Topography affects the natural forest recovery on inland dunes in Central Europe

2023-10-16T12:02:18+00:00

Topography, by spatially altering site conditions, affects ecological processes, e.g. natural forest recovery. Until now the early dynamics of naturally encroaching trees on inland dunes with regard to topography has not been sufficiently studied in detail, and became the aim of our study. To achieve this aim, in 2011 we established a 14.87 ha long-term research site located in the Toruń artillery ground (N Poland), in one of the biggest inland dune fields of Central Europe. We surveyed twice (2011 and 2021) trees occurring in the site, and investigated their characteristics (GPS coordinates, height, diameter, age, annual stem increment, slenderness) regarding 5 topographical variants: north- (N), east- (E), west- (W), and south-facing (S) slopes, as well as intra-dune depressions (D). We found that within the investigated 10 years timespan the number of trees increased almost fourfold (from 560 to 2016). The natural encroaching of trees was the most advanced in north-facing slopes (88 ± 17 and 352 ± 89 trees ha-1 in 2011 and 2021, respectively). In turn, in sunny exposures and in intra-dune depressions the process was the least advanced (in 2021: 64 ± 21 and 25 ± 15 trees ha-1, respectively), which could be primarily linked to unfavourable moisture conditions occurring on south-facing slopes, and strong competitive effect of tall grasses on young trees regarding the depressions. By showing the rate and topographically controlled spatial pattern of trees encroachment, our study can be useful e.g. for practising managers when reforestation of inland dunes by natural means is planned.

Integration of Terrestrial Laser Scanning and field measurements data for tree stem volume estimation: Exploring parametric and non-parametric modeling approaches

2024-06-05T05:40:46+00:00

Terrestrial laser scanning (TLS) has emerged as a powerful tool for acquiring detailed three-dimensional information about tree species. This study focuses on the development of models for tree volume estimation using TLS data for even aged Fagus sylvatica L. stands located in the western part of the Southern Carpathians, Romania. Both parametric and non-parametric modeling approaches were explored, leveraging variables extracted from TLS point clouds such as diameter at breast height (DBH), height, crown radius, and other relevant crown and height parameters. Reference data were collected through high-precision field measurements across 76 circular Permanent Sample Areas (PSA) spanning 500 m² each. A multi-scan approach was implemented for TLS data collection, involving four scanning stations within each PSA. Concurrently, parametric (regression equations) and non-parametric (Random Forest - RF) models were applied, leveraging all TLS-derived variables to explore potential enhancements in volume estimation accuracy. Among the parametric models, the most effective performer was the one featuring solely DBH as an input variable. The RF non-parametric model yielded more accurate stem volume estimates (RMSE = 1.52 m³*0.1ha^-1; RRMSE = 3.62%; MAE = 1.22m³*0.1ha^-1) compared to the best-performing regression model (RMSE = 5.24 m³*0.1ha^-1; RRMSE = 12.48%; MAE = 4.28 m³*0.1ha^-1). Both types of models identified DBH as the most important predictive variable, while the RF model also included height and crown related parameters among the variables of importance. Results demonstrate the effectiveness of the non-parametric RF model in providing accurate and robust estimates of tree stem volume within even aged European beech stands. This highlights the significance of TLS data, increasingly employed in diverse forest inventory and management applications. Nevertheless, additional research and refinement of the proposed models are needed. This includes thorough validation across various forest ecosystems and continued efforts to enhance the accuracy of tree height determination from point cloud data.

Annals of Forest Research

Topography affects the natural forest recovery on inland dunes in Central Europe

Integration of Terrestrial Laser Scanning and field measurements data for tree stem volume estimation: Exploring parametric and non-parametric modeling approaches