Coupling ensemble of small models with UAV-derived structural and textural metrics to predict occurrence of an invasive alien plant in an urban woodland reserve

Accurate forest parameters are crucial for ecological protection, forest resource management and sustainable development. The rapid development of remote sensing can retrieve parameters such as the leaf area index, cluster index, diameter at breast height (DBH) and tree height at different scales (e.g., plots and stands). Although some LiDAR satellites such as GEDI and ICESAT-2 can measure the average tree height in a certain area, there is still a lack of effective means for obtaining individual tree parameters using high-resolution satellite data, especially DBH. The objective of this study is to explore the capability of 2D image-based features (texture and spectrum) in estimating the DBH of individual tree. Firstly, we acquired unmanned aerial vehicle (UAV) LiDAR point cloud data and UAV RGB imagery, from which digital aerial photography (DAP) point cloud data were generated using the structure-from-motion (SfM) method. Next, we performed individual tree segmentation and extracted the individual tree crown boundaries using the DAP and LiDAR point cloud data, respectively. Subsequently, the eight 2D image-based textural and spectral metrics and 3D point-cloud-based metrics (tree height and crown diameters) were extracted from the tree crown boundaries of each tree. Then, the correlation coefficients between each metric and the reference DBH were calculated. Finally, the capabilities of these metrics and different models, including multiple linear regression (MLR), random forest (RF) and support vector machine (SVM), in the DBH estimation were quantitatively evaluated and compared. The results showed that: (1) The 2D image-based textural metrics had the strongest correlation with the DBH. Among them, the highest correlation coefficient of −0.582 was observed between dissimilarity, variance and DBH. When using textural metrics alone, the estimated DBH accuracy was the highest, with a RMSE of only 0.032 and RMSE% of 16.879% using the MLR model; (2) Simply feeding multi-features, such as textural, spectral and structural metrics, into the machine learning models could not have led to optimal results in individual tree DBH estimations; on the contrary, it could even reduce the accuracy. In general, this study indicated that the 2D image-based textural metrics have great potential in individual tree DBH estimations, which could help improve the capability to efficiently and meticulously monitor and manage forests on a large scale.

An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images

Occurrence and damage of invasive alien plants in Dehong Prefecture, western of Yunnan Province

Characterisation of invasive plant proliferation within remnant riparian green corridors in Lusaka District of Zambia using Sentinel-2 imagery

Tree species classification using UAS-based digital aerial photogrammetry point clouds and multispectral imageries in subtropical natural forests

What confers invasive alien plants a competitive advantage over native plants remains open to debate. Many of the world's worst invasive alien plants are clonal and able to share resources within clones (clonal integration), particularly in heterogeneous environments. Here, we tested the hypothesis that clonal integration benefits invasive clonal plants more than natives and thus confers invasives a competitive advantage. We selected five congeneric and naturally co-occurring pairs of invasive alien and native clonal plants in China, and grew pairs of connected and disconnected ramets under heterogeneous light, soil nutrient and water conditions that are commonly encountered by alien plants during their invasion into new areas. Clonal integration increased biomass of all plants in all three heterogeneous resource environments. However, invasive plants benefited more from clonal integration than natives. Consequently, invasive plants produced more biomass than natives. Our results indicate that clonal integration may confer invasive alien clonal plants a competitive advantage over natives. Therefore, differences in the ability of clonal integration could potentially explain, at least partly, the invasion success of alien clonal plants in areas where resources are heterogeneously distributed.

How can spatial structural metrics improve the accuracy of forest disturbance and recovery detection using dense Landsat time series?

Plants have been introduced into the United States intentionally as well as unintentionally as seeds and weeds. Technological advances, a mobile society, and our curiosity and desire to improve our landscapes have led to an ever-increasing invasive movement. These alien plants can jeopardize native populations, alter ecosystems, alter fire and water regimes, change the nutrient status, modify habitats, and cause significant economic harm. Today's public is unaware of the danger some non-native plants species pose to natural areas, thereby contributing to the lack of control for non-native invasive plants. This study looked at the knowledge and attitudes of Texas Master Gardeners as related to invasive species commonly used in landscaping. A web survey was made available to all Texas Master Gardeners that included pictures of plants along with their common and scientific names. Participants were asked to identify which they thought were invasive and contribute information regarding their knowledge of non-native invasive plants. Each of the invasive plants shown is on both the federal and the Texas Invasive Plant lists. Inquires were made concerning the occurrence of these plants in the participants' personal landscape and communities and their perceptions of each plant as an invasive threat. The purpose of the study is to determine if a relationship exists between knowledge, attitudes and perceptions of the participant and the occurrence of non-native invasive plants in the landscape. The results of this study will help determine factors that contribute to the lack of control for non-native invasive plants.

Chapter 25 - Invasive plants and climate change

BackgroundBiological invasions pose an escalating threat to native ecosystems. The accumulation of invasive alien plants worldwide is not saturated yet, underscoring the persistent and growing impact of invasions. Soil microorganisms play a key role in the process of alien plant invasion. However, the temporal dynamics of microbial communities has rarely been determined during the invasion owing to the dearth of long-term, in situ experimental systems.ResultsHere, we examined the temporal succession of soil microbial communities 8 years after experiment setup in a common garden. Bacterial communities displayed divergent temporal succession, with invasive plants exhibiting higher turnover rates. Invasive alien plants reduced stochasticity in bacterial communities, likely acting as an environmental filter on community assembly. Plant growth-promoting microbes underwent higher succession rates in invasive alien plants compared to native plants, suggesting that invasive alien plants may possess a distinct advantage in fostering a favorable microbiota for their own growth and establishment. In sharp contrast, native plants selectively increased succession rates of specific plant pathogens. Furthermore, the microbial co-occurrence network was more complex in invasive plants, suggesting that invasive plants foster intricate relationships among microbial communities.ConclusionsTherefore, the asymmetric succession in soil microbial communities enables invasive plants recruit beneficial microbiota from the surrounding soil. These results deepen our understanding of the mechanism underlying plant invasion and provide novel insights into predicting the ecological consequences resulting from widespread plant invasion. This knowledge can be incorporated into management strategies to address the evolving challenges posed by invasive plants.5vpGYAwD-uHSvdMdk78npkVideo

As globalization progresses, the threat of invasive alien plants to ecosystems is becoming increasingly prominent, and the negative effects of these plants on human health and socioeconomics are gradually increasing with the development of cities; thus, concern about the problem of invasive alien plants in cities is gradually increasing. In this context, we analyzed the differences in the distribution characteristics of invasive alien plants in urban green space, countryside and farmland in Kunshan city, which is located in the Yangtze River Delta region, an area characterized by rapid urbanization. Additionally, the relations between local plant diversity and the intensity of human activities on invasive alien plants were explored. The following results were obtained: (1) There are 38 species of invasive plants in Kunshan, among which 9 species, such as Alternanthera philoxeroides and Erigeron canadensis, are distributed in all kinds of urban areas. There are no endemic invasive plants in the urban green space; however, Amaranthus blitum and eight other species are distributed only in the countryside, and seven species, such as Bidens pilosa, are found only in farmland areas. (2) In different urban areas, native plant species and phylogenetic diversity vary in their resistance to invasive alien plants. Compared with those in other areas, the coverage and importance values of alien invasive plants in the urban countryside significantly decreased with increasing quantity of native plant species and phylogenetic diversity. (3) GDP per capita, the proportion of built-up land and road density were the main factors affecting the distribution of invasive alien plants, but there were differences in the influence of human activities in different urban areas. The importance values of invasive alien plants increased significantly with increasing population density and GDP per capita in the countryside, but there was no such trend in urban green space or farmland areas. Overall, these findings suggest that urban planning and landscape management strategies should target the management of invasive alien plants based on the characteristics in different urban areas to maintain the stability and sustainability of urban ecosystems.

ABSTRACTThe spatial distribution of invasive alien plants has been poorly documented in California. However, with the increased availability of GIS software and spatially explicit data, the distribution of invasive alien plants can be explored. Using bioregions as defined in Hickman (1993), I compared the distribution of invasive alien plants (n = 78) and noninvasive alien plants (n = 1097). The distribution of both categories of alien plants was similar with the exception of a higher concentration of invasive alien plants in the North Coast bioregion. Spatial autocorrelation analysis using Moran's I indicated significant spatial dependence for both invasive and noninvasive alien plant species. I used both ordinary least squares (OLS) and spatial autoregressive (SAR) models to assess the relationship between alien plant species distribution and native plant species richness, road density, population density, elevation, area of sample unit, and precipitation. The OLS model for invasive alien plants included two significant effects; native plant species richness and elevation. The SAR model for invasive alien plants included three significant effects; elevation, road density, and native plant species richness. The SAR model for noninvasive alien plants resulted in the same significant effects as invasive alien plants. Both invasive and noninvasive alien plants are found in regions with low elevation, high road density, and high native‐plant species richness. This is in congruity with previous spatial pattern studies of alien plant species. However, the similarity in effects for both categories of alien plants alludes to the importance of autecological attributes, such as pollination system, dispersal system and differing responses to disturbance in the distribution of invasive plant species. In addition, this study emphasizes the critical importance of testing for spatial autocorrelation in spatial pattern studies and using SAR models when appropriate.

In support of the prediction of the enemy release hypothesis regarding a growth-defense trade-off, invasive alien plants often exhibit greater growth and lower anti-herbivory defenses than native plants. However, it remains unclear how nutrient enrichment of invaded habitats may influence competitive interactions between invasive alien and co-occurring native plants, as well as production of anti-herbivore defense compounds, growth-promoting hormones, and defense-regulating hormones by the two groups of plants. Here, we tested whether: (i) nutrient enrichment causes invasive alien plants to produce greater biomass and lower concentrations of the defense compounds flavonoids and tannins than native plants; and (ii) invasive alien plants produce lower concentrations of a defense-regulating hormone jasmonic acid (JA) and higher concentrations of a growth-promoting hormone gibberellic acid (GA3). In a greenhouse experiment, we grew five congeneric pairs of invasive alien and native plant species under two levels each of nutrient enrichment (low vs. high), simulated herbivory (leaf clipping vs. no-clipping), and competition (alone vs. competition) in 2.5-L pots. In the absence of competition, high-nutrient treatment induced a greater increase in total biomass of invasive alien species than that of native species, whereas the reverse was true under competition as native species benefitted more from nutrient enrichment than invasive alien species. Moreover, high-nutrient treatment caused a greater increase in total biomass of invasive alien species than that of native species in the presence of simulated herbivory. Competition induced higher production of flavonoids and tannins. Simulated herbivory induced higher flavonoid expression in invasive alien plants under low-nutrient than high-nutrient treatments. However, flavonoid concentrations of native plants did not change under nutrient enrichment and simulated herbivory treatments. Invasive alien plants produced higher concentrations of GA3 than native plants. Taken together, these results suggest that impact of nutrient enrichment on growth of invasive alien and co-occurring native plants may depend on the level of competition that they experience. Moreover, invasive alien plants might adjust their flavonoid-based defense more efficiently than native plants in response to variation in soil nutrient availability and herbivory pressure. Our findings suggest that large-scale efforts to reduce nutrient enrichment of invaded habitats may help to control future invasiveness of target alien plant species.

Impacts of invasive alien plants on ecosystem services of Ramsar lake cluster in middle mountain Nepal

Individual tree parameters are essential for forestry decision-making, supporting economic valuation, harvesting, and silvicultural operations. While extensive research exists on uniform and simply structured forests, studies addressing complex, dense, and mixed forests with highly overlapping, clustered, and multiple tree crowns remain limited. This study bridges this gap by combining structural, textural, and spectral metrics derived from unmanned aerial vehicle (UAV) Red–Green–Blue (RGB) and multispectral (MS) imagery to estimate individual tree parameters using a random forest regression model in a complex mixed conifer–broadleaf forest. Data from 255 individual trees (115 conifers, 67 Japanese oak, and 73 other broadleaf species (OBL)) were analyzed. High-resolution UAV orthomosaic enabled effective tree crown delineation and canopy height models. Combining structural, textural, and spectral metrics improved the accuracy of tree height, diameter at breast height, stem volume, basal area, and carbon stock estimates. Conifers showed high accuracy (R2 = 0.70–0.89) for all individual parameters, with a high estimate of tree height (R2 = 0.89, RMSE = 0.85 m). The accuracy of oak (R2 = 0.11–0.49) and OBL (R2 = 0.38–0.57) was improved, with OBL species achieving relatively high accuracy for basal area (R2 = 0.57, RMSE = 0.08 m2 tree−1) and volume (R2 = 0.51, RMSE = 0.27 m3 tree−1). These findings highlight the potential of UAV metrics in accurately estimating individual tree parameters in a complex mixed conifer–broadleaf forest.