Species distribution models can be used to direct early detection of invasive species, if they include proxies for invasion pathways. Due to the dynamic nature of invasion, these models violate assumptions of stationarity across space and time. To compensate for issues of stationarity, we iteratively update regionalized species distribution models annually for European gypsy moth (Lymantria dispar dispar) to target early detection surveys for the USDA APHIS gypsy moth program. We defined regions based on the distances from the invasion spread front where shifts in variable importance occurred and included models for the non-quarantine portion of the state of Maine, a short-range region, an intermediate region, and a long-range region. We considered variables that represented potential gypsy moth movement pathways within each region, including transportation networks, recreational activities, urban characteristics, and household movement data originating from gypsy moth infested areas (U.S. Postal Service address forwarding data). We updated the models annually, linked the models to an early detection survey design, and validated the models for the following year using predicted risk at new positive detection locations. Human-assisted pathways data, such as address forwarding, became increasingly important predictors of gypsy moth detection in the intermediate-range geographic model as more predictor data accumulated over time (relative importance = 5.9%, 17.36%, and 35.76% for 2015, 2016, and 2018, respectively). Receiver operating curves showed increasing performance for iterative annual models (area under the curve (AUC) = 0.63, 0.76, and 0.84 for 2014, 2015, and 2016 models, respectively), and boxplots of predicted risk each year showed increasing accuracy and precision of following year positive detection locations. The inclusion of human-assisted pathway predictors combined with the strategy of iterative modeling brings significant advantages to targeting early detection of invasive species. We present the first published example of iterative species distribution modeling for invasive species in an operational context.

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components’ importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high‐risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info‐gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base.

Phytophthora alni subspecies alni Brasier and S.A. Kirk is a recently hybridized soil and waterborne pathogen causing root and collar rot of species of the genus Alnus spp. (alder). It has quickly spread throughout Europe via planting of infested nursery stock and irrigating fields with infested river water. Once introduced, the pathogen spreads naturally by means of streams, floods, and other drainage water. Phytophthora alni can also be passively transported with the bare-root nursery stock, as it is able to adhere to and infect fine roots of visually symptomless plants of alder and other tree species exposed to the pathogen. We used a classification tree on 434 infested and healthy sample points to determine the required conditions for P. alni to successfully infest a nonflooded forest site. Sample points had been collected from 2003 through 2006, and a potential distribution surface was created for forested areas in Bavaria. A tenfold cross-validation accuracy of 78 percent was attained. To understand the potential hazard posed by P. alni elsewhere in the world, the rules from the Bavarian classification tree were applied along with additional expert knowledge in a multicriteria model to create a global susceptibility surface for P. alni.

Recently reported, and likely to threaten the health of standing trees in the urban and peri-urban forests of the West, are at least five new subcortical insect/pathogen complexes [Agrilus coxalis Waterhouse (Buprestidae) and four species of Scolytidae: Orthotomicus (Ips) erosus (Wollaston), Hylurgus lignipderda F., Scolytus schevyrewi Semenov, and Pityophthorus juglandis Blackman, which vectors the invasive fungus, Geosmithia sp.]. Through the Forest Insect and Disease Leaflet and Pest Alert series and other extension-type publications, personnel from USDA Forest Service Research and Development (R&D) have worked closely with USDA Forest Service Forest Health Protection (FHP) specialists in the western regions to disseminate information to the public on the distribution, identification, biology, and potential impact of these new pests to western U.S. forests. Because the Mediterranean pine engraver, O. erosus, has the most potential to have a strong impact on conifers in western U.S. forests and elsewhere in North America, we focus on this species as a case study for the development of a species-specific national risk map (=Potential Susceptibility map) to illustrate how USDA Forest Service R&D and USDA Forest Service FHP [in this case the Forest Health Technology Enterprise Team (FHTET)], can work cooperatively to address an issue of pressing national concern.

Nonindigenous species have caused significant impacts to North American forests despite past and present international phytosanitary efforts. Though broadly acknowledged, the risks of pest invasions are difficult to quantify as they involve interactions between many factors that operate across a range of spatial and temporal scales: the transmission of invading organisms via various pathways, their spread and establishment in new environments. Our study presents a stochastic simulation approach to quantify these risks and associated uncertainties through time in a unified fashion. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. We simulate new potential entries of S. noctilio as a stochastic process, based on recent volumes of marine shipments of commodities from countries where S. noctilio is established, as well as the broad dynamics of foreign marine imports. The results are then linked with a spatial model that simulates the spread of S. noctilio within the geographical distribution of its hosts (pines) while incorporating existing knowledge about its behavior in North American landscapes. Through replications, this approach yields a spatial representation of S. noctilio risks and uncertainties in a single integrated product. The approach should also be appealing to decisionmakers, since it accounts for projected flows of commodities that may serve as conduits for pest entry. Our 30‐year forecasts indicate high establishment probability in Ontario, Quebec, and the northeastern United States, but further southward expansion of S. noctilio is uncertain, ultimately depending on the impact of recent international treatment standards for wood packing materials.

We developed a methodology and compared results for predicting the potential distribution of Ceratocystis fagacearum (causal agent of oak wilt), in both Anoka County, MN, and Fort Hood, TX. The Potential Distribution of Oak Wilt (PDOW) utilizes a binary classification tree statistical technique that incorporates: geographical information systems (GIS); field sample data; commonly available, inexpensive, coarse-resolution auxiliary data; and satellite imagery from both Landsat Thematic Mapper (TM) and SPOT to predict the spatial distribution of oak wilt. Two types of model evaluations were conducted -- a ten-fold cross validation and an assessment using additional oak wilt data that had been verified in the field. These evaluations indicated that at the landscape scale PDOW correctly models the presence of oak wilt, and accurately predicts oak wilt distribution in Anoka County, MN and Fort Hood, TX.

Oak wilt (Ceratocystis fagacearum), a fungal disease that causes some species of oak trees to wilt and die rapidly, is a threat to oak forested resources in 22 states in the United States. We developed a methodology for predicting the Potential Distribution of Oak Wilt (PDOW) using Anoka County, Minnesota as our study area. The PDOW utilizes GIS; the classification tree statistical test; field sample data; commonly acquired, coarse-resolution auxiliary data; and a unique application of data from the Landsat Thematic Mapper (TM) satellite to predict the spatial distribution of oak wilt. Two accuracy assessments, one being a ten-fold cross validation, the other using verified oak wilt data from a later date, indicate that, at the landscape scale, PDOW correctly models the presence of oak wilt, and accurately predicts oak wilt distribution in Anoka County. Important variables in predicting oak wilt distribution in Anoka County included: Landsat TM Bands 3, 4, 5, and 7; distances between sample sites and lakes (Distance to Lakes); density of streams within a 400 x 400 meter grid surface (Stream Density); slope; aspect; and density of roads within a 400 x 400 meter grid surface (Road Density).

We present a synoptic assessment intended to maximize the benefits to wetland species biodiversity gained through Clean Water Act regulatory efforts within 225 sub-basins in Missouri, Iowa, Nebraska and Kansas (US Environmental Protection Agency, Region 7), USA. Our assessment provides a method for prioritizing sub-basins potentially critical for supporting wetland species biodiversity and may assist environmental managers and conservationists constrained by limited resources. We prioritize sub-basins based on the projected increase in the risk of wetland species extirpation across Region 7 that would be avoided by applying a unit of regulatory protection effort within a sub-basin. Because the projected increase in risk avoided per unit effort has not been directly measured, we represent this quantity with an index of indicators drawn from readily available data. A conceptual model incorporating landscape and anthropogenic factors guides index development via a series of simple benefit-cost equations. We rank and map the final index scores to show the relative priority among sub-basins for protection effort. High priority sub-basins appear to be concentrated along the major river systems within the region, where sensitive wetland species and intensive agriculture tend to coincide. Protection of wetland species biodiversity is an important, but not exclusive, attribute around which priorities should be set. Nevertheless, incorporation of our results into management strategies should allow managers to cast their local decisions in the context of regional scale maintenance of wetland species biodiversity, increasing ecological benefits for a given protection effort.

Our present understanding of the population structure and biology of Nomia triangulifera, a solitary halictine sweat bee, suggests that genetic variability should exist, however we determined that eight allozyme loci were monomorphic both within a nesting site and among five discrete populations. Further study may reveal that polymorphisms exist at other loci, or that populations have sufficient gene flow between them to preclude variability. Nomia triangulifera may have low levels of polymorphisms because of haplodiploidy, reduced effective population size, or from occupying homogeneous niches which tend to produce selection pressures favoring monomorphism.

During germination of the spore of the sensitive fernOnoclea sensibilis L. the nucleus migrates from a central position to the proximal face and then to one end of the ellipsoidal spore. An asymmetric cell division follows giving rise to a small cell which differentiates immediately into a rhizoid, and a large cell which divides further to give rise to the prothallus. The proximal face of the spore coat is differentiated from the remainder of the spore by its ability to bind nickel ions under certain conditions and by its staining with a sulfide-silver procedure which localizes heavy metals. The inner portion of the exine at the proximal face is differentiated from the outer part by its ability to stain with sulfide-silver at specific periods during germination. The exine at the proximal face also contains pore-like structures 50 nm in diameter which extend from the inner layer of the exine to the outer surface. Sulfide-silver staining material appears to be extruded through the pores at specific periods during germination. The percentage of spores showing nickel-binding and sulfide-silver stainability increases sharply during the first two to four hours of imbibition, then decreases sharply during the following two hours. This is followed by a second rise in staining at 8 to 12 hours of imbibition.