<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd"><article xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.3"><front><journal-meta><journal-id journal-id-type="issn">2089-0257</journal-id><journal-title-group><journal-title>Jurnal Entomologi Indonesia</journal-title><abbrev-journal-title>J Entomol Indones</abbrev-journal-title></journal-title-group><issn pub-type="epub">2089-0257</issn><issn pub-type="ppub">1829-7722</issn><publisher><publisher-name>Perhimpunan Entomologi Indonesia</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.5994/jei.22.2.105</article-id><title-group><article-title>Local factors dominantly influence citrus red mite (<italic>Panonychus citri</italic> (McGregor)) population over landscape factors in Indonesian citrus orchards</article-title><subtitle>Faktor lokal lebih dominan mempengaruhi populasi tungau merah jeruk (<italic>Panonychus citri</italic> (McGregor)) daripada faktor lanskap pada pertanaman jeruk di Indonesia</subtitle></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0004-8702-6736</contrib-id><name><surname>Salamah</surname><given-names>Luklu Is</given-names></name><address><country>Indonesia</country><email>lukluissalamah@student.ub.ac.id</email></address><xref ref-type="aff" rid="AFF-1"></xref><xref ref-type="corresp" rid="cor-0"></xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6673-6198</contrib-id><name><surname>Rizali</surname><given-names>Akhmad</given-names></name><address><country>Indonesia</country><email>arizali@ub.ac.id</email></address><xref ref-type="aff" rid="AFF-2"></xref><xref ref-type="corresp" rid="cor-1"></xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9315-1849</contrib-id><name><surname>Puspitarini</surname><given-names>Retno Dyah</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-2"></xref></contrib></contrib-group><contrib-group><contrib contrib-type="editor"><name><surname>Shahabuddin</surname><given-names>Shahabuddin</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="EDITOR-AFF-1"></xref></contrib></contrib-group><aff id="AFF-1"><institution content-type="dept">Program Studi Entomologi Pertanian, Fakultas Pertanian</institution><institution-wrap><institution>Universitas Brawijaya</institution><institution-id institution-id-type="ror">https://ror.org/01wk3d929</institution-id></institution-wrap><addr-line>Jalan Veteran, Malang 65145</addr-line><country country="ID">Indonesia</country></aff><aff id="AFF-2"><institution content-type="dept">Departemen Hama dan Penyakit Tumbuhan, Fakultas Pertanian</institution><institution-wrap><institution>Universitas Brawijaya</institution><institution-id institution-id-type="ror">https://ror.org/01wk3d929</institution-id></institution-wrap><addr-line>Jalan Veteran, Kota Malang 65145, Jawa Timur</addr-line><country country="ID">Indonesia</country></aff><aff id="EDITOR-AFF-1"><institution content-type="dept">Program Studi Agroteknologi, Fakultas Pertanian</institution><institution-wrap><institution>Universitas Tadulako</institution><institution-id institution-id-type="ror">https://ror.org/01z0mc198</institution-id></institution-wrap><country country="ID">Palu</country></aff><author-notes><corresp id="cor-0">Corresponding author: Luklu Is Salamah, Program Studi Entomologi Pertanian, Fakultas Pertanian, Universitas Brawijaya, Jalan Veteran, Malang 65145, Indonesia.  Email: <email>lukluissalamah@student.ub.ac.id</email></corresp><corresp id="cor-1">Corresponding author: Akhmad  Rizali, Departemen Hama dan Penyakit Tumbuhan, Fakultas Pertanian, Universitas Brawijaya, Jalan Veteran, Kota Malang 65145, Jawa Timur, Indonesia.  Email: <email>arizali@ub.ac.id</email></corresp></author-notes><pub-date date-type="pub" iso-8601-date="2025-10-25" publication-format="electronic"><day>25</day><month>10</month><year>2025</year></pub-date><pub-date date-type="collection" iso-8601-date="2025-9-19" publication-format="electronic"><day>19</day><month>9</month><year>2025</year></pub-date><volume>22</volume><issue>2</issue><issue-title>July</issue-title><fpage>105</fpage><lpage>113</lpage><history><date date-type="received" iso-8601-date="2025-5-16"><day>16</day><month>5</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2025-10-1"><day>1</day><month>10</month><year>2025</year></date></history><permissions><copyright-statement>Copyright (c) 2025 Luklu Is Salamah, Akhmad  Rizali, Retno Dyah Puspitarini</copyright-statement><copyright-year>2025</copyright-year><copyright-holder>Luklu Is Salamah, Akhmad  Rizali, Retno Dyah Puspitarini</copyright-holder><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This work is licensed under a Creative Commons Attribution 4.0 International License.Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).</license-p></license></permissions><self-uri xlink:href="https://jurnal.pei-pusat.org/index.php/jei/article/view/933" xlink:title="Local factors dominantly influence citrus red mite (Panonychus citri (McGregor)) population over landscape factors in Indonesian citrus orchards">Local factors dominantly influence citrus red mite (Panonychus citri (McGregor)) population over landscape factors in Indonesian citrus orchards</self-uri><abstract><p>The citrus red mite <italic>Panonychus citri </italic>(McGregor) is a major pest that can reduce the quality and yield of citrus crops. However, information regarding the local and landscape factors that influence its population dynamics remains limited. This study aimed to analyse the influence of local and landscape factors on citrus red mite population density. The research was conducted in nine citrus orchards in Malang, East Java, Indonesia. Data collected included local factors (pesticide application frequency and plant canopy density) and landscape factors (landscape composition, encompassing the number of patches (NP) and class area (CA) of semi-natural habitats). Pesticide application frequency data were obtained through farmer interviews, while canopy density was measured using a photographic method and analysed with ImageJ2 software. Landscape composition data were by digitizing land-use types within a 500-meter radius of the plot center using QGIS software and subsequently analysed using LecoS (QGIS add-ins) to obtain the NP and CA of semi-natural habitats. The generalized linear  model (GLM) analysis indicated no overall significant influence of both local and landscape factors on <italic>P. citri</italic> population density. However, it was found that the variation in mite population density was significantly influenced by citrus plant canopy density. These findings suggest that local factors, particularly the canopy microhabitat conditions, are more critical in affecting the <italic>P. citri</italic> population compared to landscape factors. Therefore, the management strategy for citrus red mite should be focused on the local, on-farm scale.</p></abstract><kwd-group><kwd>canopy density</kwd><kwd>landscape composition</kwd><kwd>pest management</kwd><kwd>population density</kwd><kwd>spatial variation</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>File created by JATS Editor</meta-name><meta-value><ext-link ext-link-type="uri" xlink:href="https://jatseditor.com" xlink:title="JATS Editor">JATS Editor</ext-link></meta-value></custom-meta><custom-meta><meta-name>issue-created-year</meta-name><meta-value>2025</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec><title>INTRODUCTION</title><p>Citrus crops are of significant economic value in Indonesia, with production reaching 2.8 million tons in 2023, primarily led by East Java <xref ref-type="bibr" rid="BIBR-9">(Central Bureau of Statistics of Indonesia, 2024)</xref>. Citrus orchards not only provide substantial benefits to farmers but also bolster both local and national markets <xref ref-type="bibr" rid="BIBR-26">(Lv et al., 2015)</xref>; <xref ref-type="bibr" rid="BIBR-20">(Hidayat et al., 2022)</xref>. Despite this importance, production is frequently threatened by pests and diseases. These biological threats attack plants from flowering to harvest, leading to heavy losses and significantly reducing fruit quality <xref ref-type="bibr" rid="BIBR-24">(Kilcher, 2005)</xref>; <xref ref-type="bibr" rid="BIBR-2">(Abobatta, 2018)</xref>. For instance, recent study in Langkat, North Sumatra, have identified 16 insect families as major pests in citrus orchards <xref ref-type="bibr" rid="BIBR-25">(Kurniawan &amp; Siregar, 2023)</xref>.</p><p>Mites pose a significant threat to citrus production, potentially reducing fruit yields by as much as 70% by cause brown skin discoloration, rough skin, and stunted fruit growth <xref ref-type="bibr" rid="BIBR-16">(Ebrahim &amp; Aiad, 2019)</xref>; <xref ref-type="bibr" rid="BIBR-52">(Wicaksono et al., 2022)</xref>. Specifically, the citrus red mite <italic>Panonychus</italic><italic>citri </italic>(McGregor) (Tetranychidae) is a polyphagous species known to infest various food crops, trees, and ornamental plants <xref ref-type="bibr" rid="BIBR-21">(Hoy, 2011)</xref>. <italic>P. citri</italic> is recognized as a major economic pest in citrus orchards globally, including regions across Asia, the Mediterranean Basin, North America, South America, and Africa <xref ref-type="bibr" rid="BIBR-49">(Urbaneja et al., 2020)</xref>. Due to its adaptability, this mite can infest virtually all citrus varieties and species.</p><p>Severe <italic>P. citri</italic> infestations primarily impact citrus productivity and quality. The direct feeding damage prevents normal fruit development, leading to fruit drop, although remaining fruits may partially compensate by gaining weight, the overall effect is still a significant (~10%) reduction in yield <xref ref-type="bibr" rid="BIBR-17">(Faez et al., 2018)</xref>. Physiologically, mites damage the plant by sucking cytoplasm from plant cells, which causes chlorotic (yellow) spots and can trigger premature leaf fall <xref ref-type="bibr" rid="BIBR-11">(Demard &amp; Qureshi, 2022)</xref>. This loss of cytoplasmic contents reduces chlorophyll levels and photosynthesis, further impairing tree health and potentially degrading fruit quality <xref ref-type="bibr" rid="BIBR-3">(Afzal et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-7">(Assouguem et al., 2024)</xref>. Beyond agronomic losses,<italic> P. citri</italic> imposes substantial economic burdens. Infestation necessitates increased production costs, primarily through the need for more frequent acaricide applications and the implementation of integrated pest management (IPM) strategies. Furthermore, the external defects and poor quality resulting from major infestations severely reduce the marketability of fruits, negatively affecting both domestic and international commercial sectors <xref ref-type="bibr" rid="BIBR-17">(Faez et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-41">(Radonjić &amp; Hrnčić, 2020)</xref>.</p><p>To develop effective and sustainable control strategies for mites, it is essential to study their density and distribution in citrus orchards, requiring and integrated understanding of both local (field) and landscape factors <xref ref-type="bibr" rid="BIBR-44">(Rizali et al., 2024)</xref>. Local factors, such as canopy density and pesticide application, directly influence pests and natural enemy presence. Canopy density affects the light penetration, which in turn dictates crucial microclimatic conditions like temperature and humidity <xref ref-type="bibr" rid="BIBR-14">(Devi &amp; Challa, 2019)</xref>; <xref ref-type="bibr" rid="BIBR-54">(Zhang et al., 2019)</xref>. The significance of temperature is evident since <italic>P. citri</italic> can complete its life cycle in approximately one week at 25 °C, and its population often peaks during favorable temperatures periods in early spring or fall <xref ref-type="bibr" rid="BIBR-55">(Zhang, 2003)</xref>; <xref ref-type="bibr" rid="BIBR-12">(Demard &amp; Qureshi, 2023)</xref>. Conversely, nonoptimal temperatures and humidity levels typically lead to a decline in arthropod populations (Shrestha 2019). Furthermore, frequent pesticide applications disrupts natural biological systems, induces pest resistance, and can ultimately lead to a resurgence or increase in pest population over time <xref ref-type="bibr" rid="BIBR-43">(Rattanpal et al., 2017)</xref>; <xref ref-type="bibr" rid="BIBR-49">(Urbaneja et al., 2020)</xref>; <xref ref-type="bibr" rid="BIBR-3">(Afzal et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-13">(Demard et al., 2024)</xref>.</p><p>Landscape factors, particularly landscape composition, also play a crucial role by influencing fauna diversity and population density. Croplands situated near natural habitats generally exhibit greater natural enemy diversity and species richness <xref ref-type="bibr" rid="BIBR-33">(Pasaribu et al., 2024)</xref>, while complex landscapes support more abundant and diverse natural enemies that indirectly regulate pest populations <xref ref-type="bibr" rid="BIBR-27">(Martin et al., 2016)</xref>. For example, the presence of natural habitats within oil palm plantations affects the species richness and abundance of natural enemies <xref ref-type="bibr" rid="BIBR-44">(Rizali et al., 2024)</xref>. Similarly, semi-natural habitats can acts as dispersal or refuge sites for predatory mites (Phytoseiidae) in vineyards, suggesting that the lack of such habitats may contribute to a decrease in their population <xref rid="BIBR-31" ref-type="bibr">(Möth et al., 2023)</xref>.</p><p>While numerous studies have thoroughly examined the basic biology and ecology of <italic>P. citri</italic><xref ref-type="bibr" rid="BIBR-23">(Kasap, 2009)</xref>; <xref ref-type="bibr" rid="BIBR-53">(Zanardi et al., 2015)</xref>; <xref ref-type="bibr" rid="BIBR-11">(Demard &amp; Qureshi, 2022)</xref>, research focusing on how local and landscape factors concurrently influence its population density and spatial variation in citrus orchards remains limited. Most existing research has highlighted the direct effects of pesticides on mites <xref ref-type="bibr" rid="BIBR-4">(Amiri-Besheli et al., 2020)</xref>, but rarely incorporates landscape variables, such as landscape composition, into integrated mite management strategies <xref ref-type="bibr" rid="BIBR-31">(Möth et al., 2023)</xref>. Specifically, studies investigating how the interplay of factors like canopy density, pesticide application, and landscape composition, collectively shape <italic>P. citri</italic> population are scarce. Therefore, this study aimed to investigate the effects of local factors (i.e., frequency of pesticide application and canopy density) and landscape factors (i.e., landscape composition) on the population density and spatial variation of <italic>P. citri</italic> in Indonesian citrus orchards.</p></sec><sec><title>MATERIALS AND METHODS </title><sec><title>Study area and plot design</title><p>This study was conducted in nine citrus orchards across three districts: Dau, Bumiaji, and Poncokusumo, in Malang, East Java, Indonesia. The orchards were selected based on criteria adapted from <xref ref-type="bibr" rid="BIBR-52">(Wicaksono et al., 2022)</xref>, ensuring all sites had producing citrus trees aged of 2–7 years, a minimum area of 1,200 m<sup>2</sup>, and were separated by a distance at least 1 km but no more than 20 km. These nine orchards were distributed across nine villages (<xref ref-type="fig" rid="figure-1">Figure 1</xref>A), with elevations ranging from 578 to 994 m above sea level. The region features a tropical wet climate, with an average air temperature of 26.25 °C and relative humidity of 75.5% (Meteorology, Climatology, and Geophysical Agency 2024). All orchards cultivated the same citrus variety, <italic>Citrus nobilis</italic> L., at an average planting distance was 3 m × 3 m. Furthermore, farm management practices were consistent across sites: farmers used mixed fertilizers (organic and inorganic), applied chemical pesticides, and performed annual pruning (typically one to three times per year).</p><p>For the purpose of the study, a 900 m<sup>2</sup> (30 m × 30 m) plot consisting of 81 plants was established in each orchard (<xref ref-type="fig" rid="figure-1">Figure 1</xref>B). This central placement was chosen to minimize border and edge effects and covered approximately 75% of the area of the smallest selected orchards.</p></sec><sec><title>Local factor data collection</title><p>Local or field data collection focused on pesticide application frequency and citrus canopy cover. Data on pesticide application frequency, types, and methods were gathered through interviews with the citrus orchard owners. The owners reported an average application frequency of one to four times per month. The pesticides used, including fungicides, insecticides, and acaricides, were consistently applied by direct spraying. Citrus canopy cover (canopy density) was measured using a photographic method. In each orchard, five representative locations were selected, with each point representing a subplot of four citrus trees. Photographs were taken from the ground toward the canopy using a camera positioned 30 cm above the ground. The resulting images were subsequently processed using ImageJ2 software to determine the percentage of canopy density. This value was calculated as the average of the measurements taken at the five photographic points <xref ref-type="bibr" rid="BIBR-45">(Rueden et al., 2017)</xref>; <xref ref-type="bibr" rid="BIBR-32">(Muhammad et al., 2022)</xref>.</p><fig id="figure-1" ignoredToc=""><label>Figure 1</label><caption><p>A: Study area research citrus orchards in Malang, East Java, Indonesia. O1: Bulukerto; O2: Bumiaji; O3: Pandanrejo; O4: Gadingkulon; O5: Tegalweru; O6: Selorejo; O7: Karangnongko; O8: Wonorejo; O9: Ngebruk. B: results of landscape digitization in one of the study orchards; C: observation plots; D: layout of the four sample leaves (view from above) in the canopy of each sample citrus plant.</p></caption><graphic xlink:href="https://jurnal.pei-pusat.org/index.php/jei/article/download/933/632/8563" mime-subtype="png" mimetype="image"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>Landscape characterization</title><p>We characterized the landscape surrounding each citrus orchard within a 500 m radius. This radius was selected based on previous studies indicating its suitability for observing interactions between arthropods and their habitats, as it often encompasses the relevant spatial range for natural enemies and other arthropods <xref ref-type="bibr" rid="BIBR-31">(Möth et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-33">(Pasaribu et al., 2024)</xref>. Landscape characterization was performed using ground checks with Google Earth as the base map. We recorded land use types and classified them into six distinct categories: (i) semi-natural habitats: areas with natural characteristics and minimal human intervention, including secondary forests, savannas, and grasslands <xref ref-type="bibr" rid="BIBR-18">(Guo et al., 2022)</xref>, (ii) citrus orchards: commercial or small-scale plantations of citrus trees (<italic>Citrus </italic>spp.) <xref ref-type="bibr" rid="BIBR-34">(Pilon et al., 2023)</xref>, (iii) annual cropland: areas planted with annual crops, such as vegetables, at least once within a 12-month period <xref ref-type="bibr" rid="BIBR-10">(Defourny et al., 2014)</xref>, (iv) farms: places where livestock are bred and raised for ecological benefit, (v) open areas: areas without vegetation cover, and (vi) settlements: areas used for human habitats, including towns and villages <xref ref-type="bibr" rid="BIBR-19">(Harrison, 2006)</xref> (<xref rid="figure-2" ref-type="fig">Figure 2</xref>). Each landscape within the defined radius was digitized using QGIS software <xref ref-type="bibr" rid="BIBR-38">(Team, 2024)</xref>. We analysed the landscape composition using the Landscape Ecology Statistics (LecoS) plugin <xref ref-type="bibr" rid="BIBR-22">(Jung, 2013)</xref> to obtain two key landscape parameters for each land use type: class area (CA), defined as the area (in hectares) of a particular habitat category, and the number of patches (NP) of seminatural habitats.</p></sec><sec><title>Sampling of mites</title><p>To capture seasonal variations in population density, <italic>P. citri</italic> sampling was conducted twice: in the first week of November 2023 and the first week of December 2023. Both sampling events were performed either before or after pesticide application. We consistently sampled young leaves, as <italic>P. citri</italic> shows a clear preference for them. To account for potential microclimatic differences within the canopy <xref ref-type="bibr" rid="BIBR-36">(Puspitarini &amp; Endarto, 2021)</xref>; <xref ref-type="bibr" rid="BIBR-39">(Qureshi et al., 2021)</xref>. We collected four leaf samples from each sample tree at an approximate height of 2 m above ground level, one leaf from each cardinal direction (east, north, west, and south). In total, 36 citrus leaves were collected from the sample plants in each orchard. All leaves were carefully cut and placed in labelled plastic bags to prevent mite loss during transport. The bags were then stored in an ice box and refrigerated to keep the leaves fresh and immobilize the mites before counting.</p><p>The mite population was counted immediately upon return using a stereomicroscope. To prepare for identification, slides were created from the collected samples. After two to three days, when the mite bodies were clearly visible, identification was performed using a compound microscope. Mites were identified by examining their morphology to confirm they matched <italic>P. citri</italic>, as described in Zhang’s book Mites of Greenhouses: Identification, Biology, and Control. Finally, the average and coefficient of variation (CV) of <italic>P. citri</italic> per orchard were calculated.</p></sec><sec><title>Data analysis</title><p>We analysed the effects of landscape composition and local factors on the mean population density and spatial variation of<italic> P. citri</italic>. The mean population density and the spatial variation, represented by the coefficient of variation (CV), were calculated for <italic>P. citri</italic> per orchard. To model the relationship, we used a generalized linear model (GLM) without interaction terms. A quasi-Poisson distribution was employed to account for potential overdispersion in the count data <xref ref-type="bibr" rid="BIBR-8">(Bolker et al., 2009)</xref>; <xref rid="BIBR-57" ref-type="bibr">(Zuur et al., 2009)</xref>. The explanatory variables included both landscape and local factors: (i) landscape factors: class area (<italic>CA.nat</italic>) and number of patches (<italic>NP.nat</italic>) of semi-natural habitats, and (ii) local factors: frequency of pesticide application and percentage of canopy cover (canopy density). To prevent multicollinearity issues, all explanatory variables were checked for correlation using the variance inflation factor (VIF) test. All statistical analyses were conducted using R statistical software <xref ref-type="bibr" rid="BIBR-40">(Team, 2024)</xref>.</p></sec></sec><sec><title>RESULT</title><sec><title>Population density and spatial variation of <italic>P. citri</italic> in citrus orchards</title><p>The observed <italic>P. citri</italic> population density varied across the surveyed citrus orchards, ranging from 6.25 to 13.27 mites per four leaves sampled from a tree (<xref ref-type="fig" rid="figure-3">Figure 3</xref>). Significant spatial variation in population density was also evident among the trees within each plot (<xref ref-type="fig" rid="figure-3">Figure 3</xref>). Based on the coefficient of variation (CV), the population density in Pandanrejo Village exhibited the highest spatial variation (CV = 49.62%). This finding indicates a highly heterogeneous distribution of the <italic>P. citri</italic> population among the trees in that orchard compared to others. Conversely, the population density in Bulukerto Village was the most homogeneous (CV = 29.08%), suggesting a relatively even distribution of mites among the trees.</p></sec><sec><title>Effect of local and landscape on <italic>P. citri</italic> population density in citrus orchards</title><p>We hypothesized that both local factors (pesticide application and canopy cover) and landscape composition would influence the population density of citrus mites in the orchards. Landscape characterization revealed that all nine study orchards included seminatural habitats, though the proportion varied across sites (<xref ref-type="fig" rid="figure-2">Figure 2</xref>; <xref rid="table-1" ref-type="table">Table 1</xref>). Based on the LecoS analysis, the key landscape factors, the number of patches (NP) and class area (CA) of semi-natural habitats, ranged from 2–15 patches and 1.50–16.65 ha, respectively (<xref ref-type="table" rid="table-1">Table 1</xref>). Local factors also exhibited high variation. The frequency of pesticide application across the study sites ranged from one to four times per month (<xref ref-type="table" rid="table-1">Table 1</xref>). Similarly, canopy cover (canopy density) varied substantially, ranging from a minimum of 6% in Karangnongko to a maximum of 83% in Bumiaji (<xref ref-type="table" rid="table-1">Table 1</xref>).</p><p>The generalized linear model (GLM) analysis showed that neither the landscape factors (<italic>NP.nat</italic> and <italic>CA.nat</italic>) nor the local factors (pesticide application frequency and canopy density) significantly affected the mean density of the <italic>P. citri</italic> population (<xref ref-type="table" rid="table-2">Table 2</xref>, P &gt; 0.05). This suggests that variations in both landscape composition and these local management practices do not significantly influence the mean <italic>P. citri</italic> density. In contrast to population density, the GLM analysis revealed that a local factor, canopy density, had a significant positive effect on the spatial variation of the <italic>P. citri</italic> population (<xref ref-type="table" rid="table-2">Table 2</xref>, P = 0.039). This result indicates that increased canopy density leads to greater spatial variation (heterogeneity) in the <italic>P. citri</italic> population within citrus orchards. Conversely, the analysis found that the landscape factors (<italic>NP.nat</italic> and <italic>CA.nat</italic>) did not influence the spatial variation of the <italic>P. citri</italic> population (<xref ref-type="table" rid="table-2">Table 2</xref>, P &gt; 0.05).</p><fig id="figure-2" ignoredToc=""><label>Figure 2</label><caption><p>Landscape composition in the study area.</p></caption><graphic mimetype="image" xlink:href="https://jurnal.pei-pusat.org/index.php/jei/article/download/933/632/8564" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><fig id="figure-3" ignoredToc=""><label>Figure 3</label><caption><p>Average of spatial variation (CV) and average population density (per four leaves sampled tree) of <italic>Panonychus citri</italic> from 2 sampling in citrus orchards.</p></caption><graphic mime-subtype="png" mimetype="image" xlink:href="https://jurnal.pei-pusat.org/index.php/jei/article/download/933/632/8565"><alt-text>Image</alt-text></graphic></fig></sec></sec><sec><title>DISCUSSION</title><p>Our study demonstrated that local factors, particularly canopy density, exert a stronger influence on the spatial variation of <italic>P. citri</italic> populations than do landscape factors. Crucially, we found that neither local nor landscape factors significantly influenced the average population densities of the mites. The positive effect of canopy density on the spatial variation of <italic>P. citri</italic> suggests that denser canopies promote a heterogeneous (uneven) distribution of the mite population within an orchard. A higher coefficient of variation (CV) value confirms this greater unevenness in the mite’s spread between trees <xref ref-type="bibr" rid="BIBR-6">(Asriyanti, 2013)</xref>. This heterogeneity is likely driven by two key mechanisms facilitated by dense canopies: enhanced dispersal and aggregation and microclimate regulation. Connected canopies facilitate physical contact between leaves and branches, which is the primary mode of <italic>P. citri</italic> spread <xref ref-type="bibr" rid="BIBR-50">(Vashisth et al., 2021)</xref>. This movement, whether by walking, wind currents, or human activity, allows mites to rapidly aggregate in specific microhabitats that favour survival and reproduction. When the canopy is closed, mites tend to gather in such optimal spots, thereby increasing the unevenness of their distribution. In contrast, open canopies may lead to a more even spread or present physical barriers due to gaps between trees <xref ref-type="bibr" rid="BIBR-29">(Mockford et al., 2024)</xref>.</p><p>Canopy density significantly affects the microclimate by controlling sunlight exposure, which in turn influences temperature, humidity, and light <xref ref-type="bibr" rid="BIBR-14">(Devi &amp; Challa, 2019)</xref>; <xref ref-type="bibr" rid="BIBR-54">(Zhang et al., 2019)</xref>; <xref ref-type="bibr" rid="BIBR-1">(Abobatta, 2020)</xref>. Dense canopies maintain higher humidity, which prevents mite eggs and larvae from desiccating, and keep temperatures within the optimal 15–35 ºC range that supports <italic>P. citri</italic> development <xref ref-type="bibr" rid="BIBR-15">(Dong et al., 2020)</xref>. Open canopies, by allowing more sunlight and air circulation, create drier conditions that can increase mite mortality rates <xref ref-type="bibr" rid="BIBR-54">(Zhang et al., 2019)</xref>. Furthermore, dense canopies may offer complex habitats and protection for natural enemies, potentially increasing their survival and hunting efficiency <xref ref-type="bibr" rid="BIBR-35">(Prischmann et al., 2006)</xref>; <xref ref-type="bibr" rid="BIBR-1">(Abobatta, 2020)</xref>, which further contributes to localized mite suppression and, consequently, spatial variation.</p><table-wrap id="table-1" ignoredToc=""><label>Table 1</label><caption><p>Landscape and local factors in citrus orchards in Malang: number of patches (NP.nat) and class area (CA.nat) of semi-natural habitat, frequency of pesticide application (FPA), and canopy density (%)</p></caption><table rules="all" frame="box"><thead><tr><th colspan="1" rowspan="2" valign="middle" align="left">Orchards</th><th colspan="2" valign="top" align="center">Landscape factors</th><th valign="top" align="center" colspan="2">Local factors</th></tr><tr><th align="center" colspan="1" valign="top">CA. nat (ha)</th><th colspan="1" valign="top" align="center">NP. nat</th><th valign="top" align="center" colspan="1">FPA (times/ month)</th><th valign="top" align="center" colspan="1">Canopy density (%)</th></tr></thead><tbody><tr><td align="left" colspan="1" valign="top">Bulukerto</td><td valign="top" align="center" colspan="1">4.91</td><td align="center" colspan="1" valign="top">4</td><td valign="top" align="center" colspan="1">2</td><td valign="top" align="center" colspan="1">12.41</td></tr><tr><td valign="top" align="left" colspan="1">Bumiaji</td><td align="center" colspan="1" valign="top">13.44</td><td align="center" colspan="1" valign="top">15</td><td valign="top" align="center" colspan="1">4</td><td align="center" colspan="1" valign="top">83.16</td></tr><tr><td valign="top" align="left" colspan="1">Pandanrejo</td><td valign="top" align="center" colspan="1">9.78</td><td valign="top" align="center" colspan="1">6</td><td align="center" colspan="1" valign="top">4</td><td colspan="1" valign="top" align="center">68.43</td></tr><tr><td valign="top" align="left" colspan="1">Gadingkulon</td><td valign="top" align="center" colspan="1">4.58</td><td colspan="1" valign="top" align="center">2</td><td valign="top" align="center" colspan="1">2</td><td valign="top" align="center" colspan="1">14.49</td></tr><tr><td align="left" colspan="1" valign="top">Tegalweru</td><td colspan="1" valign="top" align="center">1.50</td><td align="center" colspan="1" valign="top">6</td><td valign="top" align="center" colspan="1">2</td><td align="center" colspan="1" valign="top">60.43</td></tr><tr><td align="left" colspan="1" valign="top">Selorejo</td><td align="center" colspan="1" valign="top">3.39</td><td align="center" colspan="1" valign="top">2</td><td align="center" colspan="1" valign="top">2</td><td colspan="1" valign="top" align="center">55.24</td></tr><tr><td align="left" colspan="1" valign="top">Karangnongko</td><td colspan="1" valign="top" align="center">12.25</td><td valign="top" align="center" colspan="1">3</td><td colspan="1" valign="top" align="center">2</td><td align="center" colspan="1" valign="top">6.15</td></tr><tr><td align="left" colspan="1" valign="top">Wonorejo</td><td align="center" colspan="1" valign="top">16.65</td><td valign="top" align="center" colspan="1">6</td><td valign="top" align="center" colspan="1">3</td><td align="center" colspan="1" valign="top">53.38</td></tr><tr><td valign="top" align="left" colspan="1">Ngebruk</td><td valign="top" align="center" colspan="1">4.32</td><td valign="top" align="center" colspan="1">2</td><td valign="top" align="center" colspan="1">1</td><td valign="top" align="center" colspan="1">27.22</td></tr></tbody></table></table-wrap><table-wrap id="table-2" ignoredToc=""><label>Table 2</label><caption><p>Generalized linear models (GLM) showing the relationship between the population density of <italic>Panonychus citri</italic> and the following variables:  number of patches (NP.nat) and class area (CA.nat) of semi-natural habitat, fre-quency of pesticide application (FPA), and canopy density (%)</p></caption><table frame="box" rules="all"><thead><tr><th align="left" colspan="1" rowspan="2" valign="middle">Variable</th><th valign="top" align="center" colspan="3">Mean of individuals</th><th valign="top" align="center" colspan="3">CV of individuals</th></tr><tr><th align="center" colspan="1" valign="top">Est</th><th colspan="1" valign="top" align="center">SE</th><th valign="top" align="center" colspan="1">P</th><th valign="top" align="center" colspan="1">Est</th><th valign="top" align="center" colspan="1">SE</th><th valign="top" align="center" colspan="1">P</th></tr></thead><tbody><tr><td align="left" colspan="1" valign="top">intercept</td><td valign="top" align="center" colspan="1">1.704</td><td valign="top" align="center" colspan="1">0.15</td><td valign="top" align="center" colspan="1">&lt;0.001</td><td align="center" colspan="1" valign="top">-1.263</td><td colspan="1" valign="top" align="center">0.17</td><td valign="top" align="center" colspan="1">&lt;0.001</td></tr><tr><td valign="top" align="left" colspan="1">NP.nat</td><td valign="top" align="center" colspan="1">0.025</td><td valign="top" align="center" colspan="1">0.02</td><td valign="top" align="center" colspan="1">0.291</td><td valign="top" align="center" colspan="1">-0.055</td><td valign="top" align="center" colspan="1">0.09</td><td align="center" colspan="1" valign="top">0.554</td></tr><tr><td valign="top" align="left" colspan="1">CA.nat</td><td valign="top" align="center" colspan="1">0.005</td><td colspan="1" valign="top" align="center">0.00</td><td align="center" colspan="1" valign="top">0.495</td><td valign="top" align="center" colspan="1">0.014</td><td align="center" colspan="1" valign="top">0.02</td><td align="center" colspan="1" valign="top">0.602</td></tr><tr><td align="left" colspan="1" valign="top">FPA</td><td align="center" colspan="1" valign="top">0.088</td><td align="center" colspan="1" valign="top">0.08</td><td valign="top" align="center" colspan="1">0.308</td><td align="center" colspan="1" valign="top">0.006</td><td align="center" colspan="1" valign="top">0.00</td><td align="center" colspan="1" valign="top">0.505</td></tr><tr><td align="left" colspan="1" valign="top">Canopy density</td><td valign="top" align="center" colspan="1">0.000</td><td align="center" colspan="1" valign="top">0.00</td><td valign="top" align="center" colspan="1">0.946</td><td align="center" colspan="1" valign="top">0.006</td><td align="center" colspan="1" valign="top">0.00</td><td align="center" colspan="1" valign="top">0.039*</td></tr></tbody></table><table-wrap-foot><p>*: P &lt; 0.05; Est: Estimate; SE: Std. Error; P: P value.</p></table-wrap-foot></table-wrap><p>Our finding that pesticide use did not affect the population density or spatial variation of <italic>P. citri</italic> mites suggests that the mite population remained relatively stable despite varying application frequencies. Based on farmer interviews, this lack of efficacy may be attributed to inappropriate application practices, such as mixing incompatible pesticides (e.g., fungicides and insecticides). Such misuse can reduce the effectiveness of the active ingredients and accelerate pest resistance <xref ref-type="bibr" rid="BIBR-5">(Asaad, 2008)</xref>; <xref ref-type="bibr" rid="BIBR-42">(Rahmasari &amp; Musfirah, 2020)</xref>. This highlights a critical lack of proper pesticide knowledge among local farmers. Promoting the correct use of pesticides (right target, quality, type, dose, time, and method) and encouraging the adoption of eco-friendly alternatives, such as black soap and detergent mixes <xref ref-type="bibr" rid="BIBR-4">(Amiri-Besheli et al., 2020)</xref>; <xref ref-type="bibr" rid="BIBR-7">(Assouguem et al., 2024)</xref>, are necessary steps to achieve effective pest control.</p><p>Although complex landscapes are generally expected to boost natural enemies and plant diversity, thereby affecting pest populations <xref ref-type="bibr" rid="BIBR-46">(Syahidah et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-56">(Zuhran et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-44">(Rizali et al., 2024)</xref>, the GLM analysis in this study found that landscape composition (number of patches and class area of semi-natural habitats) did not influence <italic>P. citri</italic> density or spatial variation. This suggests that the spread of <italic>P. citri</italic> is likely limited to the immediate local environment. While mites can spread by walking, human assistance, and wind (“ballooning”) <xref rid="BIBR-11" ref-type="bibr">(Demard &amp; Qureshi, 2022)</xref>; <xref ref-type="bibr" rid="BIBR-47">(Tehri, 2014)</xref>, this airborne dispersal method is generally considered limited to short distances <xref rid="BIBR-30" ref-type="bibr">(Montes &amp; Gleiser, 2025)</xref>. The short-term nature of this movement may prevent a strong landscape factors effect on the overall population or its spatial arrangement. Additionally, the inherent biological traits of <italic>P. citri</italic>, including its short life cycle, high reproductive rate, adaptability, and ability to utilize resources in its current habitat, may override any mitigating effects offered by surrounding landscape heterogeneity <xref ref-type="bibr" rid="BIBR-55">(Zhang, 2003)</xref>; <xref ref-type="bibr" rid="BIBR-48">(Tscharntke et al., 2016)</xref>; <xref ref-type="bibr" rid="BIBR-14">(Devi &amp; Challa, 2019)</xref>; <xref ref-type="bibr" rid="BIBR-39">(Qureshi et al., 2021)</xref>.</p></sec><sec><title>CONCLUSION</title><p>Our study revealed that the population of<italic> P. citri</italic> varied in both density and spatial distribution among the citrus orchards. We found that, in general, neither local nor landscape factors significantly influenced the mites’ overall population size. However, a key finding was that canopy density at the local level significantly influenced the spatial variation of <italic>P. citri</italic>, while pesticide use did not. This indicates that local conditions, specifically canopy proximity, are more important than broader landscape factors in determining how mites are distributed within an orchard. Consequently, effective <italic>P. citri</italic> management should focus on local factors. For instance, strategically pruning trees to create a more open canopy can alter the microclimate, making the habitat less favourable for mites while simultaneously benefiting natural predators that help control the population.</p></sec></body><back><ack><sec><title>ACKNOWLEDGMENTS</title><p>This research was completed with the help of many participants. 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