Species-diverse Forests Research Articles

Tree growth strategies mediate drought resistance in species-diverse forests.

Tree growth strategies mediate drought resistance in species-diverse forests.

How deforestation and forest use affect tree diversity in a conifer forest from central Mexico

Aim of study: To assess the association of deforestation and forest use with tree diversity and dominance of pine species. Area of study: La Malinche National Park, central Mexico. Material and methods: Three forest stands were selected on each of four slopes in La Malinche National Park, in which the percent forest cover was determined using a concave spherical densitometer. Additionally, we estimated logging, firewood, and ocoteo as indirect measures of forest use. In each forest stand, we set five 0.1-ha circular plots and we recorded tree species, diameter at breast height, and height of all individuals ≥1.5 m. We estimated diversity using Hill numbers (qD). We identified dominant species from rank-abundance curves, and explored the dissimilarity between forest stands for the three q orders. Using generalized linear mixed-effects models, we evaluated the relationships of deforestation and forest use with species diversity and pine dominance, and studied the effect of pine dominance on the abundance of other tree species through generalized linear models. Main results: We recorded a total of 16 tree species; a pine (Pinus montezumae) was the dominant species. The diversity of tree species was not associated with forest use or deforestation, but deforestation increased Pinus dominance, with a strong slope effect. Research highlights: Regulation and control of forest use should be prioritized to avoid further deforestation and the transformation of species-diverse forests into monospecific forests, further increasing the dominance of P. montezumae. We also suggest reforesting with native species and those scarcely represented to increase forest cover and maintain tree diversity.

Contrasting vulnerability of monospecific and species-diverse forests to wind and bark beetle disturbance: The role of management.

Wind and bark beetle disturbances have increased in recent decades, affecting Europe's coniferous forests with particular severity. Management fostering forest diversity and resilience is deemed to effectively mitigate disturbance impacts, yet its efficiency and interaction with other disturbance management measures remain unclear.We focused on Central Europe, which has become one of the hotspots of recent disturbance changes. We used the iLand ecosystem model to understand the interplay between species composition of the forest, forest disturbance dynamics affected by climate change, and disturbance management. The tested measures included (a) active transformation of tree species composition toward site‐matching species; (b) intensive removal of windfelled trees, which can support the buildup of bark beetle populations; and (c) reduction of mature and vulnerable trees on the landscape via modified harvesting regimes.We found that management systems aiming to sustain the dominance of Norway spruce in the forest are failing under climate change, and none of the measures applied could mitigate the disturbance impacts. Conversely, management systems fostering forest diversity substantially reduced the level of disturbance. Significant disturbance reduction has been achieved even without salvaging and rotation length reduction, which is beneficial for ecosystem recovery, carbon, and biodiversity. Synthesis and applications: We conclude that climate change amplifies the contrast in vulnerability of monospecific and species‐diverse forests to wind and bark beetle disturbance. Whereas forests dominated by Norway spruce are not likely to be sustained in Central Europe under climate change, different management strategies can be applied in species‐diverse forests to reach the desired control over the disturbance dynamic. Our findings justify some unrealistic expectations about the options to control disturbance dynamics under climate change and highlight the importance of management that fosters forest diversity.

Insights from a large-scale inventory in the southern Brazilian Atlantic Forest

A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ~5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.

Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery

The mangrove forests of northeast Hainan Island are the most species diverse forests in China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date the aboveground ground biomass (AGB) of this mangrove region has not been quantified due to the high species diversity and the difficulty of extensive field sampling in mangrove habitat. Although three-dimensional point clouds can capture the forest vertical structure, their application to large areas is hindered by the logistics, costs and data volumes involved. To fill the gap and address this issue, this study proposed a novel upscaling method for mangrove AGB estimation using field plots, UAV-LiDAR strip data and Sentinel-2 imagery (named G∼LiDAR∼S2 model) based on a point-line-polygon framework. In this model, the partial-coverage UAV-LiDAR data were used as a linear bridge to link ground measurements to the wall-to-wall coverage Sentinel-2 data. The results showed that northeast Hainan Island has a total mangrove AGB of 312,806.29 Mg with a mean AGB of 119.26 Mg ha−1. The results also indicated that at the regional scale, the proposed UAV-LiDAR linear bridge method (i.e., G∼LiDAR∼S2 model) performed better than the traditional approach, which directly relates field plots to Sentinel-2 data (named the G∼S2 model) (R2 = 0.62 > 0.52, RMSE = 50.36 Mg ha−1<56.63 Mg ha−1). Through a trend extrapolation method, this study inferred that the G∼LiDAR∼S2 model could decrease the number of field samples required by approximately 37% in comparison with those required by the G∼S2 model in the study area. Regarding the UAV-LiDAR sampling intensity, compared with the original number of LiDAR plots, 20% of original linear bridges could produce an acceptable accuracy (R2 = 0.62, RMSE = 51.03 Mg ha−1). Consequently, this study presents the first investigation of AGB for the mangrove forests on northeast Hainan Island in China and verifies the feasibility of using this mangrove AGB upscaling method for diverse mangrove forests.

INDIVIDUAL TREE DETECTION FROM UAV LIDAR DATA IN A MIXED SPECIES WOODLAND

Abstract. The study evaluates five existing segmentation algorithms to determine the method most suitable for individual tree detection across a species-diverse forest: raster-based region growing, local maxima centroidal Voronoi tessellation, point-cloud level region growing, marker controlled watershed and continuously adaptive mean shift. Each of the methods has been tested twice over one mixed and five single species plots: with their parameters set as constant and with the parameters calibrated for every plot. Overall, continuous adaptive mean shift performs best across all the plots with average F-score of 0.9 with fine-tuned parameters and 0.802 with parameters held at constant. Raster-based algorithms tend to achieve higher scores in coniferous plots, due to the clearly discernible tops, which significantly aid the detection of local maxima. Their performance is also highly dependent on the moving size window used to detect the local maxima, which ideally should be readjusted for every plot. Crown overlap, suppressed and leaning trees are the most likely sources of error for all the algorithms tested.

Aboveground overyielding in a mixed temperate forest is not explained by belowground processes.

The relationship between forest productivity and tree species diversity has been described in detail, but the underlying processes have yet to be identified. One important issue is to understand which processes are at the origin of observed aboveground overyielding in some mixed forests. We used a beech-maple plantation exhibiting aboveground overyielding to test whether belowground processes could explain this pattern. Soil cores were collected to determine fine root (FR) biomass and vertical distribution. Correlograms were used to detect spatial arrangement. Near-infrared reflectance spectroscopy was used to identify the tree species proportion in the FR samples and spatial root segregation. An isotopic approach was used to identify water acquisition patterns. The structure and the composition of the ectomycorrhizal fungal community were determined by high-throughput sequencing of DNA in the soil samples. We found no spatial pattern for FR biomass or for its vertical distribution along the gradients. No vertical root segregation was found, as FR density for both species decreased with depth in a similar way. The two species displayed similar vertical water acquisition profiles as well, mainly absorbing water from shallow soil layers; hence, niche differentiation for water acquisition was not highlighted here. Significant alterations in the fungal community compositions were detected in function of the percentage of maple in the vicinity of beech. Our findings do not support the commonly suggested drivers of aboveground overyielding in species-diverse forests and suggest that competition reduction or between-species facilitation of belowground resource acquisition may not explain the observed aboveground overyielding.

Light Measurement Methods Related to Forage Yield in a Grazed Northern Conifer Silvopasture in the Appalachian Region of Eastern USA

The Appalachian region is characterized by hilly topography and a humid temperate climate. In most areas agriculture is limited to pasture although the native climax vegetation is a species-diverse forest. Silvopasture systems can help diversify and increase farm income. Information is needed on the yield response of forage grown as an understory crop among trees. The light environment of a conifer silvopasture was characterized by three methods, a hand-held photosynthetically active radiation (PAR) meter for quick measurements over a large area, fixed PAR meters recorded using data loggers for a large number of measurements over time, and hemispherical photography with software to calculate seasonal direct beam radiation. Light data were considered in terms of forage yield. Plots were harvested when forage reached 20–25 cm in height after which the entire area was grazed by sheep. There were limitations to all methods of quantifying radiation environment for predicting yield. Yield decreased linearly with decreased PAR; however, data variability was high and correlations, while statistically significant, were weak. Grazed silvopastures are dynamic with shifting yield patterns in response to the interactions between the spatially variable soil, changing seasonal environment, and spatially variable animal impacts for each grazing event.

Plantas útiles en la selva de Los Tuxtlas (Veracruz, México): Consideraciones acerca de su potencial en el mercado

The 640 hectare large Los Tuxtlas rain forest reserve was analyzed for the commercial potential of its 860 native flowering plant species. Excluding plants with medicinal or chemical use, 91 species (10.6%) are found in the market, and we consider an additional 72 species (8.4%) to have market potential. For each of the 163 species, the following information is given: scientific and common name, geographic distribution, growth form, use, and market status. Of the 163 species, 2.4% are endemic to the Los Tuxtlas region, 10.4% are restricted to Mexico, 42.3% extend further into Central America, and 39.3% occur also in South America, while 20.2% are found in the West Indies. The majority of species (68.7%) are trees. In terms of use categories, 35.0% are employed for their timber, 32.5% for their fuelwood, 24.5% for ornamental purposes, 22.7% for their edible fruits, leaves or flowers, 11.0% for plywood or paper, 6.1% for artwork and weaving, and 1.2% as fodder plants. The more than 160 marketable species would make it possible to develop species-diverse forests of high commercial value, as an alternative to current land use, which consists in converting forest into cattle pastures.