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The potential global distribution of an emerging forest pathogen, Lecanosticta acicola, under a changing climate
Nikica Ogris, Rein Drenkhan, Petr Vahalík, Thomas L. Cech, Martin Mullett, Katherine Tubby, 2023, original scientific article

Abstract: Brown spot needle blight (BSNB), caused by Lecanosticta acicola (Thüm.) Syd., is an emerging forest disease of Pinus species originating from North America and introduced to Europe and Asia. Severity and spread of the disease has increased in the last two decades in North America and Europe as a response to climate change. No modeling work on spread, severity, climatic suitability, or potential distribution has been done for this important emerging pathogen. This study utilizes a global dataset of 2,970 independent observations of L. acicola presence and absence from the geodatabase, together with Pinus spp. distribution data and 44 independent climatic and environmental variables. The objectives were to (1) identify which bioclimatic and environmental variables are most influential in the distribution of L. acicola; (2) compare four modeling approaches to determine which modeling method best fits the data; (3) examine the realized distribution of the pathogen under climatic conditions in the reference period (1971–2000); and (4) predict the potential future global distribution of the pathogen under various climate change scenarios. These objectives were achieved using a species distribution modeling. Four modeling approaches were tested: regression-based model, individual classification trees, bagging with three different base learners, and random forest. Altogether, eight models were developed. An ensemble of the three best models was used to make predictions for the potential distribution of L. acicola: bagging with random tree, bagging with logistic model trees, and random forest. Performance of the model ensemble was very good, with high precision (0.87) and very high AUC (0.94). The potential distribution of L. acicola was computed for five global climate models (GCM) and three combined pathways of Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (SSP-RCP): SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5. The results of the five GCMs were averaged on combined SSP-RCP (median) per 30-year period. Eight of 44 studied factors determined as most important in explaining L. acicola distribution were included in the models: mean diurnal temperature range, mean temperature of wettest quarter, precipitation of warmest quarter, precipitation seasonality, moisture in upper portion of soil column of wettest quarter, surface downwelling longwave radiation of driest quarter, surface downwelling shortwave radiation of warmest quarter and elevation. The actual distribution of L. acicola in the reference period 1971–2000 covered 5.9% of Pinus spp. area globally. However, the model ensemble predicted potential distribution of L. acicola to cover an average of 58.2% of Pinus species global cover in the reference period. Different climate change scenarios (five GCMs, three SSP-RCPs) showed a positive trend in possible range expansion of L. acicola for the period 1971–2100. The average model predictions toward the end of the century showed the potential distribution of L. acicola rising to 62.2, 61.9, 60.3% of Pinus spp. area for SSP1-RCP2.6, SSP2-RCP4.5, SSP5-RCP8.5, respectively. However, the 95% confidence interval encompassed 35.7–82.3% of global Pinus spp. area in the period 1971–2000 and 33.6–85.8% in the period 2071–2100. It was found that SSP-RCPs had a little effect on variability of BSNB potential distribution (60.3–62.2% in the period 2071–2100 for medium prediction). In contrast, GCMs had vast impact on the potential distribution of L. acicola (33.6–85.8% of global pines area). The maps of potential distribution of BSNB will assist forest managers in considering the risk of BSNB. The results will allow practitioners and policymakers to focus surveillance methods and implement appropriate management plans.
Keywords: brown spot needle blight, BSNB, pines, species distribution model, climate change, biosecurity
Published in DiRROS: 02.08.2023; Views: 176; Downloads: 124
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Comparing environmental impacts of alien plants, insects and pathogens in protected riparian forests
Katharina Lapin, Sven Bacher, Thomas L. Cech, Rok Damjanić, Franz Essl, Freya-Isabel Georges, Gernot Hoch, Andreja Kavčič, András Koltay, Saša Kostić, Ivan Lukić, Aleksander Marinšek, Laszlo Nagy, Sonja Novak Agbaba, Janine Oettel, Saša Orlović, Leopold Poljaković-Pajnik, Marcus Sallmannshofer, Martin Steinkellner, Srdjan Stojnić, Marjana Westergren, Milica Zlatković, Anita Zolles, Maarten De Groot, 2021, original scientific article

Abstract: The prioritization of alien species according to the magnitude of their environmental impacts has become increasingly important for the management of invasive alien species. In this study, we applied the Environmental Impact Classification of Alien Taxa (EICAT) to classify alien taxa from three different taxonomic groups to facilitate the prioritisation of management actions for the threatened riparian forests of the Mura-Drava-Danube Biosphere Reserve, South East Europe. With local experts we collated a list of 198 alien species (115 plants, 45 insects, and 38 fungi) with populations reported in southeast European forest ecosystems and included them in the EICAT. We found impact reports for 114 species. Eleven of these species caused local extinctions of a native species, 35 led to a population decrease, 51 to a reduction in performance in at least one native species and for 17 alien species no effects on individual fitness of native species were detected. Fungi had significantly highest impact and were more likely to have information on their impacts reported. Competition and parasitism were the most important impact mechanisms of alien species. This study is, to our knowledge, the first application of EICAT to all known alien species of several taxonomic groups in a protected area. The impact rankings enabled to identify taxa that generally cause high impacts and to prioritize species for the management in protected areas according to their impact magnitudes. By following a standardized impact protocol, we identified several alien species causing high impacts that do not appear on any expert-based risk list, which are relevant for policymakers. Thus, we recommend that alien species be systematically screened to identify knowledge gaps and prioritize their management with respect to spatio-temporal trends in impact magnitudes.
Keywords: alien species, biological invasions, EICAT, invasive species management, protected areas, species prioritization
Published in DiRROS: 29.10.2021; Views: 684; Downloads: 561
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