Study of the Spatial Distribution of the Bark Beetle in the Ejido Tixtlancingo

Abstract

The spatial distribution of Dendroctonus frontalis Zimmermann, 1868, and Dendroctonus mexicanus Hopkins, 1905, was determined from 2020 to 2021 in the Tixtlancingo ejido. The information came from two surveys because, despite the abundant forested areas in this geographical area of the state of Guerrero, Mexico, economic resources for pest biomonitoring are limited. However, it was possible to identify the presence of 76 outbreaks affecting 1117.697 hectares and 95,078 trees, totaling 14,223.8 ${\mathrm{m}}^3$ of standing timber volume. In 2020, 28 outbreaks were reported, with the eastern spatial distribution showing the most damage from bark beetles, particularly in outbreaks 7 and 14 of the surveyed area. The most affected conifers were Pinus maximinoi H. E. Moore (44.71%), Pinus oocarpa Schiede ex Schltdl. (39.93%), and Pinus pseudostrobus Lindl. (15.36%). The affected timber volume was observed in diameter categories of 30 cm for the three pine species, with infestation of 90,549 trees (13,497.6 ${\mathrm{m}}^3$ t.t.v. (total tree volume)) across 1057.64 hectares. In 2021, 48 outbreaks were recorded, with the northeastern and southern parts of the surveyed area showing the most damage from the bark beetle. The trees most affected by the bark beetle were P. oocarpa (59.17%), P. maximinoi (33.94%), and P. pseudostrobus (6.89%). It was observed that the affected volume occurred in trees with diameter categories of 50 cm for the three pine species, affecting 4529 trees (726.214 ${\mathrm{m}}^3$ t.t.v.) distributed over 60.06 hectares. The contribution of this work lies in establishing a baseline for monitoring damage caused by this beetle, which affects forest resources and diminishes the possibility of maintaining carbon capture areas in the medium and long term, thus impacting the Sustainable Development Goals (SDGs) of the 2030 agenda, specifically Goals 11, 13, and 15.

1. Introduction

Beetles of the genus Dendroctonus, commonly know as pine bark beetles, are insect pests of economic and ecological importance in conifer ecosystems in North and Central America [1]. Of the 13 species of Dendroctonus described for Mexico [2], only D. mexicanus, D. frontalis, D. rhizophagus Thomas & Bright, and D. adjunctus Blandford have become important pests of pine forests [3,4,5], causing ecological imbalances and substantial economic losses for the forest industry [6,7].

The abiotic factors that most influence their distribution and abundance are water availability, temperature [8,9,10], humidity, precipitation, and altitudinal gradient [11,12,13]. According to García [14], the distribution of a species is favored by climatic variations. Thus, warm temperatures [15,16], climate change [17,18], droughts [19], forest fires [20], as well as tree stand characteristics and location [21,22] are environmental factors that favor the increase in debarking populations.

Most of the work on population fluctuations of Dendroctonus has been carried out in northern and central Mexico [23]; in the southeastern states of Guerrero, Oaxaca, and Chiapas, studies of the distribution and impact of these organisms are scarce [24]. Studies of the spatial distribution of this forest pest by Perez-Miranda [25], Endara-Agramont [26], González-Hernández [27], Viveros [28], Martínez-Rincón [29], and Carrillo-Aguilar [30] stand out, but none refer to the state of Guerrero, Mexico. However, for this federated entity, during the period 2012 to 2020, the National Forestry Commission issued 243 sanitation notifications for pests and diseases that affected an area of 88,597.74 ha [31]. The main pest agents, in order of importance, were: defoliating insects with 61,709.68 ha affected, followed by debarking insects with 17,998.43 ha, parasitic plants with 7256.56 ha, and diseases with 3379.17 ha.

Between 2020 and 2021 in the ejido Tixtlancingo municipality of Coyuca de Benitez, Guerrero, Mexico, 76 outbreaks of this pest were identified, affecting 1117.697 ha. A total of 95,078 standing pine trees (14,223.214 ${\mathrm{m}}^3$ t.t.v.) of the species P. oocarpa, P. maximinoi, and P. pseudostrobus were affected, with two causal agents: D. mexicanus and D. frontalis. In response to this situation, the ejido authorities in coordination with technical service providers and the National Forestry Commission (Conafor), helped to solve the problem with limited actions and responses. The method of combat and control is physical and chemical, in accordance with NOM 019 SEMARNAT 2006, consisting of felling the affected trees, stripping the bark, and incinerating or burying the bark; occasionally, chemical compounds are applied to felled trees with bark [32].

The objective of this study was to determine the spatial distribution of the bark beetles D. frontalis and D. mexicanus that affect the forests of the Tixtlancingo ejido.

2. Materials and Methods

The Tixtlancingo ejido, in the Municipality of Coyuca de Benítez, is located in Hydrological Region 19, Sierra Madre del Sur, Costa Grande Region of the State of Guerrero. It has a total area of 19,380 ha and is made up of 10 communities: El Papayito, La Lima, Tixtlancingo, Piedras Grandes, La Almolonga, Agua Hedionda, Ocotito, El Paso del Bellaco, La Carbonera, and La Cuadrilla. It is bordered to the north by the ejidos of Las Compuertas and Santa Rosa; to the south by the ejidos of Valle del Río, Bajos del Ejido, and Aguas Blancas; to the east by the ejidos of Santa Cruz Tasajeras, Platanillo, San José Agua Zarca, and San Juan del Rio; and to the west by the ejidos of Pueblo Viejo and Aguas Blancas. Specifically, the diagnosed area has altitudes ranging from 1700 to 2200 m above sea level, with a 15% to 35% slope, 12 to 18 mm of precipitation, and an average annual temperature of 24 to 33 °C. The ejido’s land use and vegetation is cultivated pastureland, and it is surrounded by deciduous and sub-deciduous forest, pine and oak vegetation. The area is considered Climate A (w2) Warm sub-humid with summer rains and higher humidity.

The diagnosed area is shown in Figure 1 in red, and it extends 81.26 ${\mathrm{km}}^2$.

Host Trees

Pinus maximinoi H.E. Moore. It is distributed from 200 to 2400 m above sea level in deep clay loam to clay loam soils, with a pH between 4.2 and 6.5. It can reach 25 to 30 m in height, with a diameter of up to 1 m. It has smooth and thin bark of 2 to 4 cm in large rectangular plates. When it is old, it tends to break into elongated platelets with fissures that have a reddish brown color on the inside, while the outside is gray [33]. It presents leaves of five needles per fascicle, with a length of 20 to 27 cm and width of 0.7 to 0.1 mm. Cones are ovoid or oblong, symmetrical, and reddish-brown, with dimensions of 5 to 8 cm long and 4 to 7 cm wide. The wood has a pale brown color, lustrous surface, pleasant odor, and characteristic flavor, with a fine texture and straight grain. It has a specific weight of 0.44 to 0.50 g/cm³, is light, moderately easy to work, easy to treat with preservatives, and has a good drying speed, with the characteristic of not presenting defects [34].

Pinus oocarpa Schiede ex Schltdl. It is a resinous tree that reaches heights of 30 to 35 m, with a normal diameter of up to 125 cm [35]. Its needles are straight and rigid, usually grouped in fascicles of five, with a length of 17 to 30 cm and width of 0.8 to 1.4 mm. The cones are solitary or in whorls of up to four, ovoid when open and globose when closed. They are 3 to 10 cm long and 3 to 12 cm wide [35]. The best yields have been reported from 200 to 1420 m above sea level. It is distributed on eroded and thin soils that are well-drained, acid to neutral, of low fertility, and derived from volcanic materials on sandy, sandy-loam, and clay-loam textures. The pH is in the range of 4.5 to 6.8 [36].

Pinus pseudostrobus Lindl. The tree is 15 to 40 m high and 40–80 cm in diameter, with a straight shaft free of branches from 30% to 50% of its total height. It has a thick crown and grayish rough bark, as well as dark green leaves with needles in groups of five roughly 16–34 cm long by 0.75–1.25 cm wide [37]. The cones are ovoid to cylindrical, light brown, and 10–15 cm long by 6–8 cm wide. It has small seeds that are 6 mm long and dark brown, with an articulated wing 20–23 mm long [38]. Its best development is from 2000 to 2400 m above sea level. It is distributed in moderately deep shallow soils with sandy loam or sandy-clay loam texture, with a pH ranging from 5.5 to 7.0.

Dendroctonus frontalis Zimmermann, 1868. Commonly known as the pine bark beetle, it has a hard, reddish-brown to black exoskeleton and measures about 3 mm, about the size of a grain of rice. It has short legs and a rounded rear body [39]. Its altitudinal distribution is between 600 and 3200 m above sea level. The highest percentage of occurrence (41%) is found in P. oocarpa.

Dendroctonus mexicanus Hopkins, 1905. It has a black head and a light brown to black prothorax and elytra. An aggressive species, it is capable of killing healthy trees and developing epidemic outbreaks; it is common to find it cohabiting with D. frontalis in the same tree. It is the species with the widest distribution in the forests of Mexico. Its altitudinal limits are from 800 to 3650 m above sea level. The highest percentage of incidence (38%) occurs in Pinus leiophylla Schl. & Cham.

3. Methodology

Based on the General Law of Sustainable Forest Development, its regulations, and the quantitative and qualitative information obtained from surveys and inventories, the diameter and height were used to calculate the volume of infested trees for extraction [32]. The physicochemical method was employed, namely, felling, chopping, chemical application, and immediate extraction of standing trees exhibiting the following symptoms according to Conafor [6]: hard resin clumps on the stem and foliage that may be green or light green, yellowish-green (lemony), yellowish, yellowish-reddish, or reddish, with primary pests (eggs, larvae, pupae, preimagoes, and adults) inside, a common characteristic in all trees. Samples of the pests were collected, preserved in 70% alcohol, and identified using the simplified keys of Cibrián [40] and those published by Wood [41]. Additionally, the sanitized areas underwent silvicultural actions for forest protection and promotion.

The information from the diagnoses used corresponds to the years 2020 and 2021; these were prepared from April to June during the dry season, when the highest incidence of forest fires occurs. Containment was carried out from July to September, depending on the prompt response of the environmental authority. For containment, the plagued trees were marked with an impact hammer then felled, and a sprinkler was used to apply the chemical Cypermethrin, an agricultural pyrethroid insecticide, as the active agent and Agrotín as a fixative or adherent agent, both recommended by Secretary of the Environment and Natural Resources (Semarnat), in a ratio of one liter of the former to 600 mL of the latter dissolved in 200 L of water. The roundwood from the forest cleanup was transported with the corresponding plagued forest trees to a sawmill.

3.1. Climatic Conditions

Geographically, Coyuca de Benítez borders the municipality of Acapulco de Juárez; located in this municipality are the climatic stations Laguna de Tres Palos (16°49′46.9194″ N, 99°46′41.88″ W) and Acapulco (16°45′46.06″ N, 99°44′56.68″ W), which are operated by the National Meteorological System. The Laguna de Tres Palos station, located at 24 m a.s.l., recorded information for the year 2020, and the Acapulco station, located at 5 m a.s.l., recorded information for the years 2020 and 2021.

3.2. Spatial Poisson Process

The spatial distribution of debarking in the study area was performed with a spatial Poisson process. The number of affected trees in each of the sites is the study variable, Y; the sites, $s_1,\dots ,s_n$, are the locations of the variable Y for the year 2020 ($n=28$) and for the year 2021 ($n=48$).

As $Y_i$ represent counts, then the spatial distribution of debarking can be modeled with a spatial Poisson process [42]:

$$Y_i|W(·)\sim Poisson\left({\mu }_i\right),$$

(1)

where $W=\{W\left(s\right):s\in A\subset R^2\}$ is a stationary Gaussian spatial field with a multivariate normal distribution, $E\left(W\right(s\left)\right)=0$, and $\mathsf{\Sigma }=Var\left(W\left(s\right)\right)={\sigma }^{2}R\left(\varphi \right)$, i.e.,

$$W\sim N_n(0,\Sigma ).$$

$R\left(\varphi \right)$ is a correlation matrix of the Gaussian process of dimension $n\times n$, the elements of which are given by:

$${\left(R\left(\varphi \right)\right)}_{ij}=\rho (h_{ij},\varphi ).$$

The value ${\left(R\left(\varphi \right)\right)}_{ij}$ indicates the correlation that exists between $W\left(s_i\right)$ and $W\left(s_j\right)$, $\varphi$ is a scale parameter, and $h_{ij}=\parallel s_i-s_j\parallel$ is the Euclidean distance that exists between the sites $s_i$ and $s_j$. The structure assumed for the function $\rho (h_{ij},\varphi )$ is the Matérn function [43], given by

$$\rho (h,\varphi )=\frac{1}{2^{\kappa -1}\mathsf{\Gamma }\left(\kappa \right)}{\left(\frac{h}{\varphi }\right)}^{\kappa }{K}_{\kappa }\left(\frac{h}{\varphi }\right),h\ge 0,\varphi >0,\kappa >0,$$

where $\mathsf{\Gamma }(·)$ is the gamma function, and $K_{\kappa }(·)$ denotes the modified Bessel function of order _κ.

The processes $\{Y\left(s\right):s\in A\subset R^2\}$, conditional on W, are mutually independent random variables, with $E\left[Y_i\right|W(·)]={\mu }_i$, where $g\left({\mu }_i\right)={\eta }_i$ with ${\mu }_i=g^{-1}\left({\eta }_i\right),i=1,\dots ,n$, g being a known league function. The linear predictor is given by ${\eta }_i=D\beta +W\left(s_i\right)$ and ${\mu }_i=g^{-1}(D\beta +W\left(s_i\right))$. In this case, $D=\mathbf{1}$ is the design matrix, $\mathbf{1}$ is a vector of $n\times 1$ of ones, and $\beta ={\beta }_0$ is an unknown parameter. For the estimation of the parameters of the Poisson spatial process, $\beta$, ${\sigma }^2$, ${\tau }^2$, and $\varphi$, MCMC algorithms are used [42].

3.3. Spatial Distribution Evaluation

To evaluate the distribution of the spatial model, the Pearson correlation coefficient of the observed data and the predicted values was calculated; if the spatial model is adequate, the correlation value should tend to 1.

3.4. Statistics Software

For the spatial distribution of the damage caused by debarking in the three pine species, we worked with the logarithm of the total number of affected trees at each site. For the estimation of the spatial Poisson model, we used the function pois.krige from the package geoRglm [44] and the R statistical software package, version 4.3.1 [45].

3.5. Correlation in Bark Beetle Damage

Pearson’s correlation coefficient was used to test the existence of a linear relationship in the damage caused by the bark beetle in the three pine species.

4. Results

The results for the years 2020 and 2021 are presented below; subsequently, a comparison is made of the results observed in the two temporal periods, taking into account the affected areas, volumes, and damages in relation to the pest–host.

4.1. Climatic Variables

Table 1. Laguna de Tres Palos climatological station, year 2020.

Factors	Average April	Average May	Average June
Precipitation (mm)	0.000	0.000	5.443
Air temperature (°C)	26.233	24.839	27.800
Minimum temperature (°C)	24.733	23.613	26.633
Maximum temperature (°C)	31.300	30.935	31.867

shows the monthly averages of four climatic variables for the Laguna de Tres Palos weather station for the months of April, May, and June 2020. In all three months, the average monthly temperature was higher than 24 °C and lower than 28 °C, whereas the average monthly maximum temperature was between 30 °C and 32 °C. In May, an average monthly minimum temperature of 23.613 °C was recorded. The average monthly precipitation was nil in April and May; in June, an average precipitation of 5.443 mm was observed. According to this information, for the time period of the study, precipitation was very little, and the air as well as the minimum and maximum temperatures observed in the three months were very similar.

Table 2. Acapulco climatological station, 2020–2021.

Factors	Average April	Average May	Average June	Year
Air temperature (°C)	26.907	27.525	28.780	2020
Air temperature (°C)	26.997	28.720	27.139	2021
Minimum precipitation (mm)	0.000	0.006	0.131	2021

shows the monthly averages of two environmental factors recorded by the Acapulco weather station for the months of April, May, and June 2020. Although there are several missing data points, it can be observed that the air temperature was higher in June 2020 (28.780 °C). Air temperature was higher in May 2021 and, according to the records, there was rainfall in May and June 2021.

4.2. Bark Beetle Damage, 2020

Figure 2 shows the area diagnosed with 28 virulent outbreaks observed in the ejido of Tixtlancingo in the year 2020. The areas of each of the 28 sites range from 1.46 hectares (El Arrozal 2) to 134.72 hectares (Loma Pelona (El Chorro) 1). In this year, the forest area in Tixtlancingo was 8657.26 hectares, of which 1057.64 hectares were affected; that is, 12.21% of the forest area was affected. This gave an affected volume of 13,497.586 m³ t.t.v.

In 2020, in terms of the number of trees, the most affected pine species was P. maximinoi (44.7%); however, due to its dasymetric dimensions, P. oocarpa represented the highest volume of infestation (46.8%). For the year 2021, both in terms of the number of trees (59.2%) and volume (70.3%), P. oocarpa had the highest infestation rate. Meanwhile, in both diagnosed periods, the least affected species was P. pseudostrobus (

Table 3. Trees affected by bark beetles in the forest of the Tixtlancingo ejido, 2020–2021.

Species	No. Trees	Volume (${\mathrm{m}}^3$ t.t.v.)	No. Trees	Volume (${\mathrm{m}}^3$ t.t.v.)
	Year 2020		Year 2021
P. maximinoi	40,484 (44.7%)	5735.34 (42.5%)	1537 (33.9%)	194.12 (26.7%)
P. oocarpa	36,159 (39.9%)	6320.71 (46.8%)	2680 (59.2%)	510.50 (70.3%)
P. pseudostrobus	13,906 (15.4%)	1441.54 (10.7%)	312 (6.9%)	21.59 (3.0%)
Total	90,549	13,497.59	4529	726.21

).

Figure 3, Figure 4 and Figure 5 show the total number of trees affected (TTA) by the bark beetle in each of the pine species in 2020. Figure 3 shows the spatial distribution of the damage caused by the bark beetle on P. maximinoi (TTA P. maximinoi). It can be seen that the greatest damage occurs in the eastern exposure of the diagnosed area, in the sites El Cerro Alto 1 (outbreak 7) and El Filo de la Antena 1 (outbreak 14). To the southwest is the ejido Loma Pelona (El Chorro) 1 (outbreak 26). The spatial distribution of the damage shows that there are several outbreaks in the periphery of the diagnosed area that show damage.

Figure 4 shows the total number of P. oocarpa trees affected by the bark beetle in 2020. The greatest damage occurs in La Cieneguita 1 (outbreak 23), El Cerro Alto 1 (outbreak 7, center of the ejido), and El Filo de la Antena 1 (outbreak 14), located in the east exposure of the diagnosed area. In this case, the damage of the P. oocarpa species is less dispersed. According to the above, the species P. maximinoi and P. oocarpa show more damage in outbreaks 7 and 14.

With the species P. pseudostrobus, the greatest damage is observed in outbreaks 7 and 14, El Cerro Alto 1 and El Filo de la Antena 1, respectively (east of the ejido). These coincide with the outbreaks where the species P. maximinoi and P. oocarpa show damage by the bark beetle. Graphically, it can be inferred that the greatest damage to P. pseudostrobus occurs to the east of the diagnosed area and is even less dispersed than in the other two cases (Figure 5).

Figure 6 presents the TTA in each of the outbreaks and for the three species. The species P. oocarpa has the highest values at three sites: El Cerro Alto 1, El Filo de la Antena 1, and La Cieneguita 1. On the other hand, the species P. pseudostrobus has the highest values in El Cerro Alto 1 and El Filo de la Antena 1, while P. maximinoi has the highest values in El Cerro Alto 1, El Filo de la Antena 1, and La Pelona 1. The two sites where the three species are most affected by the bark beetle are located in the east exposure of the diagnosed area, in the El Cerro Alto 1 and El Filo de la Antena 1 outbreaks.

Pearson’s correlation coefficient indicates that P. maximinoi and P. oocarpa (r = 0.52, p-value < 0), P. maximinoi and P. pseudostrobus (r = 0.73, p-value < 0), and P. oocarpa and P. pseudostrobus (r = 0.77, p-value < 0) presented a positive and significant correlation in bark beetle damage for the three pine species. The positive correlation indicates that, if any of the three species is affected by the bark beetle, then the other two species will also be affected by the bark beetle.

Spatial Interpolation

At a significance level of $\alpha$ = 0.05, the Pearson correlation coefficient between P. maximinoi damaged by the bark beetle and the estimated affected level was 0.522 (p value = 0.0004), which indicates that the model used is adequate. The spatial distribution of the bark beetle showed a higher incidence of damage in the periphery of the diagnosed area (Figure 7).

At a significance level of $\alpha$ = 0.05, the Pearson correlation coefficient between P. oocarpa damaged by the bark beetle and the estimated affected level was 0.44 (p value = 0.02), which indicates that the model used is adequate. The spatial distribution of the bark beetle showed a higher incidence of damage in the east exposure of the diagnosed area (Figure 8).

At a significance level of $\alpha$ = 0.05, the Pearson correlation coefficient between Pinus pseudostrobus damaged by the bark beetle and the estimated affected level was 0.889 (p value < 0), which indicates that the model used is adequate. The spatial distribution of the bark beetle showed a higher incidence of damage in the center of the diagnosed area (Figure 9).

4.3. Bark Beetle Damage, 2021

For the year 2021, 48 virulent outbreaks were observed in the diagnosed area of the Tixtlancingo ejido. The areas of these patches are smaller compared to the areas of the 2020 patches (Figure 10). In this year, the forest area in Tixtlancingo was also 8657.26 hectares, of which 60.057 were affected, that is, only 0.7% of the forest area was damaged by the bark beetle. This translates into a total volume affected of 726.214 ${\mathrm{m}}^3$ t.t.v.

In the species P. maximinoi, the outbreaks most affected by the bark beetle are those located to the north of the diagnosed area (Figure 11); some of these outbreaks had up to 300 trees affected. For the species P. oocarpa, the most affected outbreaks are those located in the east and southeastern exposure of the diagnosed area (Figure 12). In this case, the number of outbreaks affected by the bark beetle is greater than that observed for P. maximinoi. Finally, for the species P. pseudostrobus, the most affected outbreaks are located to the south of the diagnosed area (Figure 13); there are outbreaks with up to 60 affected trees.

For the year 2021, the bark beetle has a greater preference for P. oocarpa pines located in the center of the diagnosed area, while to the north, there is a greater preference for P. maximinoi. Finally, in the southern exposure of the diagnosed area, the three species are less affected (Figure 14).

Pearson’s correlation coefficient indicates that the species P. maximinoi and P. pseudostrobus are not correlated (r = 0.15, p-value = 0.3), nor is there any correlation between the species P. oocarpa and P. pseudostrobus (r = 0.08, p-value = 0.58). There is only a significant negative correlation between P. oocarpa and P. maximinoi (r = −0.3, p-value = 0.036), which means that, if the damage to one of these two species increases, the damage to the other species decreases.

Spatial Interpolation

At a significance level of $\alpha =0.05$, the Pearson correlation coefficient between P. maximinoi damaged by the bark beetle and the estimated affected level was 0.60 (p value < 0), which indicates that the model used is adequate. The spatial distribution of the bark beetle showed a higher incidence of damage in the periphery of the diagnosed area (Figure 15).

At a significance level of $\alpha$ = 0.05, the Pearson correlation coefficient between P. oocarpa damaged by the bark beetle and the estimated affected level was 0.76 (p value < 0), which indicates that the model used is adequate. For this year, the distribution shows that bark beetle damage to P. oocarpa occurred in most of the diagnosed area (Figure 16).

At a significance level of $\alpha$ = 0.05, the Pearson correlation coefficient between P. pseudostrobus damaged by the bark beetle and the estimated affected level was 0.687 (p value < 0), which indicates that the model used is adequate. For this year, the distribution shows that bark beetle damage to P. pseudostrobus occurred southeast of the diagnosed area (Figure 17).

From spatial interpolation, we can say that bark beetle damage in the three pine species is not the same. Generally, damage that starts at one site (point) begins to spread.

4.4. Comparison

According to the following results, the damage caused by the bark beetle to three pine species was lower in 2021 compared to 2020; see

Table 4. Trees and volume affected for the three species in the Diagnosis by years 2020 and 2021.

Ejido Tixtlancingo		Diagnostic 2020	Diagnostic 2021
Outbreaks presented		28	48
Affected surface (ha)		1057.64	60.057
Affected trees	P. maximinoi	40,484	1537
	P. oocarpa	36,159	2680
	P. pseudostrobus	13,906	312
Affected volume (${\mathrm{m}}^3$ t.t.v.)	P. maximinoi	5735.339	194.116
	P. oocarpa	6320.707	510.505
	P. pseudostrobus	1441.54	21.593

. Although the number of outbreaks identified in 2021 was 48, these did not represent large damages for the diagnosed area because the pests attacked areas with smaller polygons; see

Table 5. CD (diametric categories), TTA (total number of trees affected) and TVA (total volume affected) by bark beetle according to diameter categories, 2020 and 2021.

CD	TTA 2020	TVA 2020	TTA 2021	TVA 2021
5	21,327	715.578	872	30.135
10	25,603	797.770	1164	36.688
15	19,489	1474.452	973	67.993
20	7346	1042.056	371	45.924
25	5371	1271.337	281	57.046
30	5192	1971.889	272	85.615
35	1764	993.746	151	55.500
40	1197	861.229	138	61.714
45	1382	1414.892	131	85.359
50	1301	1610.640	113	109.167
55	206	341.814	33	38.259
60	223	493.336	12	13.934
65	19	51.014	-	-
70	50	162.925	10	20.309
75	44	153.981	4	8.522
80	35	140.927	4	10.049
Total	90,549	13,497.59	4529	726.214

.

The tree density of the stand influences the appearance of bark beetle outbreaks; pine stands with a higher density are more susceptible to attack because trees compete for space and nutrients [46,47]. Therefore, Martínez-Rincón [29] suggests that the density should not exceed the site’s capacity. Additionally, it has been documented that homogeneous and mature stands are more susceptible to attacks by D. mexicanus and D. frontalis [47].

For this study, greater impact was reported for P. maximinoi in 2020, followed by P. oocarpa, and in 2021, greater impact was found for P. oocarpa, followed by P. maximinoi (Figure 18). This is because there is a difference in the number of outbreaks, affected surface area, volume, and number of infested trees in the two years studied. This is consistent with a study by Vázquez [48], who reported that D. frontalis prefers to attack P. oocarpa trees, similar to findings by Salinas [3], who demonstrated that D. frontalis is more associated with P. oocarpa than with P. maximinoi. Although D. frontalis also attacks P. maximinoi, the number of affected trees is lower.

Parameterized by volume, the most impacted diameter categories were 30 cm (1971.889 t.t.v.) and 50 cm (109.167 t.t.v.) for 2020 and 2021, respectively. However, the results of this study demonstrate that the behavior pattern in the study area has been disrupted since, for P. oocarpa, P. maximinoi, and P. pseudostrobus, the number of affected trees was higher in diameter categories less than 20 cm, with a greater impact in 2020 than in 2021 (Figure 19 and Figure 20), probably due to higher air temperature and solar radiation in the first year than in the second, which created drier environments and stressed trees, making them susceptible to bark beetle attacks.

In relation to volume, for 2020, P. oocarpa was the most affected species, followed by P. maximinoi; see Figure 21. The bark beetle attacked the 30 cm diameter category more (Figure 22). For the year 2021, P. oocarpa was also the most affected species, followed by P. maximinoi. In this year, the pest attacked the 50 cm diameter category more (Figure 23).

5. Discussion

In natural stands of Picea orientalis (L.) Peterm. in Turkey, no difference was found between shaded and sunny areas regarding the attack pattern of Dendroctonus micans Kugelann. However, forests with lower density (29%) were more susceptible to attack than were dense stands (16%). Conversely, mature (20%) and over-mature forests (30%) were more susceptible to attack by this bark beetle than young forests were [49]. Additionally, the physical characteristics of trees, particularly their spacing, health, maturity, social position, and diameter, influence bark beetle population dynamics, as demonstrated by research on Pinus contorta Douglas and Dendroctonus ponderosae Hopkins: trees in dense populations have thinner phloem than trees growing in more open environments. The larger the tree diameter, the higher the number of insects attacking the trees [50]. This is very similar to a study on the quantity of bark beetles by Vázquez [48], who determined that, the larger the diameter, the greater the number of pupae and adults present in the trunk of P. oocarpa at a height of 0 to 6 m. This is consistent with the Diagnosis by years 2020 and 2021 in the Tixtlancingo ejido, where a preference for attacking trees with diameter categories of 30 cm for 2020 and 50 cm for 2021 was observed, similar to that reported by Endara-Agramont [26].

The bark beetle D. adjunctus is a parasitic species that affects Pinus hartwegii Lindl. forests in Mexico. Its populations are increasing, posing a threat to this pine species. A study determined the spatial distribution of D. adjunctus in two protected natural areas in central Mexico. It was found that 19% of the sampled sites were infested by the bark beetle at altitudes ranging from 3600 to 3900 m and diameter categories of 30 to 55 cm. The spatial distribution of the bark beetles is influenced by factors such as exposure, altitude, slope, and simultaneous presence with dwarf mistletoes (Arceuthobium spp.) [26].

Regarding the impact of fire, it is known that water stress can affect forest susceptibility to bark beetle attacks. In addition, high temperatures directly favor the development of these insects [26]. However, more specific research is needed to fully understand how fire affects Dendroctonus bark beetles spatial distribution.

Bark beetles have a biological interaction with pine trees: they contribute to nutrient recycling, crown thinning, gap dynamics, biodiversity, soil structure, hydrology, disturbance regimes, succession patterns, and species distribution within pine forests [47]. However, when they experience population fluctuations, they cause the loss of forest ecosystems. They bore and dig galleries, reaching the cambium layer, leading to the death of healthy trees by overcoming their defenses, causing profound ecological changes such as shifts in species composition, changes in forest age structure, and alterations in woody fuel loads and even in the global carbon balance [51]. Observations documented by Cervantes-Martínez [52] for regions in Mexico, Guatemala, and Honduras indicate that dry periods (p < 0.05) predispose trees to weakening, becoming more susceptible to bark beetle attacks. This climatic condition negatively influences resin production in pines, a primary defense mechanism against bark beetles.

Climate plays a significant role in the natural distribution of Dendroctonus. Extreme temperatures and thermal variation influence the activity, development, and distribution of bark beetles. For instance, high temperatures can directly favor their development [13]. With D. mexicanus, it has been observed that relative humidity affects the coloration of their exoskeleton. In more humid areas, individuals tend to be darker, whereas in dry zones, they are lighter [13]. Optimal climatic conditions for abundant populations of D. mexicanus are associated with average maximum and minimum aridity indices [53]. The spatial distribution of the bark beetle is determined by climate variability, generating favorable conditions for its physiology, movement, preferences, and tree conditions or availability [50]. Precipitation is a variable that modifies bark beetle population dynamics. For example, for D. mexicanus [54], precipitation was the most important variable. Similarly, Cuéllar-Rodríguez [55] confirmed that this variable is a factor modifying population dynamics (in that increased precipitation reduces bark beetle capture). This may be related to reduced flight capacity and host-searching by the insect [55], in addition to increased tree defenses and resin production. Outbreaks of pine forest infestation by D. mexicanus are influenced by temperature and humidity; as Pérez-Miranda [25] found during the period 2009–2018, 50.0% of bark beetle attacks were concentrated in the years 2012 (August–December), 2013 (January–May), and 2014 (February–July), observing during this period peaks of variable temporary attack behavior attributed to lack of rain and high temperatures, mainly in northern Mexico. This situation occurred in 2020 and 2021 in the study area between May and June, suggesting the need to continued monitoring of meteorological data and pest behavior to generate a predictive model of the potential distribution of bark beetles in pine forests in Guerrero, Mexico, in the short and medium term.

The diagnosed area presents altitudes ranging from 1700 to 2200 m a.s.l., with 15% to 35% slope. This altitude is consistent with the work of Cuéllar-Rodríguez [5], who found that D. mexicanus attacks occurred in the altitudinal interval from 1900 to 3260 m a.s.l. They also found that most of the infestations started on the tops and upper parts of the slopes, areas characterized by denser forests than in the lower parts. In addition, the slope has a determining role in the amount of solar energy that reaches the environmental system and affects the physiological processes of the plants by altering their defense capacity. On the other hand, Wermelinger [56], Raffa [57], and Six [58] found that decreases in precipitation and humidity have a direct relationship with the defense capacity of trees, while Raffa [59] suggests a dependence of insects on temperature.

From the spatial analysis, it was observed that, depending on the pine species, the damage caused by the bark beetle changes its spatial pattern in two ways: in general, it begins to disperse throughout the study area, and also the distribution of the bark beetle obeys the distribution of its hosts; this agrees with what was established by Grego [60], Ifoulis and Savopoulou-Soultani [61], and Bressan [62], who established that insect populations are generally spatially aggregated. On the other hand, the spatial Poisson processes were able to identify the sites most affected by the bark beetle, a method consistent with that of Lara [63], who obtained the fluctuation and spatial distribution of Ocoaxo near Fowleri (Hemiptera: Cercopidae) in conifers of the northern highlands of Puebla using geostatistics for this spatial model. This is useful for efficient containment of the pest, directing control measures to specific areas where the damage occurs.

The spatial distribution pattern of the bark beetle, as in other insects, is influenced by several environmental factors, such as altitude, that affect its distribution patterns and diversity. In this sense, soil properties are also considered, and soil temperature influences it. The different altitude gradients are correlated with temperature and humidity [64,65,66,67].

The procedure for implementing sanitation measures can take quite some time, so from the moment the pest is detected until sanitation actions are carried out, many things can happen considering the life cycle of these insects. Therefore, technical, economic, and social aspects are fundamental for forest health.

6. Conclusions

We detected 76 outbreaks affecting an area of 1117.697 ha, 95,078 trees, and a volume of 14,223.8 ${\mathrm{m}}^3$ t.t.v.

The preference of the bark beetle for attacking trees with diameter categories of 10 cm and, in terms of volume, diameter categories of 30 and 50 cm, was observed for the three pine species found in the study area, with 1971.889 and 109.167 ${\mathrm{m}}^3$ t.t.v., respectively.

The pattern of behavior in the study area has been altered since, for P. oocarpa, P. maximinoi, and P. pseudostrobus, the number of affected trees was higher in diameter categories less than 20 cm, with greater impact in 2020 than in 2021. The distributions of the spatial model show the areas where the pest was present with eastern exposure for 2020 (the damage for P. oocarpa was less dispersed) and northeast and south for 2021, where the bark beetle had a greater preference for P. oocarpa in the center of the diagnosed area. On the other hand, to the north, the greatest preference was for P. maximinoi, while in the southern exposure, the three species were less affected.

The spatial distribution models allowed us to visualize the Dentroctonus movements and the possibility of natural or chemical control in accordance with NOM 019 SEMARNAT [32]. The most affected trees were P. oocarpa (east and southeast) and P. maximinoi (north), as well as P. pseudostrobus in the south exposure.

The monitoring period for the pest was short (2020–2021) due to the low budget allocated for this purpose, as it is a poor region in Mexico; however, the results of these approaches give an idea of the spatial pest behavior and the effects that it can cause in the face of climate change. The behavior of insects becomes different after extreme natural phenomena, as in the case of hurricane Otis, which drastically modified the climate. Therefore, it is considered necessary to continue monitoring for a better understanding of the pest–host dynamics.