Search Results (2)

Since Euro-American settlement and associated fire exclusion, grasslands and open forests have converted to forests throughout the United States. Contributing to the weight of evidence, we determined if forestation also occurred in forests and grasslands of Colorado. Our study extent encompassed landscapes of the 0.5 million ha Arapaho and Roosevelt National Forests in the northern Front Range (eastern side) of the southern Rocky Mountains and the 1 million ha Weld County, which contains Pawnee National Grassland, in the Great Plains grasslands. We quantified tree composition, cover, and densities from historical (years 1863 to 1886) tree surveys, current surveys (2002 to 2011), and land cover (2016) to identify departures. In the Arapaho and Roosevelt, historical lack of tree presence and overall low tree densities suggested an open landscape, due to about 70% of 7134 survey points without two trees within 60 m. The treed landscape, which was not continuously forested, had density estimates of about 153 trees/ha. In contrast, the current landscape was 68% forested with high tree densities; fire-dependent pines decreased relative to subalpine fir (Abies lasiocarpa) increases. In Weld County, seven trees were surveyed historically, whereas currently, woody cover totaled 2555 ha. Uniquely applying historical surveys at landscape scales, we documented an open landscape in the northern Front Range, unlike previous research, and rare tree presence in the relatively understudied grasslands of Colorado. Forestation corresponded with changes in U.S. grasslands and forests following Euro-American settlement and associated fire exclusion. Full article

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. Full article