Co-occurring nonnative woody shrubs have additive and non-additive soil legacies.

To maximize limited conservation funds and prioritize management projects that are likely to succeed, accurate assessment of invasive nonnative species impacts is essential. A common challenge to prioritization is a limited knowledge of the difference between the impacts of a single nonnative species compared to the impacts of nonnative species when they co-occur, and in particular predicting when impacts of co-occurring nonnative species will be non-additive. Understanding non-additivity is important for management decisions because the management of only one co-occurring invader will not necessarily lead to a predictable reduction in the impact or growth of the other nonnative plant. Nonnative plants are frequently associated with changes in soil biotic and abiotic characteristics, which lead to plant-soil interactions that influence the performance of other species grown in those soils. Whether co-occurring nonnative plants alter soil properties additively or non-additively relative to their effects on soils when they grow in monoculture is rarely addressed. We use a greenhouse plant-soil feedback experiment to test for non-additive soil impacts of two common invasive nonnative woody shrubs, Lonicera maackii and Ligustrum sinense, in deciduous forests of the southeastern United States. We measured the performance of each nonnative shrub, a native herbaceous community, and a nonnative woody vine in soils conditioned by each shrub singly or together in polyculture. Soils conditioned by both nonnative shrubs had non-additive impacts on native and nonnative performance. Root mass of the native herbaceous community was 1.5 times lower and the root mass of the nonnative L. sinense was 1.8 times higher in soils conditioned by both L. maackii and L. sinense than expected based upon growth in soils conditioned by either shrub singly. This result indicates that when these two nonnative shrubs co-occur, their influence on soils disproportionally favors persistence of the nonnative L. sinense relative to this native herbaceous community, and could provide an explanation of why native species abundance is frequently depressed in these communities. Additionally, the difference between native and nonnative performance demonstrates that invasive impact studies focusing on the impact only of single species can be insufficient for determining the impact of co-occurring invasive plant species.

Integrated assessment of biological invasions.

As the main witnesses of the ecological and economic impacts of invasions on ecosystems around the world, ecologists seek to provide the relevant science that informs managers about the potential for invasion of specific organisms in their region(s) of interest. Yet, the assorted literature that could inform such forecasts is rarely integrated to do so, and further, the diverse nature of the data available complicates synthesis and quantitative prediction. Here we present a set of analytical tools for synthesizing different levels of distributional and/or demographic data to produce meaningful assessments of invasion potential that can guide management at multiple phases of ongoing invasions, from dispersal to colonization to proliferation. We illustrate the utility of data-synthesis and data-model assimilation approaches with case studies of three well-known invasive species--a vine, a marine mussel, and a freshwater crayfish--under current and projected future climatic conditions. Results from the integrated assessments reflect the complexity of the invasion process and show that the most relevant climatic variables can have contrasting effects or operate at different intensities across habitat types. As a consequence, for two of the study species climate trends will increase the likelihood of invasion in some habitats and decrease it in others. Our results identified and quantified both bottlenecks and windows of opportunity for invasion, mainly related to the role of human uses of the landscape or to disruption of the flow of resources. The approach we describe has a high potential to enhance model realism, explanatory insight, and predictive capability, generating information that can inform management decisions and optimize phase-specific prevention and control efforts for a wide range of biological invasions.

Developing dynamic mechanistic species distribution models: predicting bird-mediated spread of invasive plants across northeastern North America.

Species distribution models are a fundamental tool in ecology, conservation biology, and biogeography and typically identify potential species distributions using static phenomenological models. We demonstrate the importance of complementing these popular models with spatially explicit, dynamic mechanistic models that link potential and realized distributions. We develop general grid-based, pattern-oriented spread models incorporating three mechanisms--plant population growth, local dispersal, and long-distance dispersal--to predict broadscale spread patterns in heterogeneous landscapes. We use the model to examine the spread of the invasive Celastrus orbiculatus (Oriental bittersweet) by Sturnus vulgaris (European starling) across northeastern North America. We find excellent quantitative agreement with historical spread records over the last century that are critically linked to the geometry of heterogeneous landscapes and each of the explanatory mechanisms considered. Spread of bittersweet before 1960 was primarily driven by high growth rates in developed and agricultural landscapes, while subsequent spread was mediated by expansion into deciduous and coniferous forests. Large, continuous patches of coniferous forests may substantially impede invasion. The success of C. orbiculatus and its potential mutualism with S. vulgaris suggest troubling predictions for the spread of other invasive, fleshy-fruited plant species across northeastern North America.

[Effects of exogenous spermidine and spermine on Celastrus orbiculatus antioxidant system under soil NaHCO3 stress].

This paper studied the effects of foliar spraying spermidine and spermine on the leaf antioxidant system of Celastrus orbiculatus under soil NaHCO3 stress. The results showed that under the stress, spraying spermidine and spermine could significantly decrease the leaf O2-* production rate, H2O2 and MDA contents, and electrolyte leakage of C. orbiculatus (P < 0.05). Spraying spermidine increased the leaf SOD, CAT, POD and APX activities and GSH, CAR and Pro contents obviously, but had no effect on leaf AsA content. Spraying spermine also increased leaf POD and APX activities and GSH, CAR and Pro contents obviously, but had lesser effect on leaf SOD activity and AsA content, and even, caused a significant decrease in leaf CAT activity. In the meantime, spermidine and spermine effectively improved the growth of C. orbiculatus seedlings. It was suggested that under soil NaHCO3 stress, exogenous spermidine and spermine could improve the functions of membrane protective system and decrease the O2-* accumulation in C. orbiculatus leaves, and consequently, increase the C. orbiculatus tolerance to NaHCO3 exposure.

Hierarchical models facilitate spatial analysis of large data sets: a case study on invasive plant species in the northeastern United States.

Many critical ecological issues require the analysis of large spatial point data sets - for example, modelling species distributions, abundance and spread from survey data. But modelling spatial relationships, especially in large point data sets, presents major computational challenges. We use a novel Bayesian hierarchical statistical approach, 'spatial predictive process' modelling, to predict the distribution of a major invasive plant species, Celastrus orbiculatus, in the northeastern USA. The model runs orders of magnitude faster than traditional geostatistical models on a large data set of c. 4000 points, and performs better than generalized linear models, generalized additive models and geographically weighted regression in cross-validation. We also use this approach to model simultaneously the distributions of a set of four major invasive species in a spatially explicit multivariate model. This multispecies analysis demonstrates that some pairs of species exhibit negative residual spatial covariation, suggesting potential competitive interaction or divergent responses to unmeasured factors.