Lost in the weeds: Ligustrum sinense reduces native plant growth and survival

Greene, Brian T.; Blossey, Bernd

doi:10.1007/s10530-011-9990-1

Cited by 55 publications

(69 citation statements)

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“…Its ability to tolerate both flooding and shade makes it well suited to the floodplains and riparian zones of forests (Brown and Pezeshki, 2000). The abundance of L. sinense threatens forest ecosystems by altering the diversity, composition, and structure of forests (Greene and Blossey, 2012). The growing threat of large-scale ecosystem modification by L. sinense is of extreme concern for land managers and conservationists in the United States (Hanula et al, 2009).…”

Section: Study Systemmentioning

confidence: 99%

Detecting understory plant invasion in urban forests using LiDAR

Singh

Davis

Meentemeyer

2015

International Journal of Applied Earth Observation and Geoinfor

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a b s t r a c tLight detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Ligustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L. sinense occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized into the following groups: overstory, understory, topography, and overall vegetation characteristics, and IKONOS spectral features -optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L. sinense. We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming IKONOS data by 17.5% and the integration of LiDAR and IKONOS data by 5.3%. The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L. sinense.

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Section: Study Systemmentioning

confidence: 99%

Detecting understory plant invasion in urban forests using LiDAR

Singh

Davis

Meentemeyer

2015

International Journal of Applied Earth Observation and Geoinfor

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“…Before wetland restoration, the introduced species L. sinense was a major understory woody shrub that could effectively reduce native biodiversity (Greene and Blossey, 2012). L. sinense does not produce seeds in abundance until it reaches large stature in sunny conditions (Morris et al, 2002).…”

Section: Invasive Speciesmentioning

confidence: 99%

A five year study of floristic succession in a restored urban wetland

Richardson

2013

Ecological Engineering

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a b s t r a c tThe Stream and Wetland Assessment Management Park (SWAMP) project created a wetland-stream complex that encompasses a wide array of micro-environments and hydrology. These diverse habitats were designed to facilitate ecosystem diversity via enhanced pathways for ecological succession during restoration. We took an empirical approach to examine floral succession under natural processes following wetland restoration of floodplain and marsh habitats. Survey plots were set up in four forest gaps in palustrine wetlands, each containing a Low Marsh and a High Marsh. During five years of recovery from the soil disturbance and upland vegetation removal, wetland species richness gradually increased from 24 to 38 species in the Low Marshes, where waterlogged conditions precluded upland species invasions. Conversely, upland species richness quickly declined from 69 to 29 species over time in the High Marsh, now subjected to increase flooding. The species successional patterns suggest a slower turnover in the wet Low Marsh, but faster turnover in the moist High Marsh. Following the intermediate disturbance hypothesis, we observed that High Marsh species richness reached its maximum in the first year of the vegetation survey, whereas even after five years the plant diversity in the Low Marsh has yet to peak. The once widespread Ligustrum sinense (Chinese privet) was decimated following the SWAMP restoration. However, the exotic invasive species, Microstegium vimineum (Japanese stilt grass) dominated the floodplain except in the wettest Low Marsh sites. Given the successional patterns of increased wetland species following restoration, we recommend removal of woody invasive species such as L. sinense to prevent their re-establishment followed by long-term monitoring and continued removal (5-7 years) of invasive species to allow native species establishment. Our study shows that the creation of wetter floodplain habitats with increased flooding suppresses the establishment of the highly invasive M. vimineum.

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“…It has become widely naturalized in the southeastern United States and is reported to have invaded thousands of acres (Mitchell et al 2011;Ward 2002). It generally has multiple stems and a shrub-like growth form, with heights ranging from 1.5 to 3.6 m (5 to 12 ft), although it occasionally becomes treesized (Greene and Blossey 2011). CHP has a shallow but extensive root system and it readily forms dense monotypic thickets in forest understories, in many cases converting open park-like forest floors into impenetrable walls of dense vegetation (Greene and Blossey 2011).…”

mentioning

confidence: 99%

“…It generally has multiple stems and a shrub-like growth form, with heights ranging from 1.5 to 3.6 m (5 to 12 ft), although it occasionally becomes treesized (Greene and Blossey 2011). CHP has a shallow but extensive root system and it readily forms dense monotypic thickets in forest understories, in many cases converting open park-like forest floors into impenetrable walls of dense vegetation (Greene and Blossey 2011). The transformative success of CHP in forest ecosystems is thought to be largely due to its prolific production of viable seeds and the dispersal of these seeds by birds (Panetta 2000), flowing water (Ward 2002), and other agents.…”

mentioning

confidence: 99%

“…Research in the Piedmont region of the United States has indicated that CHP invasion suppresses herbaceous understory, causing decreases in plant species richness and diversity (Greene and Blossey 2011;Merriam and Feil 2002;Wilcox and Beck 2007). CHP litter has a lower C : N ratio than most of the understory vegetation that it displaces, which results in accelerated nutrient mineralization, especially during summer months (Mitchell et al 2011).…”

mentioning

confidence: 99%

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The Role of Soil and Landscape Factors in Chinese Privet (Ligustrum sinense) Invasion in the Appalachian Piedmont

Hagan

Mikhailova

Shearman

et al. 2014

Invasive plant sci. manag.

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There is a limited understanding about the ecological mechanisms that enable certain plant species to become successful invaders of natural areas. This study was conducted to determine the soil and landscape characteristics that correlate with invasion of Chinese privet (CHP), and to develop a model to predict the probability of CHP invasion in Piedmont forests. A landscape ecosystem classification (LEC) system—based on the percentage of clay in the B horizon, depth to maximum clay (cm), exposure, terrain shape, and aspect (degrees)—was used to determine the soil moisture characteristics of invaded and uninvaded plots. Additional measurements included the cover classes of CHP and other species, litter depth (cm), slope (degrees), overstory basal area (m2 ha−1), and soil chemical properties. CHP invasion was negatively correlated with overstory basal area and slope and positively with litter depth and pH. A stepwise logistic regression model containing these four variables was highly sensitive, with an overall accuracy of 78%. Given the accuracy of this model, we propose that it can be used to calculate the probability of invasion in a given area, provided that some basic, readily obtainable site characteristics are known.

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Lost in the weeds: Ligustrum sinense reduces native plant growth and survival

Cited by 55 publications

References 50 publications

Detecting understory plant invasion in urban forests using LiDAR

Detecting understory plant invasion in urban forests using LiDAR

A five year study of floristic succession in a restored urban wetland

The Role of Soil and Landscape Factors in Chinese Privet (Ligustrum sinense) Invasion in the Appalachian Piedmont

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