The impacts of partial cuts on carbon stocks remain uncertain due to elevated post-harvest windthrow mortality that may counteract the positive effects of thinning on stand growth. This study evaluated the effects of partial cuts and tree mortality on aboveground carbon stocks eight years after harvest in jack pine forests. The experimental design included 24 sites with varying harvest intensities: unharvested control, moderate (30–35 %), and heavy (40–50 %) thinnings. Dendrochronological analyses and allometric equations were used to quantify carbon in live and dead biomass (snags, broken, and uprooted trees). Increases in individual tree carbon stocks between the pre-harvest year and the eighth year post-harvest were lower in controls and similar among partial cut treatments. Eight years after harvest, live carbon stocks per hectare were 41 % lower in the heavy thinning than in unharvested stands but remained similar between moderate thinning and control treatments. Larger trees and those growing closer to skidding trails showed greater increases in carbon stock, with the latter exhibiting a 33 % higher increase on average. Mean total deadwood carbon stocks were 55 % higher in the control than in the partial cuts due to reduced snag carbon in harvested stands. Uprooting was influenced by harvest treatment and proximity to skidding trails, while stem breakage was driven by tree characteristics (height, age, and competition) and distance to trails. The proportion of snags was explained by mean annual wind speed. These findings suggest that moderate thinning could sustain forest carbon stocks with prescriptions aiming at maintaining snag carbon stocks.

Abstract Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost-effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision-makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time-consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047?min of audio files annotated to species-level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species-based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.