Monitoring Of Invasive Plants Research Articles

Monitoring the Invasion of S. alterniflora on the Yangtze River Delta, China, Using Time Series Landsat Images during 1990–2022

Spartina alterniflora (S. alterniflora) has grown rapidly in China since its introduction in 1979, showing the trend of alien species invasion, which has seriously affected the ecosystem balance of coastal wetlands. The temporal and spatial expansion law of S. alterniflora can be obtained through remote sensing monitoring, which can provide a reference and basis for S. alterniflora management. This paper presents a method for extracting and mapping S. alterniflora based on phenological characteristics. The coastal areas of the Yangtze River Delta Urban Agglomeration are selected as the research area, and the Landsat time series data from 1990 to 2022 on the Google Earth Engine (GEE) platform are used to support the experiment in this paper. Firstly, the possible growing area of S. alterniflora was extracted using the normalized differential moisture index (NDMI), normalized differential vegetation index (NDVI), and normalized differential water index (NDWI); Then, the time series curve characterizing the phenological characteristics of vegetation was constructed using the vegetation index to determine the difference phase of phenological characteristics between S. alterniflora and other vegetation. Finally, a decision tree was constructed based on the phenological feature difference phase data to extract S. alterniflora, and it is applied to the analysis of temporal and spatial changes of S. alterniflora in the study area from 1990 to 2022. The results show that the area of S. alterniflora increased from ~1426 ha in 1990 to ~44,508 ha in 2022. However, the area of S. alterniflora began to show negative growth in 2015 due to the construction of nature reserves and ecological management. The results of correlation analysis showed that the growth of C. japonicum was significantly affected by temperature stress and weakly affected by precipitation. This study verified that Landsat time series images can effectively extract vegetation phenological information, which has strong feasibility for extraction and dynamic monitoring of S. alterniflora and provides technical support for the management and monitoring of invasive plants in coastal wetlands.

Distribution, drivers and restoration priorities of plant invasions in India

Abstract Biological invasions threaten biodiversity and human wellbeing, with developing tropical countries being more vulnerable. Despite the urgency to reduce impacts of invasions, management interventions are constrained by unavailability of timely information on invasive species occurrence, potential drivers and restoration priorities. Generating this information at biogeographic scales can be costly, unless integrated with multi‐objective biodiversity monitoring. Invasive plant monitoring is integrated with India's national‐scale tiger population assessment, wherein natural areas are sampled at 25 km2 scale to inventory plants. In 2018, a total of 158,979 plots were sampled covering ~358,550 km2. We used 206,393 locations of high concern invasive plants to model their distribution using socio‐ecological covariates and identify potential drivers of invasions. Considering the invasion magnitude and financial constraints in management, we further identified priority restorations sites at national‐scale to maximise biodiversity outcomes. High‐concern invasive plants were recorded from ~254,880 km2 (72% sampled area) and modelled to invade in total ~750,905 km2 (66%) Indian natural systems. While open and deciduous ecosystems were the highest invaded by woody plants, areas with extreme climate and less anthropic pressure were least invaded. Since managing invasions across their range seemed futile due to costly (~13.5 billion USD for one‐time management) and ineffective strategies, restoration priority was assigned to least invaded areas (11% protected areas, 23% multi‐use) to maximise biodiversity returns. Synthesis and applications: India implemented national‐scale invasive plant monitoring by integrating it with the umbrella project on tiger assessment. Embarking on this big data, we show that two‐thirds of India's natural areas are under multiple plant invasions, owing to the legacy of anthropogenic modifications. Our study offers a restoration priority model, empowering policymakers to devise adaptive strategies for restoring invaded biomes and maximizing biodiversity returns.

Spatiotemporal Pattern of Invasive Pedicularis in the Bayinbuluke Land, China, during 2019–2021: An Analysis Based on PlanetScope and Sentinel-2 Data

The accurate identification and monitoring of invasive plants are of great significance to sustainable ecological development. The invasive Pedicularis poses a severe threat to native biodiversity, ecological security, socioeconomic development, and human health in the Bayinbuluke Grassland, China. It is imperative and useful to obtain a precise distribution map of Pedicularis for controlling its spread. This study used the positive and unlabeled learning (PUL) method to extract Pedicularis from the Bayinbuluke Grassland based on multi-period Sentinel-2 and PlanetScope remote sensing images. A change rate model for a single land cover type and a dynamic transfer matrix were constructed under GIS to reflect the spatiotemporal distribution of Pedicularis. The results reveal that (1) the PUL method accurately identifies Pedicularis in satellite images, achieving F1-scores above 0.70 and up to 0.94 across all three datasets: PlanetScope data (seven features), Sentinel-2 data (seven features), and Sentinel-2 data (thirteen features). (2) When comparing the three datasets, the number of features is more important than the spatial resolution in terms of use in the PUL method of Pedicularis extraction. Nevertheless, when compared with PlanetScope data, Sentinel-2 data demonstrated a higher level of accuracy in predicting the distribution of Pedicularis. (3) During the 2019–2021 growing season, the distribution area of Pedicularis decreased, and the distribution was mainly concentrated in the northeast and southeast of Bayinbuluke Swan Lake. The acquired spatiotemporal pattern of invasive Pedicularis could potentially be used to aid in controlling Pedicularis spread or elimination, and the methods proposed in this study could be adopted by the government as a low-cost strategy to identify priority areas in which to concentrate efforts to control and continue monitoring Pedicularis invasion.

VEGETATION INDEX BASED IN UNMANNED AERIAL VEHICLE (UAV) TO IMPROVE THE MANAGEMENT OF INVASIVE PLANTS IN PROTECTED AREAS, SOUTHERN BRAZIL

Abstract. The biological invasion is considered the second largest global threat to the maintenance and conservation of natural ecosystems biodiversity. Strategies and actions that guide the control and monitoring of invasive species in protected areas are still a challenge on the management of these areas. Remote sensing is potential tool to detect and monitoring these species, gaining a timeline scale and allowing the adoption of more effective control methods. In this study, search to evaluate the vegetation index potential by using multispectral images acquired by UAV as a support on detection and monitoring of invasive plants in Quarta Colônia State Park located on the Brazil’s southern region. A sampling area with a density of invasive plants above 80% was evaluated, with predominance of Psidium guajava and Ligustrum lucidum, generating a large data set from the extracted indexes. Among the evaluated index, the ones that showed the most potential in this study were Green Normalized Difference Vegetation Index (GNDVI), Plant Senescence Reflectance Index (PSRI) and Red Green Ratio Index (RGRI). Believe us that the use of UAVs platforms will be an important tool for the management of invasive species in protected areas.

Trained Dogs Outperform Human Surveyors in the Detection of Rare Spotted Knapweed (Centaurea stoebe)

AbstractInvasive plants have devastating effects on ecosystems and biodiversity that early intervention can prevent. Eradication or containment of new invasions is difficult to achieve because of constraints posed by the low density and detectability of individuals. Domestic dogs trained to cue on distinctive scents might provide an effective method to detect spotted knapweed. The objective of this study was to compare the accuracy and detection distances of dogs to humans in locating new spotted knapweed (Centaurea stoebe) invasions. Three dogs, trained to detect knapweed using scent discrimination and tracking techniques, were compared with human surveyors. Seven sampling units (0.5 ha [1.2 ac]) were delineated in a grazed dryland pasture. Dogs, with their handlers, and human surveyors performed line-transect surveys in fall 2005 and spring, summer, and fall 2006. Dog accuracy for large-size knapweed targets (infestations 0.52 m3[18.4 ft3]) was similar to human accuracy and better than humans (94 vs. 78%) for medium-size targets (infestations 0.13m3). Dog accuracy (67%) was greater (> 81% probability) than humans (34%) for small targets (plants; 0.02 m3). Overall dog accuracy (81%) andF-measure scores (86%) were better than human scores, 59% and 74%, respectively. Human precision was greater (100%) than dogs at 94%. Dogs detected a larger percentage of small targets (80%) at distances greater than 7.9 m (26 ft) compared with humans at only 20%. Our results indicate dogs are more accurate than humans are, especially at critical detection of small spotted knapweed plants, and from greater distances. Invasive plant monitoring using detection dogs can provide greater overall accuracy of plant detection.

Military Training and Road Effects onImperata cylindrica(L.) Beauv. (Cogongrass)

Type, level, and intensity of human activities may facilitate establishment and spread of invasive plant species. A better understanding of how human activities infl uence invasion can assist land managers in developing strategies for control and monitoring of invasive plants. Spread of the invasive species Imperata cylindrica (Cogongrass) has been attributed to human activities. During 2002I 2004, on Camp Shelby Training Site, MS, we investigated relationships between military activity and establishment and growth of Cogongrass. In areas of soil disturbance from mili- tary equipment, vegetative linear growth rates of 7I 10 m yr -1 were recorded on fi ring points. There was a positive relationship between military troop use and Cogongrass establishment on fi ring points for one of the 2 years of the study (P = 0.023). Thus, steps to minimize soil disturbance in and near Cogongrass may reduce spread. We examined frequency of Cogongrass infestation and vegetative growth rates for road- side areas along gravel roads subject to at least annual mowing and grading, and dirt tracks receiving infrequent maintenance. Cogongrass spread and establishment on roadsides did not differ for the two road types (Pi 0.116). These results may refl ect activities already in place to reduce disturbance of Cogongrass patches.