David T. Barnett

The rich get richer: patterns of plant invasions in the United States

Observations from islands, small-scale experiments, and mathematical models have generally supported the paradigm that habitats of low plant diversity are more vulnerable to plant invasions than areas of high plant diversity. We summarize two independent data sets to show exactly the opposite pattern at multiple spatial scales. More significant, and alarming, is that hotspots of native plant diversity have been far more heavily invaded than areas of low plant diversity in most parts of the United States when considered at larger spatial scales. Our findings suggest that we cannot expect such hotspots to repel invasions, and that the threat of invasion is significant and predictably greatest in these areas.

Species richness and patterns of invasion in plants, birds, and fishes in the United States

We quantified broad-scale patterns of species richness and species density (mean # species/km2) for native and non-indigenous plants, birds, and fishes in the continental USA and Hawaii. We hypothesized that the species density of native and non-indigenous taxa would generally decrease in northern latitudes and higher elevations following declines in potential evapotranspiration, mean temperature, and precipitation. County data on plants (n = 3004 counties) and birds (n=3074 counties), and drainage (6 HUC) data on fishes (n = 328 drainages) showed that the densities of native and non-indigenous species were strongly positively correlated for plant species (r = 0.86, P < 0.0001), bird species (r = 0.93, P<0.0001), and fish species (r = 0.41, P<0.0001). Multiple regression models showed that the densities of native plant and bird species could be strongly predicted (adj. R2 = 0.66 in both models) at county levels, but fish species densities were less predictable at drainage levels (adj. R2 = 0.31, P<0.0001). Similarly, non-indigenous plant and bird species densities were strongly predictable (adj. R2 = 0.84 and 0.91 respectively), but non-indigenous fish species density was less predictable (adj. R2 = 0.38). County level hotspots of native and non-indigenous plants, birds, and fishes were located in low elevation areas close to the coast with high precipitation and productivity (vegetation carbon). We show that (1) native species richness can be moderately well predicted with abiotic factors; (2) human populations have tended to settle in areas rich in native species; and (3) the richness and density of non-indigenous plant, bird, and fish species can be accurately predicted from biotic and abiotic factors largely because they are positively correlated to native species densities. We conclude that while humans facilitate the initial establishment, invasions of non-indigenous species, the spread and subsequent distributions of non-indigenous species may be controlled largely by environmental factors.

PLANT SPECIES INVASIONS ALONG THE LATITUDINAL GRADIENT IN THE UNITED STATES

It has been long established that the richness of vascular plant species and many animal taxa decreases with increasing latitude, a pattern that very generally follows declines in actual and potential evapotranspiration, solar radiation, temperature, and thus, total productivity. Using county-level data on vascular plants from the United States (3000 counties in the conterminous 48 states), we used the Akaike Information Criterion (AIC) to evaluate competing models predicting native and nonnative plant species density (number of species per square kilometer in a county) from various combinations of biotic variables (e.g., native bird species density, vegetation carbon, normalized difference vegetation in- dex), environmental/topographic variables (elevation, variation in elevation, the number of land cover classes in the county, radiation, mean precipitation, actual evapotranspiration, and potential evapotranspiration), and human variables (human population density, crop- land, and percentage of disturbed lands in a county). We found no evidence of a latitudinal gradient for the density of native plant species and a significant, slightly positive latitudinal gradient for the density of nonnative plant species. We found stronger evidence of a sig- nificant, positive productivity gradient (vegetation carbon) for the density of native plant species and nonnative plant species. We found much stronger significant relationships when biotic, environmental/topographic, and human variables were used to predict native plant species density and nonnative plant species density. Biotic variables generally had far greater influence in multivariate models than human or environmental/topographic variables. Later, we found that the best, single, positive predictor of the density of nonnative plant species in a county was the density of native plant species in a county. While further study is needed, it may be that, while humans facilitate the initial establishment invasions of non- native plant species, the spread and subsequent distributions of nonnative species are con- trolled largely by biotic and environmental factors.

A nested-intensity design for surveying plant diversity

Managers of natural landscapes need cost-efficient, accurate, and precise systems to inventory plant diversity. We investigated a nested-intensity sampling design to assess local and landscape-scale heterogeneity of plant species richness in aspen stands in southern Colorado, USA. The nested-intensity design used three vegetation sampling techniques: the Modified-Whittaker, a 1000-m2 multiple-scale plot (n = 8); a 100-m2 multiple-scale Intensive plot (n = 15); and a 100-m2 single-scale Extensive plot (n = 28). The large Modified-Whittaker plot (1000 m2) recorded greater species richness per plot than the other two sampling techniques (P < 0.001), estimated cover of a greater number of species in 1-m2 subplots (P < 0.018), and captured 32 species missed by the smaller, more numerous 100-m2 plots of the other designs. The Intensive plots extended the environmental gradient sampled, capturing 17 species missed by the other techniques, and improved species–area calculations. The greater number of Extensive plots further expanded the gradient sampled, and captured 18 additional species. The multi-scale Modified-Whittaker and Intensive designs allowed quantification of the slopes of species–area curves in the single-scale Extensive plots. Multiple linear regressions were able to predict the slope of species–area curves (adj R2 = 0.64, P < 0.001) at each Extensive plot, allowing comparison of species richness at each sample location. Comparison of species–accumulation curves generated with each technique suggested that small, single-scale plot techniques might be very misleading because they underestimate species richness by missing locally rare species at every site. A combination of large and small multi-scale and single-scale plots greatly improves our understanding of native and exotic plant diversity patterns.

NEON terrestrial field observations: designing continental‐scale, standardized sampling

Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use, and species invasion across the United States for at least 30 years. Although NEON remote sensing and tower sensor elements are relatively well known, the biological measurements are not. This manuscript describes NEON terrestrial sampling, which targets organisms across a range of generation and turnover times, and a hierarchy of measurable biological states. Measurements encompass species diversity, abundance, phenology, demography, infectious disease, ecohydrology, and biogeochemistry. The continental-scale sampling requires collection of comparable and calibrated data using transparent methods. Data will be publicly available in a variety of formats and suitable for integration with other long-term efforts. NEON will provide users with the data necessary to address large-scale questions, challenge current ecological paradigms, and forecast ecological change.

Modeling the Present and Future Geographic Distribution of the Lone Star Tick, Amblyomma americanum (Ixodida: Ixodidae), in the Continental United States.

The Lone star tick (Amblyomma americanum L.) is the primary vector for pathogens of significant public health importance in North America, yet relatively little is known about its current and potential future distribution. Building on a published summary of tick collection records, we used an ensemble modeling approach to predict the present-day and future distribution of climatically suitable habitat for establishment of the Lone star tick within the continental United States. Of the nine climatic predictor variables included in our five present-day models, average vapor pressure in July was by far the most important determinant of suitable habitat. The present-day ensemble model predicted an essentially contiguous distribution of suitable habitat extending to the Atlantic coast east of the 100th western meridian and south of the 40th northern parallel, but excluding a high elevation region associated with the Appalachian Mountains. Future ensemble predictions for 2061-2080 forecasted a stable western range limit, northward expansion of suitable habitat into the Upper Midwest and western Pennsylvania, and range contraction along portions of the Gulf coast and the lower Mississippi river valley. These findings are informative for raising awareness of A. americanum-transmitted pathogens in areas where the Lone Star tick has recently or may become established.

Forecasting Weed Distributions using Climate Data: A GIS Early Warning Tool

Abstract The number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed by eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimatic envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that countys list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.

Ecology and Space: A Case Study in Mapping Harmful Invasive Species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass (Bromus tectorum) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

NEON Technical Memo 002 The NEON 2010 Airborne Pathfinder Campaign in Florida

The National Ecological Observatory Network (NEON) conducted a series of airborne flights and supporting ground measurements in two study areas located near Gainesville, Florida in August and September 2010. The primary objectives of the combined airborne and field campaign were to prototype data collection approaches and to evaluate data processing techniques planned for use in the processing of future NEON airborne remote sensing data. Since the instrumentation slated for deployment on the eventual AOP remote sensing payloads were not yet available, airborne spectroscopic and LiDAR measurements were made during this campaign using existing systems that exhibit similar performance characteristics as the instrumentation under development. Supporting ground measurements of vegetation spectra and structure, plant species identification and key atmospheric variables measurements were made. Ground-based leaf area index (LAI) measurements were made along several 500-meter transects located within the notional airshed of the planned NEON flux tower location in OSBS. Leaf area measurement were also made along six transects in the Donaldson tract. In OSBS, detailed structure measurements were made in a 20x120 meter area along one of the transects. These included measurements of tree height, height to first branch, canopy diameter, stem diameter, and species identification. Plant diversity data were collected in a number of plots dispersed throughout OSBS.