Distribution Of Invasive Alien Species Research Articles

Erratum to: Effects of anthropogenic activities and climate factors on the distribution of invasive alien species in China

Erratum to: Effects of anthropogenic activities and climate factors on the distribution of invasive alien species in China

Assessing the Current and Future Potential Distribution of Solanum rostratum Dunal in China Using Multisource Remote Sensing Data and Principal Component Analysis

Accurate information concerning the spatial distribution of invasive alien species’ habitats is essential for invasive species prevention and management, and ecological sustainability. Currently, nationwide identification of suitable habitats for the highly destructive and potentially invasive weed, Solanum rostratum Dunal (S. rostratum), poses a series of challenges. Simultaneously, research on potential future invasion areas and likely directions of spread has not received adequate attention. This study, based on species occurrence data and multi-dimensional environmental variables constructed from multi-source remote sensing data, utilized Principal Component Analysis (PCA) in combination with the Maxent model to effectively model the current and future potential habitat distribution of S. rostratum in China, while quantitatively assessing the various factors influencing its distribution. Research findings indicate that the current suitable habitat area of S. rostratum covers 1.3952 million km2, all of which is located in northern China. As the trend of climate warming persists, the potential habitat suitability range of S. rostratum is projected to shift southward and expand in the future; while still predominantly located in northern China, it will have varying degrees of expansion at different time frames. Notably, during the period from 2040 to 2061, under the SSP1-2.6 scenario, the habitat area exhibits the most significant increase, surpassing the current scenario by 19.23%. Furthermore, attribution analysis based on PCA inverse transformation reveals that a combination of soil, climate, spatial, humanistic, and topographic variables collectively influence the suitability of S. rostratum habitats, with soil factors, in particular, playing a dominant role and contributing up to 75.85%. This study identifies target areas for the management and control of S. rostratum, providing valuable insights into factor selection and variable screening methods in species distribution modeling (SDM).

Effects of anthropogenic activities and climate factors on the distribution of invasive alien species in China

全球变化引起的生物入侵已经严重地威胁了生物多样性分布和生态系统功能与服务. 生物入侵分布格局及其影响因素的深入研究有助于更好地预测和管理外来入侵物种, 从而有效地保护生物多样性和生态系统功能与服务. 然而, 目前尚未有研究系统地讨论不同时期人类活动与自然因子对中国外来入侵植物、外来入侵昆虫和外来入侵微生物分布格局的影响. 本研究基于最近出版的外来入侵生物相关资料, 首先描述了3个外来入侵类群在我国的省级分布格局. 然后利用单因素普通最小二乘法模型和空间自回归模型探讨了不同时期人类活动和自然因素对这些分布格局的影响. 结果表明3个外来入侵类群丰富度在我国各省份的分布呈现相似的格局, 即东南偏多, 西北偏少; 相较于入侵植物和入侵昆虫, 入侵微生物在东北和华北的丰富度也较高. 2000年的国内生产总值是影响3个分类群丰富度最大的人类活动指标, 且均呈显著正相关关系. 在自然因子中, 年均温和年降水对入侵植物丰富度和入侵昆虫丰富度解释率也较高, 且呈显著正相关关系, 但对入侵微生物丰富度影响不显著. 值得一提的是, 即使在控制自然因子的影响后, 2000年的国内生产总值依然是对3个分类群丰富度影响最大的因子. 研究结果表明尽管我国东南地区温湿的气候有利于外来入侵生物的生存和扩散, 该区域大量的社会经济活动也是促进外来生物入侵的重要因素. 因此, 未来我国在开展对外贸易与发展经济的同时, 应该更加重视对外来入侵生物的管控.

On the importance of invasive species niche dynamics in plant conservation management at large and local scale

Predicting the distribution of Invasive alien species (IAS) using species distribution models is promising for conservation planning. To achieve accurate predictions, it is essential to explore species niche dynamics. New approaches are necessary for bringing this analysis to real conservation management needs. Using multi-site comparisons can provide great useful insights to better understand invasion processes. Exploring the fine-scale niche overlap between IAS and native species sharing a location can be a key tool for achieving the implementation of local species conservation actions, which can play a fundamental role in the global management of IAS. This can also increase society’s awareness of the threat of IAS. In this context, here, we explored two key research demands. First, we studied the large-scale niche dynamics of the invasive species Paraserianthes lophantha (Willd.) I.C. Nielsen’s considering different invaded areas. The analysis compared niches of the native range (South Western Australia) with the Australian invaded range (eastern Australia); the native range with the European invaded range, and its full Australian range (native plus invaded range) with the European invaded range. Second, we perform a fine-scale niche overlap analysis at landscape scale in Spain. We studied the niche overlap between P. lophantha and a species with remarkable conservation interest (Quercus lusitanica Lam). All the niche analyses were realized following a well-established ordination (principal component analysis) approach where important methodological aspects were compared and analyzed. Our multi-site study of P. lophantha large-scale niche dynamics detected niche shifts between the Australian ranges demonstrating that the species is labile and may potentially adapt to further European climate conditions and spread its invasive range. Comparative analysis between the European and the full Australian ranges supports that calibrate models including the Australian invasive information is promising to accurate predict P. lophantha European potential distribution. The fine-scale study of niche overlap further explained the potential of this IAS and can be used as a model example of how these local studies can be used to promote the implementation of conservation actions in situ as a complement to large-scale management strategies.

Passive Acoustic Monitoring as a Tool to Investigate the Spatial Distribution of Invasive Alien Species

Invasive alien species (IAS) are a threat to biodiversity and ecosystem function worldwide. Unfortunately, researchers, agencies, and other management groups face the unresolved challenge of effectively detecting and monitoring IAS at large spatial and temporal scales. To improve the detection of soniferous IAS, we introduced a pipeline for large-scale passive acoustic monitoring (PAM). Our main goal was to illustrate how PAM can be used to rapidly provide baseline information on soniferous IAS. To that aim, we collected acoustic data across Puerto Rico from March to June 2021 and used single-species occupancy models to investigate species distribution of species in the archipelago and to assess the peak of vocal activity. Overall, we detected 16 IAS (10 birds, 3 mammals, and 3 frogs) and 79 native species in an extensive data set with 1,773,287 1-min recordings. Avian activity peaked early in the morning (between 5 a.m. and 7 a.m.), while amphibians peaked between 1 a.m. and 5 a.m. Occupancy probability for IAS in Puerto Rico ranged from 0.002 to 0.67. In general, elevation and forest cover older than 54 years were negatively associated with IAS occupancy, corroborating our expectation that IAS occurrence is related to high levels of human disturbance and present higher occupancy probabilities in places characterized by more intense human activities. The work presented here demonstrates that PAM is a workable solution for monitoring vocally active IAS over a large area and provides a reproducible workflow that can be extended to allow for continued monitoring over longer timeframes.

Predicting the potential sites of Chromolaena odorata and Lantana camara in forest landscape of Eastern Ghats using habitat suitability models

Conservation strategies need reliable information on species distribution and habitat suitability. Modelling the invasion probability of species is required for invasive alien species management. The present study aims in predicting the suitable habitat and potential distribution of invasive plant species - Chromolaena odorata and Lantana camara. We used the Maximum entropy (MaxEnt), Random forest, Surface range envelope, Boosted regression tree analysis, Classification tree analysis, and Generalised boosted model to identify the suitable habitats for potential environmental distribution of invasive alien species in the Eastern Ghats of Visakhapatnam district, Andhra Pradesh, India. The Area under Curve (AUC) for each model has been estimated for predicting the potentially suitable habitats of invasion. The results suggested that the MaxEnt model, Random forest, boosted regression tree, and Surface range envelope were suitable approaches in identifying areas of potential habitats of selected invasive alien species. This study aids in developing long-term conservation practices for the management of invasive alien species.

Mapping spatial distribution of invasive alien species through satellite remote sensing in Karachi, Pakistan: an urban ecological perspective

The exponential population growth of Karachi city has taken a very heavy toll on the indigenous environment of this South Asian megacity. In this context, the unlikely roadsides plantation of nonnative species by the city decision-makers was a short-term solution to cultivate green belts, ultimately, to improve city environment. However, this has backfired and become a very serious ecological crisis as the species become invasive alien species and destroyed the native ecological environment of the city significantly. This study provided an accurate spatial extent of invasive alien species and evaluated the intensity of the problem using remote sensing technology. Firstly, the importance value index was developed to highlight the intensity of invasive alien species in native plant communities. Afterwards, the hot spots were sampled to develop training areas for Object Based Image Analysis to map the extent of invasive alien species in the city using high-resolution GeoEye satellite imagery. The overall accuracy of mapping was 93.17% with Kappa coefficient value of 0.904. In addition, to explore hyperspectral remote sensing analysis, two techniques—Derivative Vegetation Index and Spectral Angle Mapper—were employed on EO-I hyperspectral imagery to map invasive alien species using spectral signatures. The analysis revealed 99.94% correlation between the two mapping techniques. Finally, to identify the impact of invasive alien species on the microclimate of the city, a spatiotemporal analysis (1992–2016) at selected sites was performed on Landsat thermal images. The study ruled out the concept of invasive alien species influence on the microclimate of the city as both vegetation growth and ambient air temperature change were not interdependent.

Spatial distribution patterns of invasive alien species in China

The spatial distribution of invasive alien species is driven by various factors, and should be comprehensively evaluated based on multiple invasion indices and different taxonomic groups. In our study, we constructed three sets of invasion indices: (1) absolute invasive alien species (AIAS) richness; (2) weighted invasive alien species (WIAS) richness; (3) relative invasive alien species (RIAS) richness. First, we used principal component analysis (PCA) and k-means clustering to distinguish the invasion risk levels of 28 provinces in China. Then, the ordinary least squares (OLS) and partial least squares (PLS) regression methods were used to explore the factors predicting the distribution patterns of three sets of invasion indices for total species, plants and animals. Finally, the residuals’ regressions of alien plant species richness on alien animal species richness were used to evaluate the effect of environmental and anthropogenic factors on spatial congruence. Results showed that 17 provinces were identified as high invasion risk regions (Liaoning, Hebei, Shandong, Anhui, Jiangsu, Zhejiang, Hunan, Hubei, Jiangxi, Guangdong, Guangxi, Fujian, Taiwan, Hainan, Guizhou, Yunnan and Sichuan). For environmental factors, the potential evapotranspiration (PET) or actual evapotranspiration (AET) could better predict AIAS and WIAS richness, and area better predicted RIAS richness. For anthropogenic factors, the gross domestic product (GDP) or human population explained more variation in AIAS or WIAS richness, and transport volume or GDP could better explain the variation in RIAS richness. Generally, the environmental and anthropogenic factors showed identical prediction ability. The results of PLS regressions indicated that one set of predictors showed similar effects to the alien plants and animals within a model, and indicated the spatial distribution congruence of them. Removing the environmental and anthropogenic factors, to some extent, will weaken the congruence, but the congruence of plants and animals still exists for AIAS and RIAS richness. Our study provides meaningful information for the prediction and management of the biological invasions.

Sentinel-2 time series based optimal features and time window for mapping invasive Australian native Acacia species in KwaZulu Natal, South Africa

The spread of invasive Australia native Acacia tree species threatens biodiversity and adversely affecting on vegetative structure and function, including plant community composition, quantity and quality worldwide. It is essential to provide researchers and land managers for biological invasion science and management with accurate information of the distribution of invasive alien species and their dynamics. Remotely sensed data that reveal spatial distribution of the earth’s surface features/objects provide great potential for this purpose. Consistent satellite monitoring of alien invasive plants is often difficult because of lack of sufficient spectral contrast between them and co-occurring plants species. Time series analysis of spectral properties of the species can reveal timing of their variations among adjacent species. This information can improve accuracy of invasive species discrimination and mapping using remote sensing data at large scale. We sought to identify and better understand the optimal time window and key spectral features sufficient to detect invasive Acacia trees in heterogeneous forested landscape in South Africa. We explored one-year (January to December 2018) time series spectral bands and vegetation indices derived from optical Copernicus Sentinel-2 data. The attributes correspond to geographical information of invasive Acacia and native species recorded during a field survey undertaken from 21 February to 25 February 2018 over Kwa-Zulu Natal grasslands landscape, in South Africa. The results showed comparable separability prospects between times series of spectral bands and that of vegetation indices.Substantial differences between Acacia species and native species were observed from spectral indices and spectral bands which are sensitive to Leaf Area Index, canopy chlorophyll and nitrogen concentrations. The results further revealed spectral differences between Acacia species and co-occurring native vegetation in April (senescence for deciduous plants), June-July (dry season), September (peak flowering period of Acacia spp) and December (leaf green-up) with vegetation indices (overall accuracy > 80 %). While spectral bands showed the beginning of the growing season (November–January) and peak vegetation productivity (February-March) as the optimal seasons or dates for image acquisition for discriminating Acacias from its co-occurring native species (overall accuracy > 80 %). In general, the use of Sentinel-2 time series spectral bands and vegetation indices has increased our understanding of Australian Acacias spectral dynamics, and proved that the sentinel-2 data is useful for characterization and monitoring Acacias over a large scale. Our results and approach could assist in deriving detailed geographic information of the species and assessment of a spread invasive plant species and severity of invasion.

Utilization of Invasive Alien Species (IAS) by communities around Cibodas Biosphere Reserve (CBR): a recommendation for invasive alien species management and policy

The distribution of Invasive Alien Species (IAS) in the Cibodas Biosphere Reserve (CBR) area is enormous. Controlling IAS distribution is essential to be carried out, for the high potential threat to the native plant species. Generally, IAS species invade an open area of the forest. A review has been conducted with a literature study regarding recorded data about invasive alien species and studies about the utilization of plants by communities around CBR, especially the Gunung Gede Pangrango National Park area. The selected IAS list was further analyzed by using Index Cultural Significant (ICS). Recent studies concluded that 88 species of IAS spread out in the CBR area. On the other hand, many studies showed that IAS is widely used by the related communities in the CBR area. About 41 species out of 88 IAS were used by the communities, mainly for medicinal purposes. Utilisations of the medicinal plant were rooted in their traditional knowledge and culturally important for the communities’ livelihood. Additional input or recommendation for IAS management and policy in CBR was formulated by considering these conditions.

Double-edged effects of climate change on plant invasions: Ecological niche modeling global distributions of two invasive alien plants

The prediction of the potential distribution of invasive alien species is key for the control of their proliferation. This study developed ensemble niche models to explore the distribution patterns of Cecropia peltata and Ulex europaeus under baseline and future conditions, as well as the factors that regulate them. The models were based on occurrence records as well as climate, land-use and topography datasets. Climatic factors played a stronger role than land-use and topographical factors in their distribution patterns. Additionally, temperature seasonality and temperature annual range were the optimal predictor for the global distributions of C. peltata and U. europaeus, respectively. Under the baseline-RCP 8.5 scenario in 2070, significant increases in habitat suitability for C. peltata were generally detected in tropical regions, while for U. europaeus under the same condition, significant increases in habitat suitability were generally observed in west coast of South America and Europe, suggesting the impacts of climate changes on species distribution may be species specific. The contrast changes of suitable habitat areas for U. europaeus under the baseline-2.6 and 8.5 scenarios may suggest that the scenarios of climate changes may modify its distribution patterns and variations in suitable habitats. The double-edged effects of global warming on plant invasions may be a result of the scenario specific climate change and the species-specific responses to changes in climate. Our findings highlight the importance of climate change scenario specific and species-specific research on the impact of climate change on plant invasions.

Global warming promotes biological invasion of a honey bee pest.

Climate change and biological invasions are two major global environmental challenges. Both may interact, e.g. via altered impact and distribution of invasive alien species. Even though invasive species play a key role for compromising the health of honey bees, the impact of climate change on the severity of such species is still unknown. The small hive beetle (SHB, Aethina tumida, Murray) is a parasite of honey bee colonies. It is endemic to sub‐Saharan Africa and has established populations on all continents except Antarctica. Since SHBs pupate in soil, pupation performance is governed foremost by two abiotic factors, soil temperature and moisture, which will be affected by climate change. Here, we investigated SHB invasion risk globally under current and future climate scenarios. We modelled survival and development time during pupation (=pupal performance) in response to soil temperature and soil moisture using published and novel experimental data. Presence data on SHB distribution were used for model validation. We then linked the model with global soil data in order to classify areas (resolution: 10 arcmin; i.e. 18.6 km at the equator) as unsuitable, marginal and suitable for SHB pupation performance. Under the current climate, the results show that many areas globally yet uninvaded are actually suitable, suggesting considerable SHB invasion risk. Future scenarios of global warming project a vehement increase in climatic suitability for SHB and corresponding potential for invasion, especially in the temperate regions of the Northern hemisphere, thereby creating demand for enhanced and adapted mitigation and management. Our analysis shows, for the first time, effects of global warming on a honey bee pest and will help areas at risk to prepare adequately. In conclusion, this is a clear case for global warming promoting biological invasion of a pest species with severe potential to harm important pollinator species globally.

Making choices that matter – Use of statistical regularization in species distribution modelling for identification of climatic indicators – A case study with Mikania micrantha Kunth in India

Biological invasions by alien non-indigenous species are one of the major problems of the present era which impose massive environmental and socio-economic costs. In India about 40% of the floral species have long been recognized to be aliens, but the need for priority conservation efforts has only been felt since the turn of the century. Thus, it is now of utmost importance to predict the potential distribution of invasive alien species and identify suitable environmental conditions that allow the species to spread rapidly.The invasive plant Mikania micrantha was chosen as the test species. Native occurrence records (longitude and latitude) were obtained from the Global Biodiversity Information Facility (GBIF). For Indian occurrences, GBIF records were supplemented with occurrences from herbaria label data and information gathered from published literature. Nineteen climatic variables were obtained from World-Clim databse.To predict the potential distribution, species distribution models (SDMs) were built by using logistic regression and the climatic variables were chosen by using two cross-validated regularization methods induced by least absolute shrinkage and selection operator (lasso) and the ridge penalty function. This approach has twofold benefits; it deals with the multicollinearity problem efficiently and selects the raw environmental covariates. Fβ-score was utilized to measure the models’ performance. Combining the data from both native and alien ranges, seven environmental predictors were selected using four different background choices. Using lasso penalty, mean diurnal range (mean of monthly (max temp – min temp)) (BIO2), Isothermality (BIO2/BIO7) (×100) (BIO3), Temperature Annual Range (BIO5-BIO6) (BIO7), Precipitation of Wettest Month (BIO13), Precipitation Seasonality (Coefficient of Variation) (BIO15) and Precipitation of Warmest Quarter (BIO18) were found to be strong correlates for all four backgrounds. The predicted probabilities from the model containing these seven selected variables, demonstrated higher invasion risk in the central part of India than the model containing all the predictors.Accurate analysis of present distributions and effective predictive modelling of future distributions of invasive alien species is of vital importance for the early detection of the invasion and rapid remedial actions downstream. This study may aid in the adoption of management initiatives like early detection and rapid response. This could result in identifying both new populations and established populations to be prioritized for management.

THÀNH PHẦN LOÀI VÀ ĐẶC ĐIỂM PHÂN BỐ SINH VẬT NGOẠI LAI XÂM HẠI TRÊN ĐỊA BÀN HUYỆN TƯ NGHĨA, TỈNH QUẢNG NGÃI

The main objective of this paper is to study the species composition and distribu-tion of invasive alien species in Tu Nghia district, Quang Ngai province. The study was car-ried out from September 2017 to March 2018 in 15 major sites. Fourteen alien species belonging to in 13 genera, 11 families, 10 orders of the 3 phyla: Magnoliophyta, Chordata, and Mollusca were identified in the studied area, among which there were 11 invasive alien species (78.57%) and 3 potential invasive alien species (21.43%). The study has also evaluated the distribution of five common invasive alien species in Tu Nghia district that greatly affect agriculture, forestry, and aquaculture.

Does governance play a role in the distribution of invasive alien species?

Invasive alien species (IAS) constitute a major threat to global biological diversity. In order to control their spread, a detailed understanding of the factors influencing their distribution is essential. Although international trade is regarded as a major force structuring spatial patterns of IAS, the role of other social factors remains unclear. Despite studies highlighting the importance of strong governance in slowing drivers of biodiversity loss such as logging, deforestation, and agricultural intensification, no study has yet analyzed its contribution to the issue of IAS. Using estimates of governance quality and comprehensive spatiotemporal IAS data, we performed multiple linear regressions to investigate the effect of governance quality upon the distribution of species listed under “100 of the worst” IAS in 38 Eurasian countries as defined by DASIE. Our model suggested that for countries with higher GDP, stronger governance was associated with a greater number of the worst IAS; in contrast, for the lowest GDP countries under analysis, stronger governance was associated with fewer of these IAS. We elucidate how the quality of governance within a country has implications for trade, tourism, transport, legislation, and economic development, all of which influence the spread of IAS. While our findings support the common assumption that strengthening governance benefits conservation interventions in countries of smaller economy, we find that this effect is not universal. Stronger governance alone cannot adequately address the problem of IAS, and targeted action is required in relatively high‐GDP countries in order to stem the influx of IAS associated with high volumes of trade.

Distribution of invasive plants in urban environment is strongly spatially structured

Context Urban environments create a wide range of habitats that harbour a great diversity of plant species, many of which are of alien origin. For future urban planning and management of the green areas within the city, understanding of the spatial distribution of invasive alien species is of great importance.

Native vegetation pattern and the spread of three invasive species in Palani Hill National Park, Western Ghats of India

Invasions by exotic plants threaten the biodiversity and integrity of Protected Areas (PAs) by manipulating the species composition, the nutrient cycling and the hydrology prevailing in the specific habitat. Invasion of plant species in the natural ecosystem especially in the precincts of Western Ghats is due to rampant anthropogenic pressures. Complete assessment of the vegetation, richness distribution of Invasive Alien Species (IAS) and their association with the environmental drivers is essential to manage the PAs effectively. The present study analyses the richness of native vegetation with a comparative view on the distribution of Lantana camara, Chromolena odorata and Pteridium aquilinum in proposed Palani Hill National Park (PHNP), Western Ghats of Tamil Nadu. Secondly prepare models of the distribution of the target invasive species in the region. The biotic and abiotic data along with the vegetation type were generated and overlaid on IAS distribution to model the spread of target plant species. The study revealed that the distribution of invasive species negative relationship between the native species richness and positive relationship between the species dominance. Among the forest types dry evergreen, moist deciduous and tree savanna were found to be more vulnerable to invasion of Lantana camara and Chromolena odorata, wherein tree savanna and plantation were more vulnerable to invasion of Pteridium aquilinum. The information will strongly support effective management of Protected Areas.

Assessing and predicting the spread of non-native raccoons in Germany using hunting bag data and dispersal weighted models

As the second largest cause of biodiversity loss worldwide, there is an urgent need to study the dynamics of biological invasions and identify factors limiting the distribution of invasive alien species. In the present study we analyze national-scale hunting bag data from Germany to predict the dispersal of raccoons in the largest non-native population of the species. Our focus is (1) to document changes in the distribution and abundance of raccoons, (2) to identify the species–environment relationship and predict which areas will be suitable for future colonization and (3) to apply a dispersal model to predict how fast the raccoon will spread to these areas. The increase from about 9000 harvested raccoons in 2000/01 to about 71,000 in 2011/12 reflects the extensive amount of suitable habitat for this omnivorous species in Central Europe. The best model for explaining range expansion in Germany identified coverage of agriculture and fragmentation and coverage of forests as the most important explanatory variables. The range of raccoons (area with harvest index >0.1 per 100 ha) increased from 26,515 km2 in 2001 to 111,630 km2 in 2011, and is predicted to expand to 252,940 km2 by 2061, 71 % of the area of Germany. This vast area encompasses strategically important areas for conservation biology, such as wetlands with endangered native terrapins. The combination of merging of separated introduced populations and accelerating population growth highlights the potential for future impacts of raccoons on native communities, ecosystems and economic life in Germany and Central Europe.

Natural Regeneration and Biological Invasion by Pinus caribaea Morelet in Two Vereda Sites: Woody Vegetation Response

Veredas are regarded as humid complexes of ecological, water and scenery significance in Cerrado biome related to water table outcrop. Direct alterations in these environments can lead to species diversity reduction and also facilitate biological invasion processes. Thus our study aims to investigate the natural regeneration, the coverage of woody vegetation and the invasive species in two sites in secondary successional stage in the central part of Cerrado biome. Our study was carried out at two sites located at Minas Gerais state, Brazil. We established plots randomly throughout transects laid perpendicularly to the vereda’s drain line. We used the line intercept method to analyze the vegetation coverage. We set five 10-m width transects in each of both areas, perpendicular to the vereda’s drain line to evaluate the distribution of invasive alien species in the two areas. The richness did not vary between communities (U = 67.50; p = 0.061); on the other hand we found significant difference in density estimates (U = 36.50; p = 0.002). We found significant difference between categories for soil coverage in both sites. Grasses showed the highest coverage when compared to the other categories (K = 45.06; p < 0.001 for site 1 and K = 67.47; p < 0.001 for site 2). We observed a zonation tendency in site 1, with a higher native grass coverage at middle and backwards zones (K = 7.734, p < 0.05). We only found Pinus caribaea Morelet individuals in the invasive species survey. We recorded 46 Pinus caribaea individuals at site 1 and 116 Pinus caribaea individuals at site 2. From the latter group we found 13 individuals within the vereda and 103 in the surrounding vegetation. Both sites have a high natural woody plant regeneration potential although the presence of alien grasses in the veredas’ edge and Pinus caribaea all over the humidity gradient highlights the vulnerability of these areas to biological invasion.

Geographic Origins of Invasive Alien Species in “Iron Gates” Natural Park (Banat, Romania)

Abstract The paper presents an inventory and distribution of invasive alien species, in “Iron Gates” Natural Park, especially to highlight their origins, the most aggressive alien species, and their impact on conservation status of habitats, and indirectly their economic and sociological impact on the human communities. This study may have an important role in improving the efficiency of conservation measures, offering valuable information to authorities involved in protected areas administration.