Next Article in Journal
Long-Term Nitrogen Addition Could Modify Degradation of Soil Organic Matter through Changes in Soil Enzymatic Activity in a Natural Secondary Forest
Previous Article in Journal
Practical LAI Estimation with DHP Images in Complex Forest Structure with Rugged Terrain
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 14
Issue 10
10.3390/f14102048
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Future Range Shifts Suggest That the Six-Spined Spruce Bark Beetle Might Pose a Greater Threat to Norway Spruce in Europe than the Eight-Spined Spruce Bark Beetle

by
Runyao Cao
1,2 and
Jianmeng Feng
1,2,*
1
College of Agriculture and Biological Science, Dali University, Dali 671003, China
2
Research Center for Agroecology in Erhai Lake Watershed, Dali University, Dali 671003, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(10), 2048; https://doi.org/10.3390/f14102048
Submission received: 12 September 2023 / Revised: 8 October 2023 / Accepted: 11 October 2023 / Published: 12 October 2023
(This article belongs to the Section Forest Health)
Browse Figures
Versions Notes

Abstract

:
Both the eight-spined spruce bark beetle (eight-spined beetle, Ips typographus) and the six-spined spruce bark beetle (six-spined beetle, Pityogenes chalcographus) have major deleterious effects on Norway spruce (i.e., Picea abies, the host tree) in Europe. However, future potential range shifts of the two pests and their range overlap with Norway spruce have not yet been characterized. Through range dynamic models, we characterized their future range expansions, as well as their range overlap with their host tree under current–future change scenarios in 2100. Host availability was the greatest contributor to the range shifts of the two pests, and climatic changes were the main drivers of the range expansion of the host. The potential range, expanded range, and overlapped range were larger for the six-spined beetle than for the eight-spined beetle. The host tree, i.e., Norway spruce, might face increasing threats from the two pests in the future. Future climate change will likely indirectly facilitate range shifts of pests by promoting increases in the area capable of sustaining the host tree. The six-spined beetle might pose a greater threat to Norway spruce than the eight-spined beetle, albeit the latter has previously been considered to have more deleterious effects on Norway spruce.

1. Introduction

Predicting future potential ranges of pests is essential for pest control because such information can aid the identification of priority regions for pest control. Studies of the potential ranges of pests have thus received much attention in previous decades [1,2,3,4,5]. For example, Hof and Svahlin (2016) detected the range expansions of pests under future change scenarios in the Swedish boreal forest and identified priority regions for pest control in the peripheral regions of Norrland [6]. However, the range of desert locusts (Schistocerca gregaria) was predicted to contract under future change scenarios, and central Algeria, western Mali, eastern Mauritania, northern Chad, northern Niger, and northern Sudan might be priority regions for controlling this pest in the future [7]. Therefore, the effects of future change scenarios on the range shifts of pests remain unclear, and additional studies are needed.
Climate is thought to determine species distributions and potential ranges through eco-physiological constraints [8,9,10,11], and these might be applicable to pests. In recent decades, many studies have used climatic factors to project the potential ranges of pests through species distribution models (SDMs) [5,6,12]. For example, Gong et al. (2020) detected double-edged effects of future climate change on the range shifts of pests [13]. Recently, Nie et al. (2023) found that future climate change will facilitate the range expansion of gray squirrels (Sciurus carolinensis), a pest in European forest ecosystems [5].
In addition to the climatic factors, land use can also affect the potential ranges of pests, probably because land-use changes can have a strong effect on habitat availability. For example, the ranges of ticks were predicted to contract in central and southern China, probably because a decrease in the extent of forest reduces habitat availability [14]. Although both climate and land-use changes have major effects on the potential ranges of pests, their relative contributions to range shifts remain unclear [12,13,15,16]. One of the probable solutions for this debate is a hypothesis that the relative importance of land use and climate might vary with spatial scale, with climate having stronger effects at large scales and land use having stronger effects at small scales [17]. However, the generality of this hypothesis requires further confirmation. For example, Liu et al. (2020) found that land use had stronger effects on the global potential ranges of fall armyworms, a globally invasive pest, than climatic factors [12]. Thus, although both land use and climate can affect the potential ranges of pests, their relative contributions require further study.
Host availability can also have a major effect on the potential ranges of pests because host availability determines the food resources of pests; that is, the potential ranges of pests are often limited by the availability and distribution of hosts [18,19]. For example, Halsch et al. (2019) showed that shifts in host plants might induce a range expansion in the gulf fritillary butterfly [20]. However, Silva et al. (2015) observed that the geographic range of the neotropical orchid bees was not constrained by the presence of the host species [21]. Additionally, Hanspach et al. (2014) argued that host plant availability was not linked to the distributional patterns of pests in low-stress environments but was limited by climate [22]. Therefore, the relative contributions of host availability and climate to shaping the potential ranges of pests require further study.
Many studies have examined shifts in the ranges of pests, and this work has provided valuable information for developing pest control strategies. We hypothesize that studies of range overlap between pests and their hosts under future change scenarios might significantly aid the development of pest control strategies. However, although the range shifts of pests have received much attention in recent decades, few studies on the range overlap between pests and their hosts under future scenarios have been conducted.
Both the eight-spined spruce bark beetle (eight-spined beetle, Ips typographus) and the six-spined spruce bark beetle (six-spined beetle, Pityogenes chalcographus) are considered major pests of Norway spruce (Picea abies), one of the most widely distributed trees in European forest ecosystems [23,24,25,26,27,28]. The eight-spined beetle can colonize downed trees; however, it can also attack and kill healthy and mature Norway spruce [29]. Numerous large-scale outbreaks have occurred in recent centuries, which might be induced by precipitation deficits, warm summers, and storm disturbances [30,31,32], and these have resulted in the death of millions of trees [31,33,34]. The six-spined beetle can also have deleterious effects on Norway spruce, even on young trees [29]. However, the effects of this species on Norway spruce are thought to be milder than those of the eight-spined beetle [25,35]. Several studies have examined the effects of the two pests on Norway spruce, probably because of the substantial damage that it can induce to this tree [27,34,35,36,37,38], and these studies have greatly enhanced our knowledge of the consequences of their attacks on Norway spruce. For example, Göthlin et al. (2000) observed that the percentage of windthrown trees with six-spined beetles decreased with the diameter of the tree stem, and the opposite was the case for eight-spined beetles [35]. Here, we assumed that the eight-spined beetle and six-spined beetle may have different potential ranges in Europe, and the distribution patterns of Norway spruce, one of the major hosts of these two pests in Europe [25], could affect their potential ranges. However, few studies on the potential ranges of the two pests and their range overlap with Norway spruce in Europe have been conducted, and the effect of the host (i.e., Norway spruce) availability on the potential ranges of the two pests has also not been widely explored.
Here, we compiled occurrence records of the six-spined beetle, the eight-spined beetle, and Norway spruce, the host of the two pests in Europe, and used range dynamic models to investigate their potential range shifts, as well as the range overlap between the two pests and Norway spruce under future change scenarios. We hypothesized that climate, land use, and host availability affected the potential ranges of the pests and their range overlap with Norway spruce in Europe. Additionally, the threat posed by the six-spined beetle and the eight-spined beetle on Norway spruce might vary, and this might be inferred from differences in their potential ranges and their range overlap with Norway spruce. The results of our study could enhance our understanding of the future risks posed by six-spined beetle and eight-spined beetle to Norway spruce and will aid the development of strategies to minimize their destructive effects on Norway spruce in Europe under future change scenarios.

2. Materials and Methods

2.1. Occurrence Records

Our primary source of occurrence records was the Global Biodiversity Information Facility (GBIF), which contains ca. 2.2 billion species records derived from ca. 2100 publishing institutions, 89,000 datasets, and ca. 9100 peer-reviewed publications. Thus, the GBIF is the most comprehensive and robust data source of species occurrence records globally. We also used the scientific names of the two pests and their host to search for occurrences in scientific publications, including those indexed in Web of Science and Google Scholar. From these publications, we retrieved their occurrence records with clear geographical coordinates and removed duplicated records. We first built an occurrence record dataset that included 16,165, 14,255, and 615,899 records of the six-spined beetle, the eight-spined beetle, and Norway spruce in Europe, respectively. Following Yang et al. (2023), we then removed the occurrences for which the uncertainty in geographical coordinates was greater than 5 km [39]. To reduce the effects of sampling bias on our models, we spatially thinned records at a radius of 5 km [40,41]. Finally, we retrieved a total of 15,574 occurrences, including 1389, 1657, and 12,528 records for the six-spined beetle, eight-spined beetle, and Norway spruce, respectively (Figure 1).

2.2. Predictors in the SDMs

A total of 31 predictors were used in the SDMs to predict the potential ranges of the two pest beetles (Table S1), including climatic predictors (19), land-use predictors (9), topographical predictors (3), and host availability (1). A total of 30 predictors were used in the SDMs to predict the potential ranges of Norway spruce (Table S1), including climatic predictors (19), land-use predictors (8), and topographical predictors (3). Host availability was represented by the habitat suitability or occurrence probability of Norway spruce and calibrated through the SDMs. Our climatic predictors comprised 8 precipitation-related predictors and 11 temperature-related predictors at the monthly, quarterly, and annual scales (Table S1) [42]. Data for all these climatic variables were downloaded from the Worldclim 2.1 database [42]. The climatic predictors under current conditions were retrieved from the near–current gridded climatic datasets in Worldclim [42]. The climatic predictors under future change scenarios were also retrieved from Worldclim [42], including those under the two Shared Socio-economic Pathways (SSP), SSP126 and SSP585, in 2100, which represented the most optimistic and pessimistic future climate change scenarios, respectively. Additionally, all future climatic predictors were derived from one of the most robust global climate models: MPI-ESM1-2-HR [43].
Land-use predictors were at a spatial resolution of 0.25° × 0.25° (Table S1). These data were obtained from the land-use Harmonization dataset. Topographical factors, such as aspect, slope, and elevation (Table S1), can result in spatial variation in water and energy, which might be closely associated with the formation of diverse micro and macro habitats for organisms [44,45,46] and create species dispersal barriers [47]. Therefore, we included topographical predictors in our study, including elevation, slope, and aspect, which were extracted from a digital elevation model in Worldclim 2.0 [48]. Notably, we used two sets of predictors for future scenarios in 2100 (i.e., those under SSP126 and SSP585). All our predictors were at a 2.5 arc-min spatial resolution or were resampled at this spatial resolution.

2.3. Projecting the Potential Ranges of Pests and Host

2.3.1. Selection of Predictors

In light of the collinearity among predictors, we built preliminary SDMs for Norway spruce to calibrate the importance values (IVs) of each predictor (Table S1). Next, we conducted Pearson correlation analyses to identify pairs of predictors showing strong collinearity using the following threshold: correlation coefficient >0.7 [49] (Table S2). When strong collinearity was detected in any pair of predictors, we only retained predictors with higher IVs. The retained predictors were then input into the final SDMs for the potential ranges of Norway spruce. The same method was used to select predictors for the potential ranges of the eight-spined beetle and the six-spined beetle.

2.3.2. Projecting the Potential Ranges of Pests and Their Host

We used Biomod2, an ensemble SDM platform [50], to calibrate the potential ranges of Norway spruce; seven algorithms were used, including classification tree analysis, artificial neural network, random forest classifier, flexible discriminant analysis, maximum entropy model, generalized boosting model, and generalized additive model [50]. As required by presence-only SDMs, we randomly generated 1000 pseudo-absences when the number of occurrence records of the Norway spruce was fewer than 1000; otherwise, the number of randomly generated pseudo-absences was equal to that of Norway spruce occurrences [51]. The SDMs initially outputted the habitat suitability maps for Norway spruce, which were then used to project the potential ranges of the two pests. Then, we used the sensitivity–specificity sum maximization approach (MSS threshold) [52] to determine the potential ranges of Norway spruce. Similar methods were used to project the potential ranges of the six-spined beetle and the eight-spined beetle.

2.3.3. Assessment of Model Performance

We used five-times cross-validation to evaluate the performance of the SDMs; 70% of the occurrences were used to build SDMs, and the remaining 30% were used to evaluate SDM performance [53]. We only retained SDMs with true skill statistics (TSS) >0.6 or area under the ROC curve (AUC) >0.8, as suggested by Nie et al. (2023) [5].

2.4. Range Shifts between Current Conditions and Future Change Scenarios

Following Yang et al. (2023) [39], we built dynamic models to examine range shifts in Norway spruce between current conditions and future change scenarios. We used the following three metrics to characterize range shifts: stabilized range, expanded range, and unfilled range. The stabilized range (RS) was the range jointly occupied by Norway spruces under future scenarios and current conditions; the expanded range (RE) was the potential range exploited only by Norway spruce under future change scenarios; and the unfilled range (RU) was the range only occupied by Norway spruce under current conditions. The range of Norway spruce under current conditions was the sum of the stabilized range and unfilled range, and the range of Norway spruce under future change scenarios was the sum of the stabilized range and expanded range. The range ratio index (RRI) was used to compare the potential ranges of Norway spruce between current conditions (RC) and future change scenarios (RF) and could be expressed as follows:
R R I = R F R C
when RRI > 1, the ranges of Norway spruce under future change scenarios (RF) were larger relative to those under current conditions.
Moreover, the range similarity index (RSI) was used to determine shifts in the range positions of Norway spruce under current–future change scenarios and could be expressed as follows:
R S I = 2 R S R F + R C
where RS is the potential ranges jointly occupied by Norway spruce under future scenarios and current conditions. When RSI < 0.5, Norway spruce, under current conditions and future change scenarios, had different range positions and vice versa.
These methods were also used to detect range shifts of six-spined beetle and eight-spined beetle between current conditions and future change scenarios.

2.5. Range Overlap between the Two Pests and Norway Spruce

We characterized the range overlap between eight-spined beetle and Norway spruce using the following three indices: pest range (PR), overlapped range (OR), and host range (HR) under current–future change scenarios. Specifically, the pest range was the range exploited by the eight-spined beetle and not by the host; the overlapped range was the range shared by the eight-spined beetle and the host; and the host range was the range occupied by the host and not by the eight-spined beetle. Therefore, the total range of the eight-spined beetle (TPR) was the sum of PR and OR, whereas the total range of Norway spruce (THR) was the sum of HR and OR. We also used the range overlap index (ROI) to indicate the range overlap between eight-spined beetle and Norway spruce:
R O I = 2 O R T P R + T H R
This method was also used to determine the range overlap between the six-spined beetle and Norway spruce.

3. Results

3.1. Assessment of the SDMs

All of the SDMs showed high performance, and the AUC and TSS scores were high. Specifically, AUC and TSS in the SDMs for the potential ranges of Norway spruce were 0.956 and 0.792, respectively. AUC and TSS in the SDMs for the potential ranges of the eight-spined beetle (the six-spined beetle) were 0.960 (0.962) and 0.989 (0.791), respectively. Therefore, the range projections for the three species were robust.

3.2. Importance of the Predictors

The top three predictors in the SDMs for the potential ranges of Norway spruce were temperature seasonality (0.548), mean annual temperature (0.241), and maximum temperature in the warmest month (0.148) (Table 1). The top three predictors in the SDMs for the potential ranges of the eight-spined beetle were host availability, followed by mean temperature in the warmest season and temperature seasonality, which had IVs of 0.819, 0.075, and 0.068, respectively (Table 1). The predictors with the highest IVs in the SDMs for the potential ranges of the six-spined beetle were host availability (0.733), mean temperature in the coldest season (0.086), and the fraction of cropland (0.051) (Table 1). Additionally, we found that the importance values of each predictor under future scenarios were highly close to those under current conditions (Table S3).

3.3. Potential Ranges of Norway Spruces and the Two Pests

The MSS thresholds for determining the potential ranges of Norway spruce under current conditions, as well as the SSP126 and SSP585 scenarios, were 0.44, 0.51, and 0.32, respectively. The thresholds for determining the potential ranges of the eight-spined beetle (the six-spined beetle) under current conditions, as well as the SSP126 and SSP585 scenarios, were 0.53 (0.50), 0.46 (0.35) and 0.33 (0.21), respectively.
The current potential ranges of Norway spruce were mainly projected in Norway, Sweden, Finland, Estonia, France, Germany, Austria, the United Kingdom, Estonia, Latvia, Lithuania, Switzerland, and Slovakia and covered ca. 3.13 million km2 (Figure 2a and Figure S1). The potential ranges of Norway spruce under the SSP126 scenario covered 2.87 million km2 and were mainly detected in Norway, Sweden, Finland, Estonia, France, the entire of Germany, Austria, Estonia, Latvia, Lithuania, Switzerland, Slovakia, the entire United Kingdom, and almost entire Ireland and West Russia (Figure 2b and Figure S1). The potential ranges of Norway spruce under the SSP585 scenario covered 3.28 million km2 and were mainly projected in Ireland, entire Ireland, the entire United Kingdom, entire Norway, entire Sweden, Finland, Estonia, France, entire Germany, Austria, Estonia, Latvia, Lithuania, Switzerland, Slovakia and West Russia (Figure 2c and Figure S1).
The potential ranges of the eight-spined beetle under current conditions were mainly projected in Norway, Sweden, Estonia, and west Europe (including France, Germany, Switzerland, and Austria) and covered ca. 1.22 million km2 (Figure 2d and Figure S1). The potential ranges of the eight-spined beetle under the SSP126 scenario covered 1.48 million km2, and they were mainly projected in Norway, Sweden, Estonia, Finland, the United Kingdom, France, Germany, Denmark, Switzerland, Austria, and Italy (Figure 2e and Figure S1). The potential ranges of the eight-spined beetle under the SSP585 scenario covered 2.12 million km2 and were mainly detected in the western part of the United Kingdom, France, Germany, the Netherlands, Denmark, Switzerland, Austria, Croatia, Slovenia, Latvia, Lithuania, Italy, Norway, Sweden, Estonia and Finland (Figure 2f and Figure S1). In sum, under future scenarios, the potential ranges of eight-spined beetle included higher latitudinal regions compared with those under current conditions.
The potential ranges of the six-spined beetle under current conditions were mainly projected in Norway, Sweden, Finland, Estonia, France, Germany, Austria, Switzerland, the United Kingdom, and Slovakia and covered ca. 1.69 million km2 (Figure 2g and Figure S1). The potential ranges of the six-spined beetle under the SSP126 scenario covered 2.42 million km2, and their main body included those under the current condition and the higher latitudinal regions in Norway, Sweden and Finland relative to those under current conditions (Figure 2h and Figure S1). The potential ranges of the six-spined beetle under the SSP585 scenario covered 2.52 million km2, and their main body included those under the SSP126 scenario and the higher latitudinal regions in Norway, Sweden and Finland relative to those under the SSP126 scenario (Figure 2i and Figure S1).

3.4. Shifts in Potential Ranges

The stabilized range of Norway spruce under current-SSP126 and current-SSP585 showed similar spatial patterns; these were mainly detected in Norway, Sweden, Finland, Estonia, France, Germany, Ireland, and the United Kingdom and covered 2.65 million km2 and 2.67 million km2, respectively (Figure 3a,b). The expanded ranges of Norway spruce under current-SSP126 were primarily detected in Ireland, Poland, Norway, Sweden, and west Russia and covered 0.22 million km2; the unfilled ranges were mainly projected in scattered areas in west Russia, France, Spain, Poland, Czech, Latvia, Lithuania, and Estonia and covered 0.48 million km2 (Figure 3a). The expanded ranges of Norway spruce under the current-SSP585 scenario were primarily detected in Iceland, Ireland, Norway, Sweden, Finland, west Russia, and north Russia, covering 0.61 million km2; the spatial patterns of the unfilled ranges were similar to those under the current-SSP126 scenario and covered 0.46 million km2 (Figure 3b). The RRI (RSI) of Norway spruce under the current-SSP126 and current-SSP585 scenarios was 0.91 (0.88) and 1.04 (0.83), respectively.
The range shifts of the eight-spined beetle under the current-SSP126 scenario revealed that the expanded ranges were mainly projected in Finland, Norway, Sweden, Demark, France, Germany, Italy, and Finland, covering 0.29 million km2; the stabilized ranges were mainly detected in Norway, Sweden, Estonia, France, and Germany and covered 1.18 million km2; and the unfilled ranges were distributed in Finland and Sweden, covering 0.03 million km2 (Figure 3c). Under the current-SSP585 scenario, the expanded ranges were mainly detected in Finland, Norway, Sweden, Ireland, Germany, Lithuania, and the United Kingdom, covering 0.91 million km2 (Figure 3d); the spatial patterns of the stabilized ranges were similar to those under the current-SSP126 scenario, with each covering ca.1.21 and 0.0 million km2, respectively (Figure 3d). RRI (RSI) of the eight-spined beetle under the current-SSP126 and current-SSP585 scenarios was 1.21 (0.88) and 1.74 (0.73), respectively.
The stabilized range of the six-spined beetle under current-SSP126 and current-SSP585 scenarios were similar, and they were mainly detected in Norway, Sweden, Finland, Estonia, France, Germany, and Austria and covered 1.62 million km2 and 1.48 million km2, respectively (Figure 3e,f). Under the current-SSP126 scenario, the expanded ranges were mainly projected in Finland, Sweden, Norway, the United Kingdom, Ireland, Denmark, Poland, and Croatia, covering 0.79 million km2; the unfilled ranges were primarily detected in Sweden, Norway, and Estonia, covering 0.0.06 million km2 (Figure 3e). Under the current-SSP585 scenario, the expanded ranges were mainly projected in Finland, Sweden, Norway, the United Kingdom, Ireland, Iceland, Italy, France, Germany, and Croatia, covering 1.03 million km2; the unfilled ranges were primarily detected in Finland, Estonia, and France, covering ca. 0.20 million km2 (Figure 3f). The RRI (RSI) of the six-spined beetle under the current-SSP126 and current-SSP585 scenarios was 1.43 (0.79) and 1.49 (0.70), respectively.

3.5. Range Overlap between the Two Pests and Norway Spruce

Under current conditions, the range overlap between the eight-spined beetle and Norway spruce was mainly detected in France, Germany, Norway, Sweden, Finland, Estonia, and Austria, covering 1.19 million km2; the range overlap index was 0.552 (Figure 4a and Figure S2). The spatial patterns of range overlap between eight-spined beetle and Norway spruce under the SSP126 scenario were similar to those under current conditions, with the exception that potential ranges were much larger at higher latitudinal regions; the range overlap covered 1.33 million km2, and the range overlap index was 0.613 (Figure 4b and Figure S2). Under the SSP585 scenario, the range overlap between the eight-spined beetle and Norway spruce covered 1.78 million km2, and the range overlap index was 0.659. the range overlap was mainly detected in the United Kingdom, France, Germany, Norway, Sweden, Finland, Estonia, Georgia, Switzerland, Poland, and Austria (Figure 4c and Figure S2). In sum, the overlapped ranges under future scenarios shifted to higher latitudinal regions, especially in Norway, Finland, and Sweden, relative to those under current conditions.
Under current conditions, the range overlap between the six-spined beetle and Norway spruce was mainly detected in France, Germany, Switzerland, Andorra, Spain, Norway, Sweden, Finland, Italy, the United Kingdom, Estonia, Slovakia, and Austria, covering 1.67 million km2 (Figure 4d and Figure S2), and the range overlap index was 0.693. The spatial patterns of range overlap between the six-spined beetle and Norway spruce under the SSP126 scenario were similar to those under current conditions, with the exception of the larger distribution in the higher latitudinal regions of Finland, Sweden, and Norway under the SSP126 scenario, covering 2.25 million km2 (Figure 4e and Figure S2), and the range overlap index was 0.852. Under the SSP585 scenario, the range overlap between the six-spined beetle and Norway spruce was primarily projected in Ireland, the United Kingdom, France, Germany, Sweden, Norway, Finland, Iceland, Italy, Spain, and Slovakia, covering 2.21 million km2 (Figure 4f and Figure S2), and the range overlap index was 0.764. In sum, the overlapped ranges between the six-spined beetle and Norway spruce shifted to higher latitudinal regions, especially Norway, Finland, and Sweden, under future scenarios relative to those under current conditions.

4. Discussion

Here, we elucidated the range expansions of the two pests and the increases in the range overlap between the two pests and their host tree under future change scenarios, suggesting that these two pests could pose greater threats to Norway spruce in the future. Based on projected range shifts and range overlap with the host tree, the six-spined beetle might pose greater threats to Norway spruce than the eight-spined beetle, albeit the latter has previously been considered to have more deleterious effects on Norway spruce. Therefore, the results of our study provide novel insights that will aid the development of strategies to mitigate the damage to Norway spruce caused by these two pests in Europe in the future.
Our study showed that host availability had far higher importance values than other factors, i.e., 0.819 vs. 0.075 (IV of the second highest factors) and 0.733 vs. 0.086 (IV of the second highest factors), characterized in the SDMs for the potential ranges of the eight-spined and six-spined beetles, respectively. Therefore, host availability did not only have the strongest effect on the range shifts of the two pests but also, to a large extent, determined the potential ranges of the two pests, as well as largely determined the reliability of SDMs for projecting the potential ranges of the two pests. This might stem from the fact that Norway spruce provides a key food source for the two pests [25], or their survival might be substantially compromised without access to Norway spruce. In other words, changes in the range of these pests might coincide with the changes in the range of Norway spruce; these two pests might thus have long-term effects on Norway spruce. Faccoli and Berna rdinelli (2014) observed that mixed Norway spruce forests had higher resistance against the two pests compared with pure Norway spruce forests [54]. Therefore, the transformation of pure Norway spruce forests to mixed Norway spruce forests might be necessary for combating the future effects of the two pests on Norway spruce forests in Europe.
Numerous studies have shown that host availability might play a more important role in shaping the potential ranges of pests than climatic factors, especially for oligophagous species [20,55,56]. For example, Dang et al. (2021) suggested that stronger roles of host availability might be associated with the oligophagy of pests, implying that food constraints might play a particularly important role in shaping the potential ranges of the pests [57] and stronger effects of climatic factors on the potential ranges of the pests might be caused by the polyphagy or pseudo-oligophagy of pests [21,22]. Therefore, a reliable and clear definition of the feeding character (polyphagy or oligophagy) for the target species might be needed to reach a consensus on the relative roles of the host availability and climate in shaping the potential ranges of pests. In our study, the stronger roles of host availability on the potential ranges of pests might stem from the oligophagy of the two pests or their host preferences (i.e., Norway spruce) [25], and the potential ranges of the host determine the food availability of the two pests, which affects their potential ranges. However, the potential ranges of the host or Norway spruce were mainly determined by climatic factors. This suggests that the roles of climate in shaping the potential ranges of pests should not be neglected; climate likely affects the potential ranges of pests indirectly through its effects on the range of the host.
The relative contributions of climate and land use to shaping the potential ranges of species have been the subject of much discussion [12,15,16]. The results of our study indicated that climatic factors have stronger effects on the ranges of the two pests and their host tree than land-use factors. The effects of land use might have been masked by those of climatic factors. The relative effects of climatic and land-use factors depend on the spatial scale, with stronger effects of climatic factors at large scales and stronger effects of land-use factors at small scales [17]; these findings were supported by the results of Liu et al. (2019) [16] and Ding et al. (2019) [58]. Although this hypothesis has been rejected by some studies [12,59], our finding that the effects of climate factors are stronger than those of land-use factors at the continental scale seemed to provide support for this hypothesis.
Liu et al. (2020) argued that the stronger roles of land-use factors compared with climate factors in shaping the potential ranges of the fall armyworm, a global pest, might be explained by the hypothesis that herbivorous pests are more likely to occur in regions with high host availability, especially for oligophagous pests [12,60]. Therefore, the potential ranges of the fall armyworm were mainly determined by C4 annual cropland and managed pasture land, not by climatic factors. This idea was also supported by the results of Della Rocca and Milanesi (2022) [61]. In our study, although host availability had the strongest effect on the potential ranges, we found that the effects of land-use factors were weaker than the effects of climate factors on the potential ranges of the two pests. This inconsistency among studies might stem from the fact that the land-use factors in our study are not correlated with the distribution of the specific host for the two pests because land-use factors had not been subdivided in a way that would permit the host for the two pests to be accounted for. To a great extent, Norway spruce represents a type of subdivided land use. Therefore, following the argument of Liu et al. (2020) [12], land-use factors might have greater effects on the potential ranges of the two pests than climate factors. In sum, land-use changes might have greater effects than climate change on the potential ranges of herbivorous pests, especially oligophagous ones, albeit further research is needed to reach a consensus on this topic.
Our study showed that the potential ranges of the pests were considerably larger under most future change scenarios compared with those under current conditions, suggesting that the ranges of the pests will expand under future change scenarios. We also detected the considerable expansion of range overlap between the pests and Norway spruce under current-future scenarios. These observations, coupled with the projected range shifts of the pests and range overlap between the pests and host tree, suggested that the threat of the two pests to Norway spruce might be greater under future change scenarios than under current conditions.
Our study showed that from current conditions to the SSP126 and SSP585 scenarios, the potential ranges and range expansion of the six-spined beetle increased from 1.69 to 2.42 and 2.52 million km2, from zero to 0.79 and 1.03 million km2, respectively, whereas those of the eight-spined beetle increased from 1.22 to 1.48 and 2.12 million km2, from zero to 0.29 and 0.91 million km2, respectively. Our study also indicated that from current conditions to the SSP126 and SSP585 scenarios, the overlapped ranges of the six-spined beetle with the host tree increased from 1.67 to 2.25 and 2.21 km2, respectively, whereas those for the eight-spined beetle increased from 1.19 to 1.33 and 1.78 million km2, respectively. Therefore, the six-spined beetle was projected to have larger potential ranges and a larger increase in the potential ranges under current–future change scenarios, as well as larger expanded ranges and higher RRI under current–future scenarios than the eight-spined beetle. Therefore, it might suggest that its future invasion potential will be higher than that of the eight-spined beetle. Additionally, we observed larger overlapped ranges between the six-spined beetle and Norway spruce than between the eight-spined beetle and Norway spruce and a larger increase of the overlapped ranges under current–future change scenarios, suggesting that the six-spined beetle might pose greater threats to Norway spruce than the eight-spined beetle. Although the eight-spined beetle has previously been considered to have more deleterious effects on Norway spruce [25,35], analysis of future range shifts and range overlap with Norway spruce indicated that the six-spined beetle merit increased attention because, in the future, the potential ranges of this pest and its range overlap with Norway spruce larger than those of the eight-spined beetle.
Our study revealed the current range overlap between the two pests and Norway spruce in France, Germany, Switzerland, Norway, Sweden, Finland, Estonia, Austria, and Switzerland. Therefore, they might be priority regions for the development of strategies to mitigate the effects of these two pests on Norway spruce under current conditions. The range overlap between the two pests and Norway spruce under future change scenarios was mostly projected in Iceland and the higher latitudinal regions of Norway, Sweden, and Finland. These might be priority regions for the development of strategies to mitigate the effects of these two pests on Norway spruce in the future.
Finally, we have to acknowledge that the spatial uncertainty of the input data might result in the uncertainty of our model projection. First, although we have polished the occurrence records with a 5 km threshold of geographical coordinate uncertainty, we could not fully remove their spatial uncertainty. Second, the native spatial resolution of land-use predictors was 0.25° × 0.25°, which might also result in the uncertainty of our model projection. Therefore, caution should be needed to interpret our observations in the present study.

5. Conclusions

The results of our study revealed that the two pests might undergo range expansions under future change scenarios, and range overlap with their host tree might also increase; therefore, these two pests might pose greater threats to Norway spruce in the future. Additionally, host availability played a stronger role than climatic factors in shaping the range expansions of the two pests; climatic factors indirectly affect the potential ranges of the pests by altering the range of the host. Compared with the eight-spined beetle, the six-spined beetle might pose greater threats to Norway spruce based on the larger range expansion and range overlap predicted between the six-spined beetle and Norway spruce, albeit the eight-spined beetle has previously been considered to have more deleterious effects on Norway spruce. Our study could enhance our understanding of the future effects of these two pests on Norway spruce in Europe.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14102048/s1, Table S1: Importance values of each predictor in the preliminary species distribution models. Table S2: Correlations among the 19 climatic predictors. Table S3: Importance values of predictors under future scenarios. Figure S1: Potential ranges of the eight-spined beetle, the six-spined beetle and Norway spruce in Europe. Figure S2: Range overlap between the two pests and Norway spruce in Europe.

Author Contributions

Conceptualization, J.F.; methodology, J.F. and R.C.; software, R.C.; validation, R.C.; formal analysis, R.C.; investigation, R.C.; resources, R.C.; data curation, R.C.; writing—original draft preparation, R.C. and J.F.; writing—review and editing, R.C. and J.F.; visualization, R.C.; supervision, J.F.; project administration, J.F.; funding acquisition, J.F. All authors have read and agreed to the published version of the manuscript.

Funding

This study has been funded by the National Natural Science Foundation of China (Grant ID: 31560178).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

We are grateful to Xiaokang Hu for his valuable comments on the study. We would also like to thank Tao Wang for his valuable suggestions on the statistical analyses. We also appreciate anonymous reviewers’ valuable comments.

Conflicts of Interest

The authors declare that they have no known conflict of interest that could have influenced the work reported in this paper.

References

  1. MacFarlane, D.W.; Meyer, S.P. Characteristics and distribution of potential ash tree hosts for emerald ash borer. For. Ecol. Manag. 2005, 213, 15–24. [Google Scholar] [CrossRef]
  2. Looney, C.; Sheehan, K.; Bai, B.; Flowers, R.; Kohler, G.; LaGasa, E.; McKorney, A.E.; Smith, D.R. The distribution of a potential new forest pest, Monsoma pulveratum (Hymenoptera: Tenthredinidae), in the pacific northwest states. Northwest Sci. 2012, 86, 342–345. [Google Scholar] [CrossRef]
  3. Liebhold, A.M.; McCullough, D.G.; Blackburn, L.M.; Frankel, S.J.; Holle, B.V.; Aukema, J.E. A highly aggregated geographical distribution of forest pest invasions in the USA. Divers. Distrib. 2013, 19, 1208–1216. [Google Scholar] [CrossRef]
  4. Srivastava, V.; Griess, V.C.; Keena, M.A. assessing the potential distribution of Asian gypsy moth in Canada: A comparison of two methodological approaches. Sci. Rep. 2020, 10, 22. [Google Scholar] [CrossRef]
  5. Nie, P.X.; Yang, R.J.; Cao, R.Y.; Hu, X.K.; Feng, J.M. Niche and range shifts of the fall webworm (Hyphantria cunea Dury) in Europe imply its huge invasion potential in the future. Insects 2023, 14, 316. [Google Scholar] [CrossRef]
  6. Hof, A.R.; Svahlin, A. The potential effect of climate change on the geographical distribution of insect pest species in the Swedish boreal forest. Scand. J. For. Res. 2016, 3, 29–39. [Google Scholar] [CrossRef]
  7. Guan, J.; Li, M.; Ju, X.; Lin, J.; Wu, J.; Zheng, J. The potential habitat of desert locusts is contracting: Predictions under climate change scenarios. PeerJ 2021, 9, e12311. [Google Scholar] [CrossRef]
  8. Parkash, R.; Ramniwas, S.; Kajla, B. Climate warming mediates range shift of two differentially adapted stenothermal Drosophila species in the Western Himalayas. J. Asia-Pac. Entomol. 2013, 16, 147–153. [Google Scholar] [CrossRef]
  9. Lenoir, J.; Svenning, J.C. Climate-related range shifts—A global multidimensional synthesis and new research directions. Ecography 2015, 38, 15–28. [Google Scholar] [CrossRef]
  10. Perktas, U.; Elverici, C. Climate-driven range shifts of the sharp-tailed grouse Tympanuchus phasianellus. Acta Ornithol. 2019, 54, 213–222. [Google Scholar] [CrossRef]
  11. Jiang, Z.W.; Ma, L.; Mi, C.R.; Tao, S.A.; Guo, F.Y.; Du, W.G. Distinct responses and range shifts of lizard populations across an elevational gradient under climate change. Glob. Chang. Biol. 2023, 29, 2669–2680. [Google Scholar] [CrossRef] [PubMed]
  12. Liu, T.M.; Wang, J.M.; Hu, X.K.; Feng, J.M. Land-use change drives present and future distributions of fall armyworm, Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae). Sci. Total Environ. 2020, 706, 135872. [Google Scholar] [CrossRef] [PubMed]
  13. Gong, X.; Chen, Y.J.; Wang, T.; Jiang, X.F.; Hu, X.K.; Feng, J.M. Double-edged effects of climate change on plant invasions: Ecological niche modeling global distributions of two invasive alien plants. Sci. Total Environ. 2020, 740, 139933. [Google Scholar] [CrossRef] [PubMed]
  14. Yang, X.; Gao, Z.; Wang, L.Q.; Xiao, L.J.; Dong, N.; Wu, H.J.; Li, S. Projecting the potential distribution of ticks in China under climate and land use change. Int. J. Parasitol. 2021, 51, 749–759. [Google Scholar] [CrossRef] [PubMed]
  15. Balint, M.; Domisch, S.; Engelhardt, C.H.M.; Haase, P.; Lehrian, S.; Sauer, J. Cryptic biodiversity loss linked to global climate change. Nat. Clim. Chang. 2011, 1, 313–318. [Google Scholar] [CrossRef]
  16. Liu, B.Y.; Jiao, Z.H.; Ma, J.; Gao, X.; Xiao, J.H.; Hayat, M.A. Modelling the potential distribution of arbovirus vector Aedes aegypti under current and future climate scenarios in Taiwan, China. Pest Manag. Sci. 2019, 75, 3076–3083. [Google Scholar] [CrossRef]
  17. Sirami, C.; Caplat, P.; Popy, S.; Clamens, A.; Arlettaz, R.; Jiguet, F. Impacts of global change on species distributions: Obstacles and solutions to integrate climate and land use. Glob. Ecol. Biogeogr. 2017, 26, 385–394. [Google Scholar] [CrossRef]
  18. Dempster, J.P.; Pollard, E. Fluctuations in resource availability and insect populations. Oecologia 1981, 50, 412–416. [Google Scholar] [CrossRef] [PubMed]
  19. Ylioja, T.; Roininen, H.; Ayres, M.P.; Rousi, M.; Price, P.W. Host-driven population dynamics in an herbivorous insect. Proc. Natl. Acad. Sci. USA 1999, 96, 10735–10740. [Google Scholar] [CrossRef]
  20. Halsch, C.A.; Shapiro, A.M.; Thorne, J.H.; Waetjen, D.P.; Forister, M.L. A winner in the Anthropocene: Changing host plant distribution explains geographical range expansion in the gulf fritillary butterfly. Ecol. Entomol. 2020, 45, 652–662. [Google Scholar] [CrossRef]
  21. Silva, D.P.; Varela, S.; Nemésio, A.; De Marco, P. Adding biotic interactions into paleodistribution models: A host-cleptoparasite complex of neotropical orchid bees. PLoS ONE 2015, 10, e0129890. [Google Scholar] [CrossRef]
  22. Hanspach, J.; Schweiger, O.; Kuhn, I.; Plattner, M.; Pearman, P.B.; Zimmermann, N.E.; Settele, J. Host plant availability potentially limits butterfly distributions under cold environmental conditions. Ecography 2014, 37, 301–308. [Google Scholar] [CrossRef]
  23. Christiansen, E.; Bakke, A. The spruce bark beetle of Eurasia. In Plenum Publishing Corporation; Berryman, A.A., Ed.; Dynamics of Forest Insect Populations: New York, NY, USA, 1988; pp. 479–503. [Google Scholar]
  24. Pfeffer, A. Zentral-und Westpaläarktische Borken-und Kernkäfer (Coleoptera: Scolytidae, Platypodidae); Pro Entomologia, Naturhistorisches Museum Basel: Basel, Switzerland, 1995; 310p. [Google Scholar]
  25. Day, K.R.; Leather, S.R. Threats to forestry by insect pests in Europe. In Forests and Insects; Watt, A.D., Stork, N.E., Hunter, M.D., Eds.; Chapman & Hall: London, UK, 1997; pp. 177–205. [Google Scholar]
  26. Six, D.L.; Bracewell, R. Dendroctonus. In Bark Beetles: Biology and Ecology of Native and Invasive Species; Vega, F.E., Hofstetter, R.W., Eds.; Academic Press: New York, NY, USA, 2015; pp. 305–350. [Google Scholar]
  27. Muller, M.; Olsson, P.O.; Eklundh, L.; Jamali, S.; Ardo, J. Features predisposing forest to bark beetle outbreaks and their dynamics during drought. For. Ecol. Manag. 2022, 523, 120480. [Google Scholar] [CrossRef]
  28. Schebeck, M.; Schopf, A.; Ragland, G.J.; Stauffer, C.; Biedermann, P.H.W. Evolutionary ecology of the bark beetles Ips typographus and Pityogenes chalcographus. Bull. Entomol. Res. 2023, 113, 1–10. [Google Scholar] [CrossRef] [PubMed]
  29. Eidmann, H.H. Impact of bark beetles on forests and forestry in Sweden. J. Appl. Ent. 1992, 114, 193–200. [Google Scholar] [CrossRef]
  30. Marini, L.; Lindelöw, A.; Jönsson, A.M.; Wulff, S.; Schroeder, L.M. Population dynamics of the spruce bark beetle: A long-term study. Oikos 2013, 122, 1768–1776. [Google Scholar] [CrossRef]
  31. Marini, L.; Økland, B.; Jönsson, A.M.; Bentz, B.; Carroll, A.; Forster, B.; Gregoire, J.C.; Hurling, R.; Nageleisen, L.M.; Netherer, S. Climate drivers of bark beetle outbreak dynamics in Norway spruce forests. Ecography 2017, 40, 1426–1435. [Google Scholar] [CrossRef]
  32. Schroeder, M.; Cocos, D. Performance of the tree-killing bark beetles Ips typographus and Pityogenes chalcographus in non-indigenous lodgepole pine and their historical host Norway spruce. Agric. For. Entomol. 2017, 20, 347–357. [Google Scholar] [CrossRef]
  33. Seidl, R.; Schelhaas, M.J.; Lexer, M.J. Unraveling the drivers of intensifying forest disturbance regimes in Europe. Glob. Chang. Biol. 2011, 17, 2842–2852. [Google Scholar] [CrossRef]
  34. Markovic, C.; Stojanovic, A. Differences in bark beetle (Ips typographus and Pityogenes chalcographus) abundance in a strict spruce reserve and the surrounding spruce forests of Serbia. Phytoparasitica 2010, 38, 31–37. [Google Scholar] [CrossRef]
  35. Göthlin, E.; Schroeder, L.M.; Lindelöw, A. Attacks by Ips typographus and Pityogenes chalcographus on windthrown spruces (Picea abies) during the two years following a storm felling. Scand. J. For. Res. 2000, 15, 542–549. [Google Scholar] [CrossRef]
  36. Eriksson, M.; Lilja, S.; Roininen, H. Dead wood creation and restoration burning: Implications for bark beetles and beetle induced tree deaths. For. Ecol. Manag. 2006, 231, 205–213. [Google Scholar] [CrossRef]
  37. Jurc, M.; Perko, M.; Dzeroski, S.; Demsar, D.; Hrasovec, B. Spruce bark beetles (Ips typographus, Pityogenes chalcographus, Col.: Scolytidae) in the Dinaric mountain forests of Slovenia: Monitoring and modeling. Ecol. Model. 2006, 194, 219–226. [Google Scholar] [CrossRef]
  38. Berthelot, S.; Fruhbrodt, T.; Hajek, P.; Nock, C.A.; Dormann, C.F.; Bauhus, J.; Frund, J. Tree diversity reduces the risk of bark beetle infestation for preferred conifer species, but increases the risk for less preferred hosts. J. Ecol. 2021, 109, 2649–2661. [Google Scholar] [CrossRef]
  39. Yang, R.J.; Cao, R.Y.; Gong, X.; Feng, J.M. Large shifts of niche and range in the golden apple snail (Pomacea canaliculate), an aquatic invasive species. Ecosphere 2023, 14, e4391. [Google Scholar] [CrossRef]
  40. Brown, J.L. SDMtoolbox: A python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol. Evol. 2014, 5, 694–700. [Google Scholar] [CrossRef]
  41. Brown, J.L.; Bennett, J.R.; French, C.M. SDMtoolbox 2.0: The next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. PeerJ 2017, 5, e4095. [Google Scholar] [CrossRef] [PubMed]
  42. Fick, S.E.; Hijmans, R.J. WorldClim2: New 1 km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 2017, 37, 4302–4315. [Google Scholar] [CrossRef]
  43. Zhang, M.Z.; Xu, Z.F.; Han, Y.; Guo, W.D. Evaluation of CMIP6 models toward dynamical downscaling over 14 CORDEX domains. Clim. Dyn. 2022, 50, 803–817. [Google Scholar] [CrossRef]
  44. Duarte, A.; Wolcott, D.M.; Chow, T.E.; Ricca, M.A. Identifying potential habitat for the endangered Aleutian shield fern using topographical characteristics. J. Fish Wildl. Manag. 2012, 3, 303–310. [Google Scholar] [CrossRef]
  45. Nauyoma, L.T.; Wassenaar, T.D.; Mfune, J.K.E.; van der Waal, C.; Kwembeya, E.G. Field surveys and revegetation experiments show that simulation of topographical habitat features could improve the chances of successful restoration for the threatened succulent Juttadinteria albata. Restor. Ecol. 2019, 27, 730–737. [Google Scholar] [CrossRef]
  46. Beckerath, X.V.; Benadi, G.; Gilg, O.; Sittler, B.; Yannic, G.; Klein, A.M.; Eitzinger, B. Long-term monitoring reveals topographical features and vegetation that explain winter habitat use of an Arctic rodent. Arct. Sci. 2022, 8, 349–361. [Google Scholar] [CrossRef]
  47. Michalak, J.L.; Lawler, J.J.; Roberts, D.R.; Carroll, C. Distribution and protection of climatic refugia in North America. Conserv. Biol. 2018, 32, 1414–1425. [Google Scholar] [CrossRef]
  48. Hijmans, R.J.; Cameron, S.E.; Parra, J.L.; Jones, P.G.; Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 2005, 25, 1965–1978. [Google Scholar] [CrossRef]
  49. Dormann, C.F.; Elith, J.; Bacher, S.; Buchmann, C.; Carl, G.; Carre, G.; Marquez, J.R.G.; Jaime, R.; Gruber, B.; Lafourcade, B.; et al. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 2013, 36, 27–46. [Google Scholar] [CrossRef]
  50. Thuiller, W.; Lafourcade, B.; Engler, R.; Araujo, M.B. BIOMOD—A platform for ensemble forecasting of species distributions. Ecography 2009, 32, 369–373. [Google Scholar] [CrossRef]
  51. Barbet-Massin, M.; Jiguet, F.; Albert, C.H.; Thuiller, W. Selecting pseudo-absences for species distribution models: How, where and how many? Methods Ecol. Evol. 2012, 3, 327–338. [Google Scholar] [CrossRef]
  52. Liu, C.; Newell, G.; White, M. On the selection of thresholds for predicting species occurrence with presence–only data. Ecol. Evol. 2016, 6, 337–348. [Google Scholar] [CrossRef]
  53. Nie, P.X.; Feng, J.M. Global niche and range shifts of Batrachochytrium dendrobatidis, a highly virulent amphibian-killing fungus. Fungal. Biol. 2022, 126, 809–816. [Google Scholar] [CrossRef]
  54. Faccoli, M.; Bernardinelli, I. Composition and elevation of spruce forests affect susceptibility to bark beetle attacks: Implications for forest management. Forests 2014, 5, 88–102. [Google Scholar] [CrossRef]
  55. Nielsen, D.G.; Muilenburg, V.L.; Herms, D.A. Interspecific variation in resistance of Asian, European, and North American birches (Betula spp.) to bronze birch borer (Coleoptera: Buprestidae). Environ. Entomol. 2011, 40, 648–653. [Google Scholar] [CrossRef] [PubMed]
  56. Dilts, E.; Steele, M.O.; Engler, J.D.; Pelton, E.M.; Jepsen, S.J.; McKnight, S.J.; Taylor, A.R.; Fallon, C.E.; Black, S.H.; Cruz, E.E.; et al. Host plants and climate structure habitat associations of the western monarch butterfly. Front. Ecol. Evol. 2019, 7, 188. [Google Scholar] [CrossRef]
  57. Dang, Y.Q.; Zhang, Y.L.; Wang, X.Y.; Xin, B.; Quinn, N.F.; Duan, J.J. Retrospective analysis of factors affecting the distribution of an invasive wood-boring insect using native range data: The importance of host plants. J. Pest Sci. 2021, 94, 981–990. [Google Scholar] [CrossRef]
  58. Ding, F.Y.; Fu, J.Y.; Jiang, D.; Hao, M.M.; Lin, G. Mapping the spatial distribution of Aedes aegypti and Aedes albopictus. Acta Trop. 2018, 178, 155–162. [Google Scholar] [CrossRef] [PubMed]
  59. Dickens, B.L.; Sun, H.; Jit, M.; Cook, A.R.; Carrasco, L.R. Determining environmental and anthropogenic factors which explain the global distribution of Aedes aegypti and Ae. albopictus. BMJ Glob. Health 2018, 3, e000801. [Google Scholar] [CrossRef]
  60. Root, R.B. Organization of a plant–arthropod association in simple and diverse habitats: Fauna of collards (Brassica oleracea). Ecol. Monogr. 1973, 43, 95–120. [Google Scholar] [CrossRef]
  61. Rocca, F.D.; Milanesi, P. The new dominator of the world: Modeling the global distribution of the Japanese beetle under land use and climate change scenarios. Land 2022, 11, 567. [Google Scholar] [CrossRef]
Forests 14 02048 g001
Figure 1. Occurrences of Norway spruce, the eight-spined beetle and the six-spined beetle in Europe. (a) Occurrence records of Norway spruce, 12,528 records; (b) occurrence records of the eight-spined beetle, 1657 records; (c) occurrence records of the six-spined beetle, 1389 records.
Figure 1. Occurrences of Norway spruce, the eight-spined beetle and the six-spined beetle in Europe. (a) Occurrence records of Norway spruce, 12,528 records; (b) occurrence records of the eight-spined beetle, 1657 records; (c) occurrence records of the six-spined beetle, 1389 records.
Forests 14 02048 g001
Forests 14 02048 g002
Figure 2. Potential ranges of the eight-spined beetle, the six-spined beetle and Norway spruce in Europe. (a–c) Represented the potential ranges of Norway spruce under current situations and SSP126 and SSP585 scenarios, covering 3.13 million km2, 2.87 million km2, and 3.28 million km2, respectively. (d–f) Represented the potential ranges of the eight-spined beetle under current conditions and the scenarios of SSP126 and SSP585, covering 1.22 million km2, 1.48 million km2, 2.12 million km2, respectively; (g–i) represented the potential ranges of the six-spined beetle under current conditions and the scenarios of SSP126 and SSP585, covering 1.69 million km2, 2.42 million km2, 2.52 million km2, respectively. Red and grey indicated the potential ranges and no-potential ranges, respectively.
Figure 2. Potential ranges of the eight-spined beetle, the six-spined beetle and Norway spruce in Europe. (a–c) Represented the potential ranges of Norway spruce under current situations and SSP126 and SSP585 scenarios, covering 3.13 million km2, 2.87 million km2, and 3.28 million km2, respectively. (d–f) Represented the potential ranges of the eight-spined beetle under current conditions and the scenarios of SSP126 and SSP585, covering 1.22 million km2, 1.48 million km2, 2.12 million km2, respectively; (g–i) represented the potential ranges of the six-spined beetle under current conditions and the scenarios of SSP126 and SSP585, covering 1.69 million km2, 2.42 million km2, 2.52 million km2, respectively. Red and grey indicated the potential ranges and no-potential ranges, respectively.
Forests 14 02048 g002
Forests 14 02048 g003
Figure 3. Range shifts of the eight-spined beetle, the six-spined beetle and Norway spruce in Europe. (a,b) Represented the range shifts of Norway spruce under the current-SSP126 scenario and current-SSP585 scenario, respectively. (c,d) Represented the range shifts of the eight-spined beetle under the current-SSP126 scenario and current-SSP585 scenario, respectively. (e,f) The range shifts of the six-spined beetle under the current-SSP126 scenario and current-SSP585 scenario, respectively. Range expansions of the pests were observed in both scenarios. Expanded range, stabilized range and unfilled range represented the potential ranges occupied only by a species occupied only under future scenarios, the potential ranges shared by a species under both current conditions and future scenarios and the potential ranges occupied only by a species occupied only under current conditions, respectively. Blue, red and yellow indicated the expanded range, stabilized range and unfilled range, respectively.
Figure 3. Range shifts of the eight-spined beetle, the six-spined beetle and Norway spruce in Europe. (a,b) Represented the range shifts of Norway spruce under the current-SSP126 scenario and current-SSP585 scenario, respectively. (c,d) Represented the range shifts of the eight-spined beetle under the current-SSP126 scenario and current-SSP585 scenario, respectively. (e,f) The range shifts of the six-spined beetle under the current-SSP126 scenario and current-SSP585 scenario, respectively. Range expansions of the pests were observed in both scenarios. Expanded range, stabilized range and unfilled range represented the potential ranges occupied only by a species occupied only under future scenarios, the potential ranges shared by a species under both current conditions and future scenarios and the potential ranges occupied only by a species occupied only under current conditions, respectively. Blue, red and yellow indicated the expanded range, stabilized range and unfilled range, respectively.
Forests 14 02048 g003
Forests 14 02048 g004
Figure 4. Range overlap between the two pests and Norway spruce in Europe. (a–c) Represented the range overlap between the eight-spined beetle and Norway spruce under current conditions and the scenarios of SSP126 and SSP585, with range overlap indices being 0.552, 0.613 and 0.659, respectively. (d–f) Represented the range overlap between the six-spined beetle and Norway spruce under current conditions and the scenarios of SSP126 and SSP585, with range overlap indices being 0.693, 0.852 and 0.764, respectively. Pest range, overlapped range and host range represented the potential ranges occupied only by the pests, the potential ranges shared by the pests and the host, and the potential ranges occupied only by the host, respectively. Brown, blue and red indicated pest range, overlapped range and host range, respectively.
Figure 4. Range overlap between the two pests and Norway spruce in Europe. (a–c) Represented the range overlap between the eight-spined beetle and Norway spruce under current conditions and the scenarios of SSP126 and SSP585, with range overlap indices being 0.552, 0.613 and 0.659, respectively. (d–f) Represented the range overlap between the six-spined beetle and Norway spruce under current conditions and the scenarios of SSP126 and SSP585, with range overlap indices being 0.693, 0.852 and 0.764, respectively. Pest range, overlapped range and host range represented the potential ranges occupied only by the pests, the potential ranges shared by the pests and the host, and the potential ranges occupied only by the host, respectively. Brown, blue and red indicated pest range, overlapped range and host range, respectively.
Forests 14 02048 g004
Table 1. The importance values of the predictors in the species distribution models for Norway spruce, the eight-spined beetle and the six-spined beetle.
Table 1. The importance values of the predictors in the species distribution models for Norway spruce, the eight-spined beetle and the six-spined beetle.
Norway SpruceThe Eight-Spined BeetleThe Six-Spined Beetle
CategoryPredictorsIVsCategoryPredictorsIVsCategoryPredictorsIVs
ClimateBio40.5482Host availabilityHost availability0.8194Host availabilityHost availability0.7331
ClimateBio10.2407ClimateBio100.0746ClimateBio110.0856
ClimateBio50.1479ClimateBio40.0683Land-useCropland0.0513
Land-usePrimf0.0852TopographyEle0.0531Land-usePaster0.0377
Land-useCropland0.0419Land-usePrimf0.0358ClimateBio150.0319
ClimateBio180.0291ClimateBio90.0299Land-useSecdf0.0251
TopographyEle0.0208Climate Bio150.0253ClimateBio160.0205
ClimateBio20.0159ClimateBio170.0245Land-usePrimn0.0195
Land-useUrban0.0154Land-useCropland0.0213TopographySlope0.0168
ClimateBio140.0108Land-useUrban0.0207Land-useUrban0.0128
Land-useSecdf0.0089ClimateBio20.0154ClimateBio80.0121
ClimateBio80.0057Land-usePaster0.0148TopographyEle0.0094
Land-usePaster0.0045Land-usePrimn0.0148Land-useRang0.0086
Land-useSecdn0.0045ClimateBio180.0144ClimateBio20.0079
Land-useRang0.0040Land-useSecdn0.0130Land-usePrimf0.0071
Land-usePrimn0.0023Land-useRang0.0071TopographyAspect0.0035
ClimateBio150.0018Climate Bio80.0067
TopographySlope0.0012TopographyAspect0.0038
TopographyAspect0.0001
Note: IVs: importance values. Bio1: mean annual temperature (°C); Bio2: averaged diurnal range (°C); Bio4: seasonality of temperature; Bio5: maximum temperature in the warmest month (°C); Bio8: averaged temperature in the wettest season (°C); Bio9: averaged temperature in the driest season (°C); Bio10: averaged temperature in the warmest season (°C); Bio11: averaged temperature in the coldest season (°C); Bio14: Precipitation in the driest month (mm); Bio15: seasonality of precipitation (mm); Bio16: Precipitation in wettest season; Bio17: precipitation in the driest season (mm); Bio18: precipitation in the warmest season (mm); Asp: Aspect (°); Ele: Elevation (m); Slope: Slope (°); Primf: Fractions of forested primary land; Primn: Fractions of non-forested primary land; Cropland: Fractions of cropland; Paster: Fractions of managed pasture; Secdf: Fractions of potentially forested secondary land; Secdn: Fractions of potentially non-forested secondary land; Range: Fractions of rangeland; Urban: Fractions of urban land. Host availability: host availability.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cao, R.; Feng, J. Future Range Shifts Suggest That the Six-Spined Spruce Bark Beetle Might Pose a Greater Threat to Norway Spruce in Europe than the Eight-Spined Spruce Bark Beetle. Forests 2023, 14, 2048. https://doi.org/10.3390/f14102048

AMA Style

Cao R, Feng J. Future Range Shifts Suggest That the Six-Spined Spruce Bark Beetle Might Pose a Greater Threat to Norway Spruce in Europe than the Eight-Spined Spruce Bark Beetle. Forests. 2023; 14(10):2048. https://doi.org/10.3390/f14102048

Chicago/Turabian Style

Cao, Runyao, and Jianmeng Feng. 2023. "Future Range Shifts Suggest That the Six-Spined Spruce Bark Beetle Might Pose a Greater Threat to Norway Spruce in Europe than the Eight-Spined Spruce Bark Beetle" Forests 14, no. 10: 2048. https://doi.org/10.3390/f14102048

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop