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Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus Armandi in China

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Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus Armandi in China Article Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus armandi in China Hang Ning 1,2, Ming Tang 1,2 and Hui Chen 1,2,* 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China; [email protected] (H.N.); [email protected] (M.T.) 2 College of Forestry, Northwest A&F University, Yangling 712100, China * Correspondence: [email protected] Abstract: Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) is a bark beetle native to China and is the most destructive forest pest in the Pinus armandii woodlands of central China. Due to ongoing climate warming, D. armandi outbreaks have become more frequent and severe. Here, we used Maxent to model its current and future potential distribution in China. Minimum temperature of the coldest month and precipitation seasonality are the two major factors constraining the current distribution of D. armandi. Currently, the suitable area of D. armandi falls within the Qinling Mountains and Daba Mountains. The total suitable area is 15.83 × 104 km2. Under future climate scenarios, the total suitable area is projected to increase slightly, while remaining within the Qinling Mountains and Daba Mountains. Among the climate scenarios, the distribution expanded the most under the maximum greenhouse gas emission scenario (representative concentration pathway (RCP) 8.5). Under all assumptions, the highly suitable area is expected to increase over time; the increase will occur in southern Shaanxi, northwest Hubei, and northeast Sichuan Provinces. By the 2050s, the highly suitable area is projected to increase by 0.82 × 104 km2. By the 2050s, the Citation: Ning, H.; Tang, M.; Chen, suitable climatic niche for D. armandi will increase along the Qinling Mountains and Daba Mountains, H. Impact of Climate Change on posing a major challenge for forest managers. Our findings provide information that can be used to Potential Distribution of Chinese monitor D. armandi populations, host health, and the impact of climate change, shedding light on the White Pine Beetle Dendroctonus effectiveness of management responses. armandi in China. Forests 2021, 12, 544. https://doi.org/10.3390/f12050544 Keywords: Dendroctonus armandi; climate change; species distribution models; potential distribution; pest management Academic Editor: Manuela Branco Received: 15 March 2021 Accepted: 26 April 2021 1. Introduction Published: 27 April 2021 The Chinese white pine beetle, Dendroctonus armandi Tsai and Li (Coleoptera: Cur- Pinus armandii Publisher’s Note: MDPI stays neutral culionidae: Scolytidae), a bark beetle native to China, is distributed in the with regard to jurisdictional claims in Franch. woodlands of central China [1]. As a pioneer species, this bark beetle invades published maps and institutional affil- healthy P. armandii individuals older than 30 years. Subsequently, secondary bark bee- iations. tles attack the infected or withered hosts, resulting in landscape-level tree mortality [2]. Dendroctonus armandi inhabits and feeds on the phloem of the host [3]. When mature adults search for new host trees, they briefly leave the gallery. It is always the females that break through the first line of defense, by boring through the host’s bark. The females then release aggregation pheromones to attract males for mating and colonization. The Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. females subsequently lay eggs in the phloem, and the larvae excavate feeding tunnels in This article is an open access article this tissue [4]. In the Qinling Mountains, the number of beetle generations varies with distributed under the terms and elevation, with ca. 2 per year below 1700 m, 1.5 per year at 1700–2150 m, and 1 per year conditions of the Creative Commons above 2150 m [5]. Outbreaks of this beetle have occurred every year in recent decades, Attribution (CC BY) license (https:// altering the ecosystem and causing economic losses. creativecommons.org/licenses/by/ Because insects are poikilotherms and have short generation times, their life history is 4.0/). closely related to temperature [6]. They are therefore particularly sensitive to the warming Forests 2021, 12, 544. https://doi.org/10.3390/f12050544 https://www.mdpi.com/journal/forests Forests 2021, 12, 544 2 of 14 associated with climate change, and may be early indicators of local climate change [7]. In recent years, field observations have revealed that the D. armandi outbreak frequency and intensity have increased with the rise in temperature [8,9]. New occurrence records continue to be published [10]. The projected climate changes are likely to alter the char- acteristics of D. armandi eruptions, and cause alterations in species distributions. It is therefore critical to understand how the geographical distribution of D. armandi in China may respond to climate change, to enable appropriate ongoing forest ecosystem manage- ment. To address this, we applied species distribution models (SDMs) to predict climate change-driven habitat shifts for this species. SDMs have become a major focus of large-scale ecology and biogeography stud- ies. They are widely applied to model plant and insect habitat ranges, assess the ef- fects of global environmental change on species and ecosystems, evaluate the risk of species invasion and spread, and manage and plan habitats for species, communities, and ecosystems [11,12]. Popular SDMs, including BIOCLIM, GARP, BIOMAPPER, DOMAIN, GAM, GLM, CLIMEX, and Maxent, use species occurrence records (presence only, or presence/absence) associated with environmental variables to describe the fundamental niche of a particular species [13–20]. They then project this niche onto the landscape of interest to reflect the potential distribution of the species [21]. Maxent is commonly used because of its excellent predictive performance. Maxent modeling predictions are typically stable and reliable even when species distribution data are incomplete or sample sizes are small [22–24]. Effective representation of the geographical distribution of the D. armandi population can provide a reference point for forest managers in the face of climate change. In this study, we used Maxent to model the current distribution of D. armandi in China, and predict its future habitat alterations. This research has three objectives: (1) to identify the dominant environmental variables that describe the distribution range of D. armandi; (2) to map current potential distribution of D. armandi; and (3) to predict future potential distribution of D. armandi under climate change scenarios. 2. Materials and Methods 2.1. Occurrence Data Dendroctonus armandi presence data was collected in the field, from May to October 2016–2019. The fieldwork was conducted with the assistance of the Department of Forestry Protection. The distance between the sampling sites was >20 km. When the distance between two or more occurrence points was <20 km, we recorded only one occurrence. First, we judged beetle presence by observing resin-flow from the bark, because P. armandii responds to attack by D. armandi by releasing large amounts of distinctly fluid resin. Further, we used pheromone-baited traps to detect beetle presence in areas with population outbreaks. The traps consisted of six identical black plastic funnels aligned vertically over a cup (model YBQ-LD-004, Geruibiyuan Technology Co., Ltd., Beijing, China), similar to those commonly used to collect bark beetles. As an attractant we used <bait: mixture of terpenes and pheromones> (Sino-Czech Trading Company, Beijing, China) packed in a 15 mL slow-release polyethylene vial with a release rate of 200 mg/day. Each trap was vertically suspended from a manila rope tied between two host trees at the forest edge and positioned more than 1 m from the closest host tree. The lower end of the trap was 1.5 m above ground. The traps were spaced at least 30 m apart. Liquid paraffin was used as a killing agent in the cups. Trapped D. armandi were collected weekly, counted, and then stored in 70% ethanol. Location name, longitude, latitude, and altitude were documented for all occurrence points. In addition, occurrence records were collected from the literature [1–5,8–10]; points without accurate location data were excluded. In total, we obtained 132 point-based occurrence records from the literature and fieldwork (Figure1). Forests 2021, 12, x FOR PEER REVIEW 3 of 14 Forests 2021, 12, 544 5,8–10]; points without accurate location data were excluded. In total, we obtained3 of 132 14 point-based occurrence records from the literature and fieldwork (Figure 1). FigureFigure 1.1.Occurrence Occurrence recordsrecords ofof DendroctonusDendroctonus armandiarmandi andand currentcurrent distributiondistribution ofof PinusPinus armandii in China.China. ForFor thethe hosthost distributiondistribution variable,variable, wewe gatheredgathered presencepresence datadata forfor thethe hosthostP. P. armandii armandii usingusing three three methods. methods First,. First, we we registered registeredP. armandiiP. armandiiin the in fieldthe field from from 2016 2016 to 2018. to 2018. Raw dataRaw weredata processedwere processed as for theas forD. armandithe D. armandidata. Second, data. weSecond obtained, we obtainedP. armandii P.occurrence armandii occur- data fromrence the data Global from Biodiversitythe Global Biodiversity Information Information Facility (GBIF, Facility http://www.gbif.org (GBIF, http://www.gbif.org
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