Dataset Information

Using lidar to assess the development of structural diversity in forests undergoing passive rewilding in temperate Northern Europe.

ABSTRACT: Forested areas are increasing across Europe, driven by both reforestation programs and farmland abandonment. While tree planting remains the standard reforestation strategy, there is increased interest in spontaneous regeneration as a cost-effective method with equal or potentially greater benefits. Furthermore, expanding areas of already established forests are left for passive rewilding to promote biodiversity conservation. Effective and objective methods are needed for monitoring and analyzing the development of forest structure under these management scenarios, with airborne laser scanning (lidar: light detection and ranging) being a promising methodology. Here, we assess the structural characteristics and development of unmanaged forests and 28- to 78-year old spontaneously regenerated forests on former agricultural land, relative to managed forests of similar age in Denmark, using 25 lidar-derived metrics in 10- and 30-m grid cells. We analyzed the lidar-derived cell values in a principal component analysis (PCA) and interpreted the axes ecologically, in conjunction with pairwise tests of median and variance of PCA-values for each forest. Spontaneously regenerated forest in general had increased structural heterogeneity compared to planted and managed forests. Furthermore, structural heterogeneity kept increasing in spontaneously regenerated forest across the maximal 78-year timespan investigated. Natural disturbances showed strong impacts on vegetation structure, leading to both structural homogeneity and heterogeneity. The results illustrate the utility of passive rewilding for generating structurally heterogeneous forested nature areas, and the utility of lidar surveys for monitoring and interpreting structural development of such forests.

SUBMITTER: Thers H

PROVIDER: S-EPMC6336013 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The spatial patterns of biodiversity and their underlying mechanisms have been an active area of research for a long time. In this study, a total of 63 samples (20m × 30m) were systematically established along elevation gradients on Mount Tai and Mount Lao, China. We explored altitudinal patterns of plant diversity in the two mountain systems. In order to understand the mechanisms driving current diversity patterns, we used phylogenetic approaches to detect the spatial patterns of phylogenetic diversity and phylogenetic structure along two elevation gradients. We found that total species richness had a monotonically decreasing pattern and tree richness had a unimodal pattern along the elevation gradients in the two study areas. However, altitudinal patterns in shrub richness and herbs richness were not consistent on the two mountains. At low elevation, anthropogenic disturbances contributed to the increase of plant diversity, especially for shrubs and herbs in understory layers, which are more sensitive to changes in microenvironment. The phylogenetic structure of plant communities exhibited an inverted hump-shaped pattern along the elevation gradient on Mount Tai, which demonstrates that environmental filtering is the main driver of plant community assembly at high and low elevations and inter-specific competition may be the main driver of plant community assembly in the middle elevations. However, the phylogenetic structure of plant communities did not display a clear pattern on Mount Lao where the climate is milder. Phylogenetic beta diversity and species beta diversity consistently increased with increasing altitudinal divergence in the two study areas. However, the altitudinal patterns of species richness did not completely mirror phylogenetic diversity patterns. Conservation areas should be selected taking into consideration the preservation of high species richness, while maximizing phylogenetic diversity to improve the potential for diversification in the future.

Project description:An important challenge for silvicultural practices is the conservation of tree diversity while fulfilling the traditional objectives of forest management, most notably timber harvesting. The purpose of this study was to compare the tree diversity before and after the application of silvicultural treatments in a temperate forest in northern Mexico. Fifteen experimental plots, each measuring 2500 m2, were established to evaluate the immediate effect of four silvicultural treatments. These treatments were identified by their levels of management: intensive (clearcut, removal 100%), semi-intensive (removal of 59-61% of basal area), conservative (removal of 29-31% of basal area), and a control group. New forest guidelines, in contrast to conventional approaches, were applied to the semi-intensive and conservative treatments based on health and diversity conditions. Basal area, canopy cover, tree and total volume were measured in each plot. The Importance Value Index, alpha diversity, and evenness were estimated before and after treatments. Eighteen species belonging to five genera and five families were found in the study area. The species with the highest ecological values were Pinus durangensis, P. teocote, Quercus sideroxyla, and Quercus convallata with IVI numbers between 13.6 and 24.5%. Alpha diversity was intermediate (Margalef: 2.9 to 3.8), while dominance and evenness were above average compared to other studies (Simpson: 0.69 to 0.77; Shannon-Wiener: 1.44 to 1.6; Pielou: 0.76 to 0.85). The species evenness index in the conservative treatment was high (Sorensen, Jaccard, quantitative Sorensen and Morisita-Horn; 88 to 99%), although abundance decreased. Overall, there were no significant differences in IVI values and diversity indicators before and after treatments, with the exception of the clearcut treatment. When associating the diversity indices with stand variables, only the Pielou's evenness index showed a significant relationship between them. We concluded that both the conservative and semi-intensive treatments did not generate significant changes in tree diversity, but the former had slightly higher alpha diversity indices. These results can provide a better insight on silvicultural practices and their effects on species composition.

Project description:AimForest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors).LocationTemperate forests in Europe.Time period2017-2018.Major taxa studiedWoody plants.MethodsWe combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures.ResultsThe maximum temperature during the summer was on average cooler by 2.1 °C inside than outside forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 °C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position.Main conclusionsForest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate-species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate deciduous forests, providing ecologically important microclimate data for forest understories.

Project description:Widespread afforestation is a crucial component of climate mitigation strategies worldwide. This presents a significant opportunity for biodiversity conservation if forests are appropriately managed. Within forests, structural and habitat diversity are known to be critical for biodiversity but pragmatic management recommendations are lacking. We make a comprehensive assessment of the effects of habitat variables on bird populations using data from over 4000 ha of forested landscape. We combine high-resolution remote sensing data with comprehensive management databases to classify habitat attributes and measure the response of six taxonomic and functional diversity metrics: species richness, Shannon diversity, functional richness, functional evenness, functional divergence, and functional dispersion. We use a novel approach that combines hierarchical partitioning analysis with linear models to determine the relative importance of different habitat variables for each bird diversity metric. The age class of forest stands was consistently the most important variable across all bird diversity metrics, outperforming other structural measures such as horizontal and vertical heterogeneity and canopy density. Shrub density and gap fraction were each significantly associated with one bird diversity metric. In contrast, variables describing within-stand structural heterogeneity (vertical and horizontal) were generally less important while tree species identity (e.g., conifer or broadleaved) was not significant for any bird diversity metric. Each of the six bird diversity metrics had different patterns of independent variable importance and significance, emphasizing the need to consider multiple diversity metrics in biodiversity assessments. Similarly, the optimal resolution for remote sensing metrics varied between structural variables and bird diversity metrics, suggesting that the use of remote sensing data in biodiversity studies could be greatly improved by first exploring different resolutions and data aggregations. Based on the results from this comprehensive study, we recommend that managers focus on creating habitat diversity at the between-, rather than exclusively within-stand scale, such as by creating a matrix of different age classes, to maximize bird diversity. This recommendation for forest managers is powerful yet pragmatic in its simplicity.

Project description:Bacteria are a crucial component of forest soil biodiversity and play an important role in numerous ecosystem processes. Here, we studied the patterns of soil bacterial community diversity and structure in a climax forest (Larix gmelinii; LG) compared with those in degraded forest ecosystems of four forest vegetation types (BD, Betula dahurica; BP, Betula platyphylla; QM, Quercus mongolica; and LGQM, a mixed coniferous-broadleaved forest composed of Larix gmelinii and Quercus mongolica) in the Heilongjiang Zhongyangzhan Black-billed Capercaillie Nature Reserve in northern China, using Illumina MiSeq sequencing of 16 S rRNA genes. Soil physicochemical properties (pH, soil organic carbon = SOC, total nitrogen = TN, carbon/nitrogen = C/N, total phosphorous = TP, available nitrogen = AN, available phosphorous = AP) differed significantly (p < .05) among the five forests. SOC, C/N, TP, AN, and AP were highest in QM, whereas SOC was lowest in LGQM. Soil pH was lowest in BD and highest in LGQM. α diversity was highest in LG and lowest in QM. The soil bacterial community composition in the climax forest was significantly different from that in the four degraded forests (p < .05). The dominant bacterial phyla were Acidobacteria, Proteobacteria, Verrucomicrobia, Bacteroidetes, Actinobacteria, Gemmatimonadetes, Firmicutes, Chloroflexi, and Rokubacteria. The highest relative abundances of these phyla were: 30.7% for Acidobacteria in LGQM, 42.6% for Proteobacteria in LG, 17.6% for Verrucomicrobia in BD, 5.5% for Firmicutes in BP, and 6.9% for Actinobacteria in QM. The dominant bacterial genera across the five forest vegetation types were Bryobacter and some poorly characterized taxa (e.g., Candidatus_Udaeobacter and Candidatus_Solibacter). Redundancy analysis indicated that SOC, C/N, TP, AN, and AP were the main soil physicochemical properties that shaped the bacterial communities. Our study revealed distinct bacterial diversity and composition in the climax forest compared with values in degraded forests, suggesting that the biotic and abiotic factors associated with climax ecosystems play an important role in shaping soil bacterial community structure and thus biogeochemical functions. The results of this study contribute to a deeper understanding and better predictions of the network among belowground systems and of the functions and services of degraded forests compared with climax ecosystems.

Dataset Information

Using lidar to assess the development of structural diversity in forests undergoing passive rewilding in temperate Northern Europe.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets