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opencc-by-4.0Apr 2024View details →

The conservation burden of Intact Forest Landscapes (IFLs): A global database of management units and IFLs

Introduction This dataset includes a global overview of publicly available forest Management Units (MUs), Intact Forest Landscapes (IFLs) and their overlap. This includes both the boreal forests of Canada and Russia, and the tropical forests in the Amazon, the Congo basin, South-East Asia. The dataset was developed for the paper "Feasibility and effectiveness of global Intact Forest Landscape protection through forest certification: The conservation burden of Intact Forest Landscapes" by Zwerts et al. (2024). A comprehensive list of MUs with % and absolute overlap with IFLs is presented in Table S1 of Zwerts et al. (2024). Data collection We collected and collated all publicly available MU and IFL data of Central Africa, Southeast Asia, the Amazon, and of the boreal forests in Canada and Russia. As such, we included MU data from Cameroon, Canada, the Central African Republic, the Democratic Republic of Congo, Equatorial Guinea, Gabon, Indonesia, Malaysia, the Republic of Congo and Russia. Together, these forests comprise the majority of all IFLs (Potapov et al., 2017). We utilized the 2020 intact forest landscape (IFL) dataset generated by Potapov et al. (2017). Both FSC-certified and non-FSC MUs were considered and FSC-certification status data was collected using the FSC public dashboard (FSC, 2023). All data was collected in March 2023. Our dataset is not exhaustive. To our knowledge, not all MU data is publicly available. For Southeast Asia no public MU data is available for Papua New Guinea and Peninsular Malaysia. For the Amazon, insufficient public MU data was available to create an accurate representation of the situation. This area was excluded from the main analysis in Zwerts et al., 2024. We included a distinction between FSC-certified and non-FSC MUs in Russia, even though the FSC has withdrawn all certificates in Russia in April 2023 following the invasion of Ukraine. We chose to retain the distinction between FSC and non-FSC MUs for the Russian data because of the uncertainty of the current situation and the significant influence of FSC-certification in the Russian management of IFLs. Overlap analysis All area was transformed to geodesic distance. Furthermore, several MU names were altered because of duplicate names. The number of hectares of MUs that overlap with IFLs was calculated in ArcGIS Pro 3.0.0, using the WGS_1984_Web_Mercator_Auxiliary_Sphere coordinate system. Using the intersect and multipart to singlepart tools every overlap fragment was isolated. For the results in Zwerts et al. (2024) the total overlap and the percentage of overlap was calculated in R.  Abstract of the related article Intact Forest Landscapes (IFLs) are defined as forested areas of at least 500 km2 that show no signs of remotely sensed human activity. They are considered to be of high conservation value due to their role in maintaining biodiversity and mitigating climate change. In 2014, the members of the Forest Stewardship Council (FSC), one of the major global certification schemes for responsible forest management, took a conservation stand by restricting logging in FSC-certified IFLs. However, this move raised concerns about the economic viability of FSC-certified logging in these areas. To address these challenges, in 2022, FSC proposed an integrated landscape approach, considering local conditions and stakeholders' needs to balance IFL protection, economic sustainability, and community interests. Here, we leverage publicly available management unit (MU) data, to provide a global quantitative overview of IFLs designated for timber production. We use the concept of 'conservation burden' for the extent that MUs overlap with IFLs, representing the impact that IFL protection has on forest management operations if logging is disallowed. Our data indicates that currently FSC-certified MUs affect 0.6% of global IFLs. Too restrictive policies for logging in IFLs may discourage FSC-certification in global IFLs. Considering the environmental and social benefits of FSC certification, it warrants careful examination whether the benefits of protecting a limited subset of FSC-certified IFLs outweighs the cost of potentially reduced growth of the total FSC-certified area. Our data can provide a basis to facilitate stakeholder engagement for landscape-level IFL management.

opencc-by-4.0Nov 2024View details →

Digital repository for: Large-scale forest disturbance and associated management shape bird communities in Central European spruce forests

Repository containing R-script and data to reproduce analysis and main figures on the effect of large-scale forest disturbance and associated pre- and post-disturbance management on bird communities in the Harz Mountains, Germany. R-script includes: <ul> <li>indicator species analysis (R package indicspecies; Cáceres & Legendre, 2009)</li> <li>non-metric multidimensional scaling (R package vegan; Oksanen et al., 2016)</li> <li>rarefaction- and extrapolation of Hill numbers (R package iNEXT; Hsieh et al., 2019)</li> <li>multi-species community distance sampling (R package sp Abundance; Doser et al., 2023)</li> </ul> Attached files: <ul> <li>bird_data_Graser_et_al.csv (row data of bird species point counts per distance category)</li> <li>bird_data_abundance_100_Graser_et_al.csv (abundance of species per sampling site, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>siteCovs_Graser_et_al.csv (environmental variables for each sampling point)</li> <li>A_species_matrix_100_new_Graser_et_al.csv (species-site matrix of bark-beetle disturbance, unlogged sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>B_species_matrix_100_new_Graser_et_al.csv (species-site matrix of windthrow disturbance, unlogged sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>C_species_matrix_100_new_Graser_et_al.csv (species-site matrix of bark-beetle/windthrow disturbance, underplanted, unlogged sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>D_species_matrix_100_new_Graser_et_al.csv (species-site matrix of bark-beetle /windthrow disturbance, salvage-unlogged sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>E_species_matrix_100_new_Graser_et_al.csv (species-site matrix of bark-beetle /windthrow disturbance, underplanted, salvage-unlogged sites for rarefaction and extrapolation, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li> F_species_matrix_100_new_Graser_et_al.csv (species-site matrix of mature spruce plantation sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li>msHDS_bird_data_management_model_Graser_et_al.rds (R-data set for multi-species community distance sampling of the effect of different pre- and post-disturbance management groups)</li> <li>msHDS_bird_data_stand_age_model_Graser_et_al.rds (R-data set for multi-species community distance sampling of the effect of post-disturbance forest succession)</li> </ul> A more detailed description of the data can be found in the README.txt document. References: Cáceres, M. D., & Legendre, P. (2009). Associations between species and groups of sites: Indices and statistical inference. Ecology, 90(12), 3566–3574. https://doi.org/10.1890/08-1823.1 Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2023). spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models. Methods in Ecology and Evolution, 15(6), 1024–1033. https://doi.org/10.1111/2041-210X.14332 Hsieh, T. C., Ma, K. H., & Chao, A. (2019). iNEXT-package: Interpolation and extrapolation for species diversity. https://cran.r-project.org/web/packages/iNEXT/vignettes/Introduction.html Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., O’hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H., Minchin, P. R., Gavin, L., & Henry, H. (2016). Vegan: Community ecology package. R package version 1.17-4. Http://CRAN. R-Project. Org/Package=vegan.

opencc-zeroDec 2021View details →

Simulated treatment effects on bird communities inform landscape‐scale dry conifer forest management

Human land use and climate change have increased forest density and wildfire risk in dry conifer forests of western North America, threatening various ecosystem services, including habitat for wildlife. Government policy supports active management to restore historical structure and ecological function. Information on potential contributions of restoration to wildlife habitat can allow assessment of tradeoffs with other ecological benefits when prioritizing treatments. We predicted avian responses to simulated treatments representing alternative scenarios to inform landscape‐scale forest management planning along the Colorado Front Range. We used data from the Integrated Monitoring in Bird Conservation Regions program to inform a hierarchical multispecies occupancy model relating species occupancy and richness with canopy cover at two spatial scales. We then simulated changes in canopy cover (remotely sensed in 2018) under three alternative scenarios, (1) a "fuels reduction" scenario representing landscape‐wide 30% reduction in canopy cover, (2) a "restoration" scenario representing more nuanced, spatially variable treatments targeting historical conditions, and (3) a reference, no‐change scenario. Model predictions showed areas of potential gains and losses for species richness, richness of ponderosa pine forest habitat specialists, and the ratio of specialists to generalists at two (1 km2 and 250 m2) spatial scales. Under both fuels reduction and restoration scenarios, we projected greater gains than losses for species richness. Surprisingly, despite restoration more explicitly targeting ecologically relevant historical conditions, fuels reduction benefited bird species richness over a greater spatial extent than restoration, particularly in the lower montane life zone. These benefits reflected generally positive species associations with moderate canopy cover promoted more consistently under the fuels reduction scenario. In practice, contemporary forest management is likely to lie somewhere between the fuels reduction and restoration scenarios represented here. Therefore, our results inform where and how active forest management can best support avian diversity. Although our study raises questions regarding the value of including landscape‐scale heterogeneity as a management objective, we do not question the value of targeting finer-scale heterogeneity (i.e., stand and treatment level). Rather, our results combined with those from previous work clarify the scale at which targeting structural heterogeneity and historical reference conditions can promote particular ecosystem services.

opencc-by-4.0Apr 2024View details →

Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors: Dataset

This dataset is linked to the paper “Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors" submitted to Science of The Total Environment.

FIG. 3 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 3. — Co-correspondence analysis biplot illustrating the ordination of most frequent bryophyte species colonizing ground in relation to the statistically significant environmental variables (n=75). Abbreviations: Age, forest age; DBH.max, maximal trees diameter at breast height; DW.vol, dead wood volume; L, Ellenberg indicator value (EIV) for light; T, EIV for temperature; F, EIV for moisture; R, EIV for pH; N, EIV for nitrogen; the first four letters of species indicate genus name, next four indicate species names and next four letters subspecies names.

0.0 0.5 1.0 1.5 RDA 1 FIG. 4 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

0.0 0.5 1.0 1.5 RDA 1 FIG. 4. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree trunks in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=41). Abbreviations as in Fig. 3.

FIG. 6 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 6. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing dead wood in relation to the statistically significant environmental variables for the plots with the presence of decaying logs (n=80). Abbreviations as in Fig. 3

FIG. 5 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 5. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree bases in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=96). Abbreviations as in Fig. 3.

FIG. 2 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 2. — Frequency of occurrence of bryophytes generally and in the four types of substrates considered.

opencc-by-4.0Dec 2019View details →

Fig.6 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy

Fig.6. CO2 emissions in Latvia by sources in 2016, CO2 kt eq (Source: Created by authors after National GHG inventories).

opencc-by-4.0Dec 2019View details →

Fig.2 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy

Fig.2. Scheme of LFSRI Silava changes in forest resources projections process based on Nation Forest Inventory data (Source: LFSRI Silava).

opencc-by-4.0Dec 2019View details →

Fig.1 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy

Fig.1. Policy documents affecting the Climate Change Mitigation policy of the Forest sector by 2020.

opencc-by-4.0Jan 2018View details →

Database of Pines from the Forests paper: "Intraspecific Variation in Pines from the Trans-Mexican Volcanic Belt Grown Under Two Watering Regimes: Implications for Management of Genetic Resources"

Raw data from the Forests paper: "Intraspecific Variation in Pines from the Trans-Mexican Volcanic Belt Grown under Two Watering Regimes: Implications for Management of Genetic Resources" Forests 2018 9(2), 71. doi:<a href="http://dx.doi.org/10.3390/f9020071">10.3390/f9020071. </a> The database correspond to seedlings of four Mexican pines: P. oocarpa, P. patula and P. pseudostrobus, that were submitted to two watering treatments: Field Capacity (FC) and Drought-Stress (DS), during 90 days. Growth and biomass, survival and ontogenetic score were measured.

opencc-by-4.0Sep 2019View details →

Data from: Spatial configuration matters when removing windfelled trees to manage bark beetle disturbances in Central European forest landscapes

The published dataset contains the result of the paper titled Spatial configuration matters when removing windfelled trees to manage bark beetle disturbances in Central European forest landscapes, in Journal of Environmental Management. Two zip files contain maps in ascii format for the total bark beetle and wind damage over 54 simulation year in our study region in Slovakia under reference climate and different climate change scenarios. No- salvaging and 95% salvaging scenarios are shown, just as in the paper. Excel file contains data of the other figures in the paper (main text and appendices as well). See more details about target area, and iLand model: https://www.sciencedirect.com/science/article/pii/S0168192318302946 http://iland.boku.ac.at/startpage contact: Laura Dobor; dobor.laura@gmail.com

opencc-by-4.0Oct 2024View details →

Data and analysis code for Repo et al., "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes"

This repository contains analysis code and pre-processed data for the study "Contrasting forest management strategies: impacts on biodiversity and ecosystem services under changing climate and disturbance regimes" by Repo et al. Data processing and analysis mainly done by Aapo Jantunen, Katharina Albrich Due to respository space limitations, the original model outputs are archived in the Finnish "Allas" data storage service. For access, contact katharina.albrich@luke.fi The code used to process the raw data is included here for reproducibility. If you are interested in using iLand, visit https://iland-model.org/ and https://iland-model.org/iland-book/ for information on using the model and a guide to setting up a landscape. This work was supported by the Ministry of Agriculture and Forestry by funding project Future multifunctional forests and their disturbance risk in the changing climate (Foster) through the “Catch the Carbon” initiative (project number VN/28654/2020). A.R. has been supported by the grant [TRACY Trade-offs and synergies in land-based climate change mitigation and biodiversity conservation decision 322066 by the Academy of Finland.], J. H by the grant [CASCADE - Changing Disturbance Regimes and Forest Landscapes of Fennoscandia 342569 by the Academy of Finland].

opencc-by-4.0Jun 2021View details →

Data set: Forest management to increase carbon sequestration in boreal Pinus sylvestris forests

Data supporting the results and analyses published in Plant and Soil, "Forest management to increase carbon sequestration in boreal Pinus sylvestris forests". Data from a long-term fertilization (N and N+P) and thinning experiment in Pinus sylvestris stands across Sweden (56–67°N). Carbon stocks in soil and trees, tree growth, soil respiration and soil available nitrogen (ammonium, nitrate) are included. Data (data file + meta data file) include: jorgensen_etal_plantsoil_treesoil_data.csv (site data, carbon stocks: trees and their separate parts and soil, soil available nitrogen) jorgensen_etal_plantsoil_treesoil_data_METADATA.csv jorgensen_etal_plantsoil_resp_data.csv (site data, soil respiration, temperature, moisture) jorgensen_etal_plantsoil_resp_data_METADATA.csv R-script: Jorgensen_etal_plantsoil.R

opencc-by-4.0May 2019View details →

Data and code for: Roost selection by male northern long-eared bats (Myotis septentrionalis) in a managed fire-adapted forest

Data and code for: Roost selection by male northern long-eared bats (Myotis septentrionalis) in a managed fire-adapted forest

opencc-zeroJan 2023View details →

Data from: Wind turbines in managed forests partially displace common birds

Wind turbines are increasingly being installed in forests, which can lead to land use disputes between climate mitigation efforts and nature conservation. Environmental impact assessments precede the construction of wind turbines to ensure that wind turbines are installed only in managed or degraded forests that are of potentially low value for conservation. It is unknown, nevertheless, if animals deemed of minor relevance in environmental impact assessments are affected by wind turbines in managed forests. We investigated the impact of wind turbines on common forest birds, by counting birds along an impact-gradient of wind turbines in 24 temperate forests in Hesse, Germany. During 860 point counts, we counted 2,231 birds from 45 species. Bird communities were strongly related to forest structure, season and the rotor diameter of wind turbines, but were not related to wind turbine distance. For instance, bird abundance decreased in structure-poor (-38%) and monocultural (-41%) forests with wind turbines, and in young (-36%) deciduous forests with larger and more wind turbines (-24%). Overall, our findings suggest that wind turbines in managed forests partially displace common forest birds. If these birds are displaced to harsh environments, wind turbines might indirectly contribute to a decline of their populations. Yet, forest bird communities are locally more sensitive to forest quality than to wind turbine presence. To prevent further displacement of forest animals, forests of lowest quality for wildlife should be preferred in spatial planning for wind turbines, for instance small and structure-poor monocultures along highways.

publicJan 2023View details →

Simulated treatment effects on bird communities inform landscape‐scale dry conifer forest management

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