The effects of temporally variable dispersal and landscape structure on invasive species spread

Many invasive species are too widespread to realistically eradicate. For such species, a viable management strategy is to slow the rate of spread. However, to be effective, this will require detailed spread data and an understanding of the influence of environmental conditions and landscape structure on invasion rates. We used a time series of remotely sensed distribution maps and a spatial simulation model to study spread of the invasive Lepidium latifolium (perennial pepperweed) in California's Sacramento-San Joaquin River Delta. L. latifolium is a noxious weed and exhibited rapid, explosive spread. Annual infested area and empirical dispersal kernels were derived from the remotely sensed distributions in order to assess the influence of weather conditions on spread and to parameterize the simulation model. Spread rates and dispersal distances were highest for nascent infestations and in years with wet springs. Simulations revealed that spread rates were more strongly influenced by the length of long-distance dispersal than by temporal variation in its likelihood. It is thus important to capture long-distance dispersal and the conditions that facilitate spread when collecting data to parameterize spread models. Additionally, management actions performed in high-spread years, targeting long-distance recruits, can effectively contain infestations. Corridors were relatively unimportant to spread rates; their effectiveness at enhancing rate of spread was limited by the species' dispersal ability and the time needed to travel through the corridor. In contrast, habitat abundance and shape surrounding the introduction site strongly influenced invasion dynamics. Satellite patches invading large areas of invasible habitat present especially high risk

Identifying and classifying water hyacinth (Eichhornia crassipes) using the HyMap sensor

In recent years, the impact of aquatic invasive species on biodiversity has become a major global concern. In the Sacramento-San Joaquin Delta region in the Central Valley of California, USA, dense infestations of the invasive aquatic emergent weed, water hyacinth (Eichhornia crassipes) interfere with ecosystem functioning. This silent invader constantly encroaches into waterways, eventually making them unusable by people and uninhabitable to aquatic fauna. Quantifying and mapping invasive plant species in aquatic ecosystems is important for efficient management and implementation of mitigation measures. This paper evaluates the ability of hyperspectral imagery, acquired using the HyMap sensor, for mapping water hyacinth in the Sacramento-San Joaquin Delta region. Classification was performed on sixty-four flightlines acquired over the study site using a decision tree which incorporated Spectral Angle Mapper (SAM) algorithm, absorption feature parameters in the spectral region between 0.4 and 2.5μm, and spectral endmembers. The total image dataset was 130GB. Spectral signatures of other emergent aquatic species like pennywort (Hydrocotyle ranunculoides) and water primrose (Ludwigia peploides) showed close similarity with the water hyacinth spectrum, however, the decision tree successfully discriminated water hyacinth from other emergent aquatic vegetation species. The classification algorithm showed high accuracy (K value = 0.8) in discriminating water hyacinth

Mapping successional boreal forests in interior central Alaska

Abstract. It is necessary to develop new satellite methods to monitor boreal forests responses to climate warming. Remotely sensed maps derived from hyper-spectral Advanced Visible/Infrared Imaging Spectrometer (AVIRIS) data were developed and compared for the four conifer forest ecosystems at the Bonanza Creek Experimental Forest, a long-term ecological research site on the Tanana River ood plain near Fairbanks,Alaska. The site was rst strati ed into montane, lowland alluvial plain, and ood plain zones based on topography. A classi cation of six forest and three non-forest types was created from AVIRIS images and compared on a pixel-by-pixel basis to a published vegetation map, a classi ed SPOT (Satellite Pour l’Observation de la Terre) image, and a hybrid SPOT image and digital elevation model classi cation. A comparison of AVIRIS with SPOT results showed that the AVIRIS classi cation was consistently more accurate (74, 43, and 43 % overall accuracy, respectively). Hyperspectral classi cation methods have promise for mapping forest ecosystems in other boreal regions when little or no ground data are available for validation. The time diVerence between the creation of these maps show that substantial ecosystem changes have occurred over the past 15 years, demonstrating the need for developing a capability to obtain cost-eVective landscape characterization. 1

The role of environmental context in mapping invasive plants with hyperspectral image data

Lepidium latifolium (perennial pepperweed) is a noxious Eurasian weed invading riparian and wetland areas of the western US. Effective management of Lepidium requires detailed, accurate maps of its distribution, as may be provided by remote sensing, to contain existing infestations and eradicate incipient populations. We mapped Lepidium with 3 m spatial resolution, 128-band HyMap image data in three sites of California's San Francisco Bay/Sacramento-San Joaquin Delta Estuary (Rush Ranch in Suisun Marsh and the Greater Jepson Prairie Ecosystem and the Cosumnes River Preserve in the Delta). These sites are markedly different in terms of hydrology, salinity, species composition, and structural and landscape diversity. Aggregated classification and regression tree models (CART), incorporating the results of mixture tuned matched filter (MTMF) analyses and spectral physiological indexes, were used to map Lepidium at the three sites. This approach was sufficiently flexible and robust to detect Lepidium with similar accuracies (~ 90%) at both Rush Ranch and Jepson Prairie, but was unsuccessful at Cosumnes River Preserve. Comparisons of the behavior of the MTMFs and the CARTs between sites reveal the importance of environmental context in species mapping. Rush Ranch presents the simplest conditions for mapping Lepidium: it is the wettest and least diverse site and Lepidium is spectrally distinct from co-occurring species. At Jepson Prairie, several co-occurring species closely resemble Lepidium spectrally. Nevertheless, hyperspectral data provide sufficient spectral detail to resolve Lepidium even at this challenging site, which is facilitated by phenological separation from the matrix of annual grasses. At Cosumnes River Preserve, however, Lepidium is neither spectrally nor phenologically distinct, and consequently could not be mapped successfully. Evidence suggests that the success of a remote sensing analysis declines as site complexity increases (species, structural, and landscape diversity; spectral variability; etc.), although this relationship is complex, indirect, and may be phenology-dependent

Habitat suitability modelling of an invasive plant with advanced remote sensing data

Lepidium latifolium (Brassicaceae; perennial pepperweed) is a noxious Eurasian weed invading riparian and wetland areas of the western USA. Understanding which sites are most susceptible to invasion by L. latifolium will allow more efficient management of this weed. We assessed the ability of advanced remote sensing techniques to develop habitat suitability models for L. latifolium. Location San Francisco Bay-Sacramento-San Joaquin River Delta, California, USA. Methods Lepidium latifolium distribution was mapped with hyperspectral image data of Rush Ranch Open Space Preserve, providing presence-absence data to train and validate habitat models. A high-resolution light detection and ranging digital elevation model was used to derive predictor environmental variables (distance to channel, distance to upland, elevation, slope, aspect and convexity). Aggregate decision tree models were used to predict the potential distribution of this species. Results Lepidium latifolium infested two zones: near the marshland-upland margin and along channels within the marsh. Topographical data, which are typically strongly correlated with wetland species distributions, were relatively unimportant to L. latifolium occurrence, although relevant microtopography information, particularly relative elevation, was subsumed in the distance to channel variable. The map of potential L. latifolium distribution reveals that Rush Ranch contains considerable habitat that it is susceptible to continued invasion. Main conclusions Lepidium latifolium invades relatively less stressful sites along the inundation and salinity gradients. Advanced remote sensing datasets were shown to be sufficient for species distribution modelling. Remote sensing offers powerful tools that deserve wider use in ecological research and management

Spectral and physiological uniqueness of perennial pepperweed (Lepidium latifolium)

Perennial pepperweed is an aggressive, exotic weed invading wetland and riparian areas in California, including the San Francisco Bay/Sacramento-San Joaquin Delta Estuary. Effective management will require detailed and accurate maps of its distribution. Remote sensing technologies offer the capability to map weed species over broad areas and with rapid return intervals. As a first step in assessing the potential to map perennial pepperweed with hyperspectral remote sensing data, this study determined its spectral uniqueness relative to co-occurring species. Spectral measurements were conducted during summer drought conditions in the Sacramento-San Joaquin Delta region. Reflectance spectra of perennial pepperweed and seven co-occurring species were collected with a portable spectrometer. Nineteen physiological indexes were calculated from the reflectance data. Physiological indexes are sensitive to narrow spectral features and encapsulate reflectance information in ecologically relevant ways. Classification trees generated from these indexes were able to discriminate both flowering and fruiting perennial pepperweed from co-occurring species with high levels of cross-validated accuracy when using the original spectrometer data and also when this data set was resampled to simulate the spectral resolution of two widely used airborne hyperspectral imagers. Perennial pepperweed's characteristic white flowers are the major component of the spectral uniqueness of this species. Phenological state influenced reflectance spectra more strongly than variation in intraseasonal maturity. Field spectrometer spectra were qualitatively and quantitatively similar to perennial pepperweed spectra extracted from airborne image data. These results suggest that hyperspectral remote sensing will be a powerful tool for the mapping and monitoring of perennial pepperweed. Future work will extend these analyses to image data encompassing the San Francisco Bay/Sacramento-San Joaquin Delta region

Effects of microtopography and hydrology on phenology of an invasive herb

Phenological traits may influence invasion success via effects on invasiveness of the colonizing species and invasibility of the receiving ecosystems. Many species exhibit substantial fine-scaled spatial variation in phenology and interannual differences in phenological timing in response to environmental variation. Yet describing and understanding this variation is limited by the availability of appropriate spatial and temporal datasets. Remote sensing provides such datasets, but has primarily been used to monitor broad-scale phenological patterns at coarse resolutions, necessarily missing fine spatial detail and intraspecies variation. We used hyperspectral remote sensing to characterize the spatial and temporal phenological variation of the invasive species Lepidium latifolium (perennial pepperweed) at two sites in California's San Francisco Bay/Sacramento-San Joaquin River Delta. Considerable phenological variation was detected: L. latifolium was simultaneously present in vegetative, early flowering, peak flowering, fruiting, and senescent stages in late June; the relative dominance and distribution of these stages varied interannually. Environmental determinants of phenology were investigated with variables derived from the hyperspectral image data, from a high resolution LiDAR (light detection and ranging) digital elevation model (DEM), and from local precipitation and streamflow data. Lepidium latifolium phenology was found to track water availability, and may also be influenced by intraspecific competition and edaphic stress. Lepidium latifolium has a unique phenology (summer flowering) relative to the communities it invades, which may allow invasion of an empty niche. Furthermore, many habitats are invaded by L. latifolium, which occurs in locally appropriate phenologies under the different environmental conditions. The environmental responsiveness of L. latifolium phenology may mediate the wide breadth of invasible habitats

Vertical Profile and Temporal Variation of Chlorophyll in Maize Canopy: Quantitative “Crop Vigor” Indicator by Means of Reflectance-Based Techniques

Chlorophyll (Chl) content is among the most important crop biophysical characteristics. Chlorophyll can be related to photosynthetic capacity, thus, productivity, developmental stage, and canopy stresses. The objective of this study was to quantify and characterize the temporal variation of Chl content in the vertical profile of maize (Zea mays L.) canopies by means of a reflectance-based, nondestructive methodology. A recently developed technique that relates leaf reflectance with leaf pigment content has been used for accurate leaf Chl estimation. The technique employs reflectance in two spectral bands: in the red edge (720-730 nm) and in the near infrared (770-800 nm). More than 2,000 maize leaves were measured for reflectance and total and green area during a growing season. A bell-shaped curve showed a very good fit for the vertical distribution of Chl content regardless of crop growth stage. The parameters and coefficients of the bell-shape function were found to be very useful to interpret temporal changes in the vertical profile of each variable. Comparisons among Chl, leaf area index (LAI) and green LAI showed that Chl content was more sensitive to changes in the physiological status of maize than other biophysical characteristics. The quantification of Chl content in canopy should be seen as a useful tool to complement the information on green LAI or LAI. Its applicability will help to improve the understanding of the crop ecophysiology, productivity, the radiation use efficiency and the interplant competition

Daily reference evapotranspiration for California using satellite imagery and weather station measurement interpolation

Important water resources in California's agricultural and urban landscapes are at risk without more efficient management strategies. Improved monitoring can increase the efficiency of water use and mitigate these potential risks. The California Irrigation Management Information System (CIMIS) programme helps farmers, turf managers, and other resource managers develop water budgets that improve irrigation scheduling and monitor water stress. The CIMIS system is a repository of meteorological data collected at over 130 computerised weather stations. These are located at key agricultural and municipal sites throughout California and provide comprehensive, timely, weather data collected hourly and daily. In this article, the CIMIS sensor system is combined with hourly NOAA Geostationary Operational Environmental Satellite (GOES) visible satellite data to develop a methodology to extend reference evapotranspiration ($ET_0$) station estimations to spatial daily ET0 maps of California. The maps are calculated on a (2 km)2 grid, a high spatial resolution compared with the density of CIMIS stations. The hourly GOES satellite images are used to estimate cloud cover, which are used in turn to modify clear sky radiation estimates. These are combined with interpolated CIMIS weather station meteorological data to satisfy the Penman–Monteith $ET_0$ equatio