Developing a point process model for ecological risk assessment of pine wilt disease at multiple scales

Matsuhashi, Saeko; Hirata, Akiko; Akiba, Mitsuteru; Nakamura, Kenichiro; Oguro, Michio; Takano, Kohei Takenaka; Nakao, Katsuhiro; Hijioka, Yasuaki; Matsui, Tetsuya

doi:10.1016/j.foreco.2020.118010

Cited by 30 publications

(18 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The effective cumulative temperature of the species particularly ranges within 25-30 • C, and an increase in the PWN population promotes the growth of the population of trees experiencing PWD [21]. The research results of Matsuhashi and others have indicated the effect of temperature on the spread of PWD in Japan [22]. Morimoto proposed that the spread of PWD was achieved by the transmission of the pinewood nematode through several species of Monochamus alternatus [19].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Hao

Huang

Zhou

et al. 2021

Forests

View full text Add to dashboard Cite

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

show abstract

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Hao

Huang

Zhou

et al. 2021

Forests

View full text Add to dashboard Cite

show abstract

“…We analyzed the distribution of PWD-damaged forests in China using district-level occurrence data from 1982 to 2020. This differed from the method of previous studies, which used species occurrence points (latitude and longitude) for the current year or at limited locations (monitoring stations) over long time series [19,30]. Although PWD occurrence point data at high temporal resolution are unavailable at the national or regional scale, publicly released district-level occurrence data allowed us to determine the species occurrence points using the centroids of districts, which has been the most commonly used solution in similar research [32,40].…”

Section: Discussionmentioning

confidence: 99%

“…These MaxEnt models are generally built by integrating PWD occurrences (presence-only or presence-absence records) with different spatial environmental factors [28,29]. Several studies have investigated the meteorological factors that control the current PWD distribution, such as the average monthly mean temperatures in the warmest 3 months and the aridity in three geographic regions (Europe, North America, and East Asia) in 2017 [2]; the mean annual temperature, as the most important of the 19 bioclimatic variables at the national, regional, and local spatial scales in Japan [30]; and water deficit, which increases the susceptibility of pines to PWN [14]. However, there is no agreement among their conclusions.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Dynamics and Factors Driving the Distributions of Pine Wilt Disease-Damaged Forests in China

Wei

Peng

Liu

et al. 2022

Forests

View full text Add to dashboard Cite

Many forests have suffered serious economic losses and ecological consequences of pine wilt disease (PWD) outbreaks. Climate change and human activities could accelerate the distribution of PWD, causing the exponential expansion of damaged forest areas in China. However, few studies have analyzed the spatiotemporal dynamics and the factors driving the distribution of PWD-damaged forests using continuous records of long-term damage, focusing on short-term environmental factors that influence multiple PWD outbreaks. We used a maximum entropy (MaxEnt) model that incorporated annual meteorological and human activity factors, as well as temporal dependence (the PWD distribution in the previous year), to determine the contributions of environmental factors to the annual distribution of PWD-damaged forests in the period 1982–2020. Overall, the MaxEnt showed good performance in modeling the PWD-damaged forest distributions between 1982 and 2020. Our results indicate that (i) the temporal lag dependence term for the presence/absence of PWD was the best predictor of the distribution of PWD-damaged forests; and (ii) Bio14 (precipitation in the driest month) was the most important meteorological factor for affecting the PWD-damaged forests. These results are essential to understanding the factors governing the distribution of PWD-damaged forests, which is important for forest management and pest control worldwide.

show abstract

“…This indicates that areas where an increase in temperature is predicted along with both decrease and increase in precipitation may possibly be exposed to future disease outbreaks. Indeed, Fabre et al (2011), Bosso et al (2017), and Matsuhashi et al (2020) predicted future increases in disease outbreaks under these different scenarios ( Supplementary Table 1). Thus, despite the contrasting observations, increased disease outbreaks are likely in many areas as climate predictions are equally contrasting in different regions of the world (IPCC, 2018).…”

Section: Forest Disease Outbreakmentioning

confidence: 97%

“…This is particularly urgent in the context of global climate change, which may further complicate the interactions through increasing the frequency and severity of extreme weather events (IPCC, 2018). These events may increase the susceptibility of trees (Buotte et al, 2017), facilitate the spread, reproduction, and development of pathogens and pests (Matsuhashi et al, 2020), and weaken or destroy their natural enemies and competitors (Thurman et al, 2017). While climate change may also reduce damage by negatively affecting pests and pathogens (Zhan et al, 2018), more increased than decreased effects on tree growth and mortality have been observed (Creeden et al, 2014;Camarero et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

The Threat of the Combined Effect of Biotic and Abiotic Stress Factors in Forestry Under a Changing Climate

2020

View full text Add to dashboard Cite

Plants encounter several biotic and abiotic stresses, usually in combination. This results in major economic losses in agriculture and forestry every year. Climate change aggravates the adverse effects of combined stresses and increases such losses. Trees suffer even more from the recurrence of biotic and abiotic stress combinations owing to their long lifecycle. Despite the effort to study the damage from individual stress factors, less attention has been given to the effect of the complex interactions between multiple biotic and abiotic stresses. In this review, we assess the importance, impact, and mitigation strategies of climate change driven interactions between biotic and abiotic stresses in forestry. The ecological and economic importance of biotic and abiotic stresses under different combinations is highlighted by their contribution to the decline of the global forest area through their direct and indirect roles in forest loss and to the decline of biodiversity resulting from local extinction of endangered species of trees, emission of biogenic volatile organic compounds, and reduction in the productivity and quality of forest products and services. The abiotic stress factors such as high temperature and drought increase forest disease and insect pest outbreaks, decrease the growth of trees, and cause tree mortality. Reports of massive tree mortality events caused by “hotter droughts” are increasing all over the world, affecting several genera of trees including some of the most important genera in plantation forests, such as Pine, Poplar, and Eucalyptus. While the biotic stress factors such as insect pests, pathogens, and parasitic plants have been reported to be associated with many of these mortality events, a considerable number of the reports have not taken into account the contribution of such biotic factors. The available mitigation strategies also tend to undermine the interactive effect under combined stresses. Thus, this discussion centers on mitigation strategies based on research and innovation, which build on models previously used to curb individual stresses.

show abstract

Developing a point process model for ecological risk assessment of pine wilt disease at multiple scales

Cited by 30 publications

References 49 publications

Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Spatiotemporal Dynamics and Factors Driving the Distributions of Pine Wilt Disease-Damaged Forests in China

The Threat of the Combined Effect of Biotic and Abiotic Stress Factors in Forestry Under a Changing Climate

Contact Info

Product

Resources

About