we show that the framework we applied was robust for detecting forest treatment impacts on carbon trajectories, closely tracked changes in site-level biomass, and was supported by multiple evaluation methods converging on similar management effects on resistance and resilience. Second, we found that stand species composition, site productivity, and elevation predicted resistance, but resilience was only related to elevation and aspect. Our analyses demonstrate application of a practical approach for comparing forest treatments and isolating specific site and physiographic factors associated with resistance and resilience to biotic disturbance in a forest system, which can be used by managers to monitor and plan for both outcomes. More broadly, the approach we take here can be applied to many scenarios, which can facilitate integrated management and monitoring efforts.

opencc-zeroMay 2022View details →

zenodo32/100

A trait-based approach to both forestry and timber building can synchronize forest harvest and resilience: Supporting data

Input files and trait data used in the associated paper. They can be used to reproduce the results of the study. The model documentation is freely available at <a href="https://www.landis-ii.org/">https://www.landis-ii.org/</a> The LANDIS-II code is distributed under an open source license at <a href="https://github.com/LANDIS-II-Foundation">https://github.com/LANDIS-II-Foundation</a>. If interested in using this dataset for a research study or project, please contact <a href="https://www.marco-mina.com/">P</a><a href="mailto:peter.osborne@mail.mcgill.ca?subject=QUESTION%3A%20A%20trait-based%20approach%20to%20both%20forestry%20and%20timber%20building%20can%20synchronize%20forest%20harvest%20and%20resilience%20%20">eter Osborne</a> --------------------- ABSTRACT: Along with forest managers, builders are key change agents of forest ecosystems' structure and composition through the specification and use of wood products. New forest management approaches are being advocated to increase the resilience and adaptability of forests to climate change and other natural disturbances. Such approaches call for a diversification of our forests based on species' functional traits that will dramatically change the harvested species composition, volume and output of our forested landscapes. This calls for the wood-building industry to adapt its ways of operating. Accordingly, we expand the evaluation of the ecological resilience of forest ecosystems based on functional diversification to include a trait-based approach to building with wood. This trait-based plant-building framework can illustrate how forecasted forest changes in the coming decades may impact and guide decisions about wood-building practices, policies and specifications. We apply this approach using a fragmented rural landscape in temperate southeastern Canada. We link seven functional groups based on the ecological traits of tree species in the region to a similar functional grouping of building traits to characterize the push and pull of managing forests and wood buildings together. We relied on a process-based forest landscape model to simulate long-term forest dynamics and timber harvesting to evaluate how various novel management approaches will interact with the changing global environment to affect the forest-building relationships. Our results suggest that adopting a whole system, plant-building approach to forests and wood buildings is key to enhancing forest ecological and timber construction industry resilience.

opencc-by-4.0Jul 2023View details →

dryad32/100