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Cazzolla Gatti, R.

Publications and source records attributed to Cazzolla Gatti, R..

2 recordsLinked to original sources

A global map of wood density

Wood density influences how quickly woody plants grow, how long they live and how much carbon they store, yet its global variation remains poorly mapped. Here we combined 109,626 wood density measurements from 16,829 species with 300,949 vegetation plots to produce a km-scale map of community-weighted wood density for every woody biome. Our model led to a prediction accuracy 32-51 % higher than previous global products, and a 1.8-3.7-fold wider wood density range (0.28-1.00 g cm-3; global mean: 0.57 g cm-3) than previously assumed. Spatial cross-validation showed low bias ({+/-}2.5 % of the mean), and uncertainties decreased from 20% in poorly sampled drylands and boreal regions to 5% in data-rich temperate forests. Mean annual temperature was the best predictor of community-weighted mean wood density, increasing by 0.01 g cm-3 for every 1{degrees}C change. We deliver a low-bias, high-resolution wood density layer for Earth system models, together with spatially explicit error maps. This study represents a major step forward for carbon accounting and trait-based forecasts of vegetation change.

plant biology↗

Spatial instability affects Key Biodiversity Areas scoping for bumblebees across three decades

Identifying potential Key Biodiversity Areas (KBAs) using species occurrence records is crucial for integrating hyperdiverse taxa, such as insects, into the KBA network. To ensure the KBA network supports effective conservation decision-making, established KBAs need to be reassessed every 8 to 12 years. Realistically, reassessments for very high numbers of species will be based also on opportunistic occurrence points. However, how changes in species distribution data availability and completeness in different time periods influence the spatial stability of potential KBAs over time has not been investigated in any taxa yet. We performed potential KBA assessments for 28 species and subspecies of bumblebees in Italy using an expert-validated dataset of distribution data collected between 1990 and 2023, using 10-year cumulative and progressive time series. Our findings reveal that KBA scoping for species with distributional knowledge gaps does not ensure stability and reliability over time. Potential KBA turnover percentages between different time periods can be high ([~=]133%). While only seven species/subspecies could trigger potential KBAs, their turnover percentage ranged between 28.5% and 50%. We highlight the need for standardized and strategic monitoring of established KBAs and species distributions between reassessments. We also discuss strategies to optimize monitoring plans under resource constraints.

ecology↗