{"paper_id":"3f8946a4-b410-47ee-a6d4-e0b65a4d1969","body_text":"Effects of Agroforestry Practices on Insect Conservation in Transformed Ecosystems of the Semi-Arid Area, Dodoma, Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Agroforestry Practices on Insect Conservation in Transformed Ecosystems of the Semi-Arid Area, Dodoma, Tanzania James Michael Machallo, Kelvin Ngongolo, Naza E. Mmbaga This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9232955/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigated insect diversity and abundance to understand how agroforestry impacts biodiversity in transformed semi-arid ecosystems. Insects were collected using pitfall traps across areas with only trees (afforested), areas practicing agroforestry (agroforestry), areas with few remaining shrubs (shrubland), and untouched bushy areas (bushland). A total of 2,889 insects were collected. Shrubland had the lowest insect abundance but the highest diversity, while afforested land showed the highest abundance. Despite differences in diversity and richness, statistical tests revealed no significant variation among sites. Agroforestry had lower species diversity and richness compared to shrublands. Evenness was higher in bushland than in agroforestry and shrubland. These results suggest that agroforestry supports more insects but fewer species, possibly due to management practices and the type of trees integrated, which might favor specialist species. Further research is needed to understand how age and agroforestry components influence insect diversity in semi-arid regions. Agroforestry Insects’ abundance Insect diversity semi-arid ecosystems Figures Figure 1 1. Introduction Recent years have seen an increase in the conversion of forests into agricultural ecosystems, settlements, and infrastructure, among other uses, to meet the growing population's demand. [ 1 ]. This has significantly contributed to the ongoing loss of biodiversity worldwide, decreasing the ecosystem benefits that such biota provide [ 2 , 3 ]. The management of these transformed landscapes will determine whether or not efforts to maintain the planet's declining biodiversity are successful, according to [ 4 ]. So, any attempt to halt the loss of biodiversity must focus on conservation efforts in these transformed landscapes, with particular emphasis on preserving biodiversity in these altered ecosystems [ 1 ]. The use of sustainable agroecological practices that mimic natural ecosystems will enhance species diversity and promote healthy ecosystems in the semi-arid areas [ 5 ]. Agroforestry, the integration of trees into agricultural land, has become a farming method that offers several environmental, social, and economic advantages [ 6 ]. Agroforestry helps preserve biodiversity in tropical areas used by humans by preserving and diversifying specific trees on farms [ 7 ]. Agroforestry systems can support species diversity greater than 60% of that of a natural forest [ 7 , 8 ]. This is possible because agroforestry integrates the germplasm of several multipurpose trees, shrubs, and various grass species on farms, allowing the coexistence of additional species, as in natural forests. Despite their ecological importance, limited research has examined how agroforestry practices influence insect diversity and abundance in transformed ecosystems of the semi-arid regions, such as in Dodoma, Tanzania. Insects are among the species that can benefit from agroforestry, alongside other habitats [ 9 ]; however, there has been limited research on how agroforestry practices affect insect diversity and abundance in transformed ecosystems in semi-arid regions such as Dodoma. The diversity and abundance of insects have long served as a crucial indicator of the ecological health of many ecosystems [ 10 , 11 ]. Insect diversity and abundance were used by [ 12 ]to predict the ecological health of salt wetlands in the Setif Area of Algeria. Semi-arid landscapes present unique ecological constraints, including low and erratic rainfall, high temperatures, and sparse vegetation cover, all of which shape insect community dynamics. In such environments, agroforestry may play a disproportionately important role by enhancing habitat heterogeneity, moderating microclimatic extremes, and providing continuous floral, structural, and trophic resources that support diverse insect guilds. Understanding insect responses to agroforestry in these fragile ecosystems is therefore essential for designing land-use systems that maintain ecological functioning and resilience. The variety and availability of host plants, the environment, and the physiological status of the vegetation in agroforestry are all related to insect biodiversity [ 13 ]. Because host plants serve as both acceptable oviposition sites for adult females and prospective food sources for the young, their availability and an insect's capacity to locate them are crucial for a species' survival [ 14 ]. Although many studies have documented variations in insect diversity across forests, wetlands, rangelands, monoculture farms, and untouched natural ecosystems, fewer have focused specifically on the conservation potential of newly established agroforestry systems arising from land-use changes. This gap is especially evident in semi-arid regions, where ecosystem conversion is often viewed as a way to expand agricultural land and infrastructure. Additionally, agroforestry is increasingly promoted as a climate-resilient land-use option in these semi-arid areas. Understanding its conservation potential is therefore essential for proper planning and sustainability. This study addresses this gap by examining how agroforestry practices influence insect diversity and abundance in areas modified for building construction and infrastructure development within the University of Dodoma. It compares insect communities across four land-use types—newly established agroforestry systems, afforested forests, bushland, and shrubland—to evaluate the conservation value of agroforestry relative to other semi-arid habitats. 2. Materials and methods 2.1 Description of the Study Area The research was conducted at the University of Dodoma (UDOM), located in the Dodoma region, about 8 km to the east of the city center (Fig. 1). The University is located at 6°10′23\"S and 35°44′31\" E in the Dodoma District. UDOM covers approximately 6,000 acres. UDOM is situated in a semi-arid area with low, unimodal annual rainfall of approximately 550–600 mm between December and April [ 15 ]. With an annual average temperature of 29.0°C, the mean daily temperature is lowest in July (13.1°C) and highest in November (30.6°C) (Kayombo et al., 2020). Dry savanna shrub-thicket vegetation with sporadic trees and grassland areas characterizes UDOM. 21% of the country's total land area, or 193,604 km2, is covered by dry savanna. During the dry season, the bush becomes leafless, while during the wet season it flourishes with abundant life, making the whole area brilliant green. The study was specifically conducted at the College of Natural and Mathematical Sciences (CNMS), where part of its land has been cleared to make way for buildings and other infrastructure, another part of land has been cleared but is now covered with exotic trees, another area has been covered in fruit trees integrated with annual crops (agroforestry), and the remaining area is still covered in unaltered bushland and shrubland. There are also some areas of open grassland 2.2 Study Design The study area was divided into four study sites: agroforestry practiced area (here referred to as agroforestry), afforested area (here referred to as afforested), intact bushy area (here referred to as bushland), open shrubby region, and area with no grasses (shrubland). Each site was divided into two transects of 100 m each, spaced 50 m apart [ 15 ]. Pitfall trap points were placed along each transect at intervals of 20 meters, totaling 5 points per transect. Ten pitfall traps measuring 6 cm x 12 cm and 1lt in volume were placed at a distance of 20 m between each spot. In this instance, 5 samples were collected at each transect during each emptying session, for a total of 120 samples. The pitfall traps were filled with a 0.25 solution of soap to restrain the trapped insects [ 11 , 16 ]. 2.3 Data Collection For three consecutive days, the pitfalls were emptied every 24 hours, yielding a total of 30 samples at each study site (n = 120 samples across all sites over three days). The insects were temporarily stored in a plastic collecting bag before being preserved in 70% alcohol. [ 17 ], and then they were transported to the CNMS laboratory for identification, which was conducted using a guidebook [ 18 ]. 2.4 Data analysis A nonparametric test (Kruskal-Wallis test) was used to evaluate variation in insect abundance among the four study sites because the data were non-normally distributed. The diversity of the study sites was assessed using the Shannon-Weiner index and evenness. Using a permutation test on the Shannon-Weiner index, differences in diversity across the four study sites were identified. Using a generalized linear model (GLM), the impact of other factors on diversity and abundance was assessed. In all analyses, the statistical software package PAST version 4.03 was used. [ 19 ]. 3. Results 3.1 Insect Abundance Based on 120 samples, the study region had 2,889 insects overall. Of these, the most insects were found in afforested land (mean = 16.28876), followed by agroforestry areas (15.28973), shrubland (13.87674), and bushland (9.075471). The Kruskal-Wallis test revealed no statistically significant difference in insect abundance across the four sites (H = 0.6858, p = 0.86). In the study area, Aranea spp. were quite common (29.70%, n = 858), followed by Pachycondyla tarsata (27.13%, n = 784) and Lepisiola spp. (26.83%, n = 775). Amitermes spp., Epioscopomantis chalybea , Gryllacnididae spp., Ceroctis spp., Japygidae spp., Stenocara spp., Meliponula spp., and Mymicaria natalensis were the least numerous species in the research areas, with n = 2 and 0.04%, respectively. Based on the relative abundance of each species at a given location, Pachycondyla tarsata (17.44%) and Lepisiota spp. (12.32%) were found to be particularly numerous. Both bushland (7.68%) and shrubland (10.18%) were found to have higher abundances of Araneae spp. Table 1 Descriptive summary of the abundance of insects across the four habitats Habitat Abundance Percentage Mean Afforested land 863 30.0 16.29 Agroforestry 810 28.0 15.29 Bushland 481 16.6 9.1 Shrubland 735 25.4 13.9 Total 2889 100 Statistics H = 15.28973, p = 0.86 3.2 Species richness Across the research area, a total of 53 insect species from 16 orders were found. The shrubland had the highest number of species recorded (67.92%, n = 36), followed by the afforested land area (64.15%, n = 34), while the bushland and agroforestry had the lowest number of species (54.72%, n = 29). Lepisiota spp, Patchycondyla tarsata, and Araneae spp are a few of the species that exhibit high distribution in the research area. Amitermes spp., Epioscopomantis chalybea, and Gryllacrididae spp., on the other hand, are less common in the research area. It was shown that the variation in species richness distribution across the four habitats was not statistically significant(p = 0.756). Table 2 Descriptive summary of the insects’ richness across the four habitats Habitat Number of species Percentage Afforested land 34 64.15 Agroforestry 29 54.72 Bushland 29 54.72 Shrubland 36 67.92 Total 53 100 Statistics χ2 = 1.187, p = 0.756 3.3 Insect Species Diversity Among the four habitats assessed, Shrubland exhibited the highest Shannon diversity (1.859) and the greatest Hill number for effective species richness (Hill q1 = 6.416), indicating a more even and compositionally rich assemblage. Bushland showed similarly elevated diversity (Shannon = 1.803; Hill q1 = 6.069), with the highest Simpson index (0.717) after Shrubland, reflecting a relatively low dominance structure. In contrast, Afforested sites supported intermediate levels of diversity (Shannon = 1.573; Hill q1 = 4.819), while agroforestry systems had the lowest diversity across all indices (Shannon = 1.507; Hill q1 = 4.513). Hill q2 values, which emphasize abundant taxa, followed the same pattern, ranging from 3.991 in Shrubland to 2.403 in Agroforestry. Table 3 Descriptive summary of insects’ diversity across the four habitats Habitat_type Shannon Simpson Hill_q1 Hill_q2 Afforested 1.573 0.697 4.819 3.301 Agroforestry 1.507 0.584 4.513 2.403 Bushland 1.803 0.717 6.069 3.528 Shrubland 1.859 0.749 6.416 3.991 3.4 Species diversity indices Table 1 presents the diversity indices for the four habitats in our study area. Regarding overall species diversity, shrubland has the highest Shannon Weiner (H') and Gini Simpson (GS) indices, with values of 1.86 and 0.75, respectively. The lowest species diversity indices were recorded for agroforestry (Shannon-Weiner, H' = 1.51; Simpson 1-D = 0.58). According to the findings, there were significant differences in species diversity between agroforestry and all other habitats (Shannon index, p = 0.0001; Simpson's index, p = 0.0001). Agroforestry had the lowest species richness (Margalef index D = 4.18), whereas shrubland had the highest (D = 5.30). Similarly, the shrubland had a higher species richness estimate (46.11) than the other sites (Table 1 ). Only the difference in species richness between shrubland and agroforestry was statistically significant (Margallef, p = 0.05). The degree of species evenness was greatest in bushland (eH/S = 0.21), followed by shrubland (e = 0.18), agroforestry (e = 0.16), and an afforested site (e = 0.14), with bushland having the highest level. Moreover, the equitability J index indicates that shrubland has higher evenness, whereas afforested sites have lower evenness (Table 1 ). Between agroforestry and bushland, the observed variation in evenness was statistically significant (p = 0.06, p = 0.0006 for equitability), and between agroforestry and shrubland, p = 0.0002 for equitability. About species dominance, further analysis revealed that shrubland agroforestry sites had the highest levels (Dominance D = 0.42, Berger-Parker D = 0.62) and the lowest levels (Dominance D = 0.25, Berger-Parker D = 0.40). The differences in species dominance between afforested, bushland, and shrubland, and agroforestry were all statistically significant (Dominance p = 0.0001; Berger-Parker p = 0.0001). Table 4 Species Diversity Indices for the four study sites. Taxa_S Agroforestry Afforested Bushland Shrubland 29 34 29 36 Individuals 810 863 481 735 Dominance_D 0.4161 0.303 0.2834 0.2506 Simpson_1-D 0.5839 0.697 0.7166 0.7494 Shannon_H 1.507 1.573 1.803 1.859 Evenness_e^H/S 0.1556 0.1417 0.2093 0.1782 Brillouin 1.451 1.518 1.715 1.788 Menhinick 1.019 1.157 1.322 1.328 Margalef 4.181 4.881 4.534 5.303 Equitability_J 0.4476 0.446 0.5355 0.5187 Fisher_alpha 5.879 7.063 6.783 7.929 Berger-Parker 0.6222 0.4125 0.4615 0.4 Chao-1 38 39.5 35 46.11 3.5 Effects of habitats on insect abundance To determine how each study site affected insect abundance, the association between each site's abundance (independent variable) and the dependent variable was examined. Findings indicate that whereas afforested and bushlands exhibit a negative link to the insect's abundance, agroforestry and shrubland show a positive correlation (Table 2 ) Table 5 Generalized Linear Model (GLM) results showing the influence of ecological habitats on insect abundance across study sites. c/n Variable Classification Coefficients: Estimate Std. Error z value P-value 1 Ecological habitats (Study sites) (Intercept) 1.9252647 0.0539530 35.684 < 2e-16 *** Agroforestry 0.0070040 0.0001233 56.797 < 2e-16 *** Afforested -0.0044536 0.0005600 -7.953 < 2e-15 *** Bushland -0.0442972 0.0023509 -18.843 < 2e-16 *** Shrubland 0.0529511 0.0023420 22.609 < 2e-16 *** 3.6 Effects of habitats on insect richness Regression analysis revealed no significant differences in insect richness among Agroforestry, Bushland, and Shrubland habitats relative to Afforested sites (Agroforestry: Estimate = − 0.124, p = 0.656; Bushland: Estimate = − 0.024, p = 0.931; Shrubland: Estimate = 0.022, p = 0.932). The intercept (Estimate = 3.068, p < 0.001) indicates that Afforested habitats supported significantly higher insect richness overall. Thus, while Afforested sites exhibited a robust baseline richness, other habitat types did not differ significantly from this reference. Table 6 Generalized Linear Model (GLM) results assessing the effect of habitat type on insect species richness. Habitat type Estimate Std. error Statistic p.value (Intercept) 3.068 0.192 15.972 < 2e-16*** Agroforestry -0.124 0.277 -0.446 0.656 Bushland -0.024 0.273 -0.086 0.931 Shrubland 0.0223 0.271 0.085 0.932 Notes: The intercept indicates baseline habitat richness (afforested), while agroforestry, bushland, and shrubland habitats showed no statistically significant deviations from the baseline (p > 0.05). 3.7 Effects of habitats on insects’ diversity Linear models assessing the effects of habitat type on insect diversity revealed no significant differences among Agroforestry, Bushland, and Shrubland relative to Afforested sites across all indices. For Shannon diversity (Table 6 ), the intercept representing Afforested habitats was significant (Estimate = 1.514, p = 0.009), while Agroforestry (p = 0.904), Bushland (p = 0.586), and Shrubland (p = 0.667) showed no significant effects. Similarly, Simpson diversity (Table 7 ) was significant in Afforested habitats (Estimate = 0.633, p = 0.048), but non-significant across the other habitat types. Hill numbers (q1 and q2; Tables 8 and 9 ) confirmed this pattern: Afforested habitats exhibited significant baseline diversity (Hill_q1: Estimate = 1.547, p = 0.006; Hill_q2: Estimate = 1.195, p = 0.015), whereas Agroforestry, Bushland, and Shrubland did not differ significantly from the reference. Overall, Afforested habitats supported consistently higher insect diversity, while other habitats showed no meaningful deviations from this baseline. Table 7 Generalized Linear Model (GLM) results evaluating the effect of habitat type on Shannon diversity of insects. Habitat Type Estimate Std. error Statistic p.value (Intercept) 1.514 0.316 4.794 0.009*** Agroforestry -0.058 0.447 -0.129 0.904 Bushland 0.265 0.448 0.592 0.586 Shrubland 0.207 0.447 0.464 0.667 Notes : The intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not show statistically significant differences compared to the baseline (p > 0.05). Table 8 Generalized Linear Model (GLM) results assessing the effect of habitat type on Simpson diversity of insects. Habitat Type Estimate Std. error Statistic p.value (Intercept) 0.633 0.320 1.976 0.048** Agroforestry -0.381 0.444 -0.857 0.392 Bushland 0.128 0.457 0.280 0.780 Shrubland 0.226 0.461 0.492 0.623 Notes: The intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not show statistically significant differences compared to the baseline (p > 0.05). Table 9 Generalized Linear Model (GLM) results for Hill q₁ diversity indices across habitat types. Habitat Type Estimate Std. error Statistic p.value (Intercept) 1.547 0.293 5.282 0.006*** Agroforestry 0.054 0.414 0.131 0.902 Bushland 0.246 0.414 0.593 0.585 Shrubland 0.174 0.414 0.420 0.696 Notes: The intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not exhibit statistically significant differences compared to the baseline (p > 0.05). Table 10 Generalized Linear Model (GLM) results for Hill q₂ diversity indices across habitat types. Habitat Type Estimate Std. error Statistic p.value (Intercept) 1.195 0.294 4.058 0.015** Agroforestry -0.046 0.416 -0.111 0.917 Bushland 0.074 0.416 0.179 0.867 Shrubland 0.176 0.416 0.423 0.694 Notes: The intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not exhibit statistically significant differences compared to the baseline (p > 0.05). 4. Discussion 4.1 Species abundance Findings indicate that the abundance is highest in afforested areas, followed by agroforestry areas, and lowest in bushland areas. Unlike afforested and agroforestry sites, where trees and crops are artificially managed to prevent predator development, the presence of insect predators in the bushy area may be responsible for the low insect numbers in the bushland. The findings of the present study are in contrast with those of a study by [ 20 ]which claimed that converting natural ecosystems to alternative land uses leads to declines in insect populations. According to [ 21 ] and [ 22 ], afforestation, however, provides microhabitats for a variety of faunal species, including insects. Further literature explains that variations in environmental conditions, the time of year when insects were collected, and the presence of vulnerable hosts in the research location can all be linked to variations in observed abundance. [ 23 ]. 4.2 Species richness According to this study, shrubland had the highest species richness while agroforestry had the lowest. Compared with young afforested and agroforestry ecosystems, the shrubland ecosystem is more complex and has several feeding niches, which are major contributors to its higher species richness. In his study on the impact of afforestation on coleopteran abundance and diversity, [ 24 ], reported similar findings. He said that the shrubland's omnivorous, phytophagous, and predatory beetle species all lived there, making the environment more stable. Similar to this observation,[ 25 ] and[ 26 ] high insect species richness as a sign of a more complex food web structure, which is frequently associated with established and stable ecosystems. 4.3 Species diversity The shrubland and afforested areas had the highest insect diversity, whereas the bushland and agroforestry sites had the lowest. This pattern may be explained by the availability of a variety of resources, such as food for various species, and by the shrubland's more favorable environment for more species than at the other sites. It is important to keep in mind that areas planted solely with trees have lower layers covered in grasses and other shorter plants that resemble shrubland. According to a study by [ 27 ], maintaining a diverse understory of native species increases wildlife populations and ecological diversity. Despite access to a variety of resources, agroforestry is considered to support a limited number of insect species. This can be explained by various factors, such as the age of the trees, frequent management measures that disrupt some species, leading to their emigration or relocation to surrounding areas [ 28 ]. The bushland and shrubland had higher evenness indices than the agroforestry and afforested areas, which both had lower evenness. This finding indicates that some species are more dominant in agroforestry and wooded areas due to resource conditions that favor them. For instance, Pachycondyla tarsata , Lepisiota spp., and Araneae spp. appear to have high dominance in bushland, agroforestry, and planted areas, respectively. According to the study's findings, shrubland has a lower species dominance index than agroforestry (Table 4 ). Lower species evenness and diversity in agroforestry are a result of the inverse relationship between the dominance index and other diversity indices. This finding is consistent with a study by [ 24 ], which found that coleopteran evenness was higher in grasslands and lower in a three-year tree plantation. In addition, a study by[ 29 ] produced findings that were similar to those of the current study. The study claims that many species of Scarabaeidae and Scarabaeinae preferred wooded patches, such as bushland, over grassland and cultivated sites in semi-arid Tanzania, resulting in greater species richness and evenness. 4.4 Effects of habitats on species abundance and diversity To assess the impact of each site on the insect abundance and diversity, a correlation test was conducted. The findings revealed a favorable relationship between shrubland and agroforestry in terms of insect abundance. This shows that while afforested and bushland areas lead to a decline in insect abundance, agroforestry and shrubland areas increase it. Ecologically, agroforestry is an agroecosystem composed of numerous components that are coordinated to provide diverse microhabitats, which, in turn, support a variety of insect species. According to[ 24 ] microhabitats that were ideal for many different beetle species. This study's findings, which suggested that afforested areas may negatively affect insect abundance, are at odds with these findings. This deviation can be explained by the fact that the age of the afforested site matters for insect abundance and distribution [ 15 , 30 ]. Interestingly, only the afforested site had a significant positive influence on insect diversity indices, meaning that although afforestation harbors a small total number of species, these species are distributed across many insect taxa. This might be contributed to by the presence of a few predators in the newly established afforested sites. On the other hand, shrublands are characterized by numerous niches due to the variety of vegetation structures and the ecosystem's age [ 24 ]. Overall, the gradient in diversity metrics (Shrubland > Bushland > Afforested > Agroforestry) suggests that more structurally complex or less intensively managed habitats support richer and more even insect communities. Similar findings were reported by [ 31 ], who claimed that animal and insect species diversity has been shown to correspond to the structural complexity of habitats and the diversity of vegetation forms. 5. Conclusion Of the four study locations, the agroforestry site had the second-highest insect abundance, but it had low overall insect species diversity, species richness, and evenness. Also, across the three locations, agroforestry showed the highest level of species domination. The correlation analysis, however, revealed a strong association between agroforestry and insect abundance, indicating that agroforestry helps boost insect populations. Findings also demonstrate that agroforestry approaches may offer an environment conducive to insect survival and reproduction. The dominance of some species, such Pachycondyla tarsata , which was discovered to be extremely common in agroforestry, reveals this. The age of the ecosystem and management strategies were found to affect insect diversity and abundance. Although our study provides robust baseline data, seasonal variation and functional diversity were not assessed. Future research should explore how insect diversity translates into ecosystem services such as pollination and nutrient cycling, and how agroforestry practices within semi-arid areas can be optimized to balance biodiversity conservation with household livelihoods. Declarations Acknowledgments. The authors of this work are grateful to the University of Dodoma for letting us carry out this investigation on one of its properties. They also acknowledge the assistance from the Department of Biology, notably during data collection and analysis. Author contributions J.M.M designed and conducted the study, collected and analyzed the data, and drafted the manuscript. K.N and N.M provided ongoing guidance, critical feedback, and substantial revisions throughout the development of the manuscript. All authors read and approved the final version. Data availability The data are available upon request. Ethics approval and consent to participate: Not applicable. This study involved only invertebrate insects. Ethical approval was therefore not required. Field sampling was conducted in accordance with local regulations and standard entomological practices. No vertebrate animals were involved. Consent to participate Not applicable. 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Challenges Of Producing Quality Tree Seeds To Support Afforestation In Tanzania. In: Proceedings of the 1st TAFORI Scientific Conference on Forestry Research for Sustainable Industrial Economy in Tanzania . 2018, pp. 63–72. Shakeel M, Ali H, Ahmad S, et al. Insect pollinators diversity and abundance in Eruca sativa Mill. (Arugula) and Brassica rapa L. (Field mustard) crops. Saudi J Biol Sci. 2019;26:1704–9. Gayo L. Influence of afforestation on coleopterans abundance and diversity at the University of Dodoma, Tanzania. Environ Sustain Indic. 2022;16:100208. Nagy DD, Magura T, Mizser S, et al. Recovery of surface-dwelling assemblages (Coleoptera: Carabidae, staphylinidae) during clear-cut originated reforestation with native tree species. Period Biol. 2016;118:195–203. Medina AM, Lopes PP. Seasonality in the dung beetle community in a Brazilian tropical dry forest: Do small changes make a difference? Lopes J Insect Sci |. 2014;14:123. Lindenmayer DB, Laurance WF. The ecology, distribution, conservation and management of large old trees. Biol Rev. 2017;92:1434–58. Saria GA, Munishi PKT, Kashaigili JJ, et al. Plant species composition, richness and diversity in different agroforestry practices of Moshi rural district, Northern Tanzania. Int J Biodivers Conserv. 2025;17:1–22. Tind Nielsen S. Deforestation and biodiversity: Effects of bushland cultivation on dung beetles in semi-arid Tanzania. Biodivers Conserv. 2007;16:2753–69. Chan EKW, Yu YT, Zhang Y, et al. Distribution patterns of birds and insect prey in a tropical riparian forest. Biotropica. 2008;40:623–9. Alarape AA, Omifolaji JK, Mwansat GS. Butterfly Species Diversity and Abundance in University of Ibadan Botanical Garden, Nigeria. Open J Ecol. 2015;05:352–60. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-9232955\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":624325577,\"identity\":\"0c25de0f-a09e-4853-8f66-d0b349df2d58\",\"order_by\":0,\"name\":\"James Michael Machallo\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYHACNgaGAgYDIMn4AMjj4SNOiwFYC7MBSAsb0VpADAkoFz/QbT/87MEPAxtjPonkY5Vfc+xk2BiYHz66gUeL2Zk0c8MegzQzNom0tNuy25KBDmMzNs7Bp+VADpsEj8FhGzbpHLPbktuYgVp4gGx8Ws6/YZP8A9aS/61Ycls9EVpu5LBJA20xAypjY/y47TAxWp6ZScsYpBmzyT8zlmbcdpyHjZmQX84nP5N8U2FjOL/n8MOPP7dV2/OzNz98jE8LCmDmAZPEKgcBxh+kqB4Fo2AUjIIRAwD1yj6KCe1vfgAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"The University of Dodoma\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"James\",\"middleName\":\"Michael\",\"lastName\":\"Machallo\",\"suffix\":\"\"},{\"id\":624325578,\"identity\":\"fabaf2c2-17bf-4032-ac64-e5df90358b86\",\"order_by\":1,\"name\":\"Kelvin Ngongolo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Dodoma\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kelvin\",\"middleName\":\"\",\"lastName\":\"Ngongolo\",\"suffix\":\"\"},{\"id\":624325579,\"identity\":\"134fd691-e735-49bf-b3b8-9205078f1fe9\",\"order_by\":2,\"name\":\"Naza E. Mmbaga\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Dodoma\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Naza\",\"middleName\":\"E.\",\"lastName\":\"Mmbaga\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-03-26 10:39:26\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9232955/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9232955/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":107695512,\"identity\":\"8803d123-85db-43da-82a8-074ec1ab6db9\",\"added_by\":\"auto\",\"created_at\":\"2026-04-24 07:01:43\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":5713,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLegend not included with this version\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9232955/v1/099b3b1c8bd2b1bf4f96dd05.png\"},{\"id\":108716622,\"identity\":\"a2af63a9-da96-482f-93d4-0f7843dbe60a\",\"added_by\":\"auto\",\"created_at\":\"2026-05-07 15:11:57\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":411038,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9232955/v1/64382416-fa7d-40e3-8c7a-99e4c6a8eeb8.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Effects of Agroforestry Practices on Insect Conservation in Transformed Ecosystems of the Semi-Arid Area, Dodoma, Tanzania\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eRecent years have seen an increase in the conversion of forests into agricultural ecosystems, settlements, and infrastructure, among other uses, to meet the growing population's demand. [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. This has significantly contributed to the ongoing loss of biodiversity worldwide, decreasing the ecosystem benefits that such biota provide [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. The management of these transformed landscapes will determine whether or not efforts to maintain the planet's declining biodiversity are successful, according to [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. So, any attempt to halt the loss of biodiversity must focus on conservation efforts in these transformed landscapes, with particular emphasis on preserving biodiversity in these altered ecosystems [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. The use of sustainable agroecological practices that mimic natural ecosystems will enhance species diversity and promote healthy ecosystems in the semi-arid areas [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAgroforestry, the integration of trees into agricultural land, has become a farming method that offers several environmental, social, and economic advantages [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. Agroforestry helps preserve biodiversity in tropical areas used by humans by preserving and diversifying specific trees on farms [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. Agroforestry systems can support species diversity greater than 60% of that of a natural forest [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. This is possible because agroforestry integrates the germplasm of several multipurpose trees, shrubs, and various grass species on farms, allowing the coexistence of additional species, as in natural forests. Despite their ecological importance, limited research has examined how agroforestry practices influence insect diversity and abundance in transformed ecosystems of the semi-arid regions, such as in Dodoma, Tanzania.\\u003c/p\\u003e \\u003cp\\u003eInsects are among the species that can benefit from agroforestry, alongside other habitats [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]; however, there has been limited research on how agroforestry practices affect insect diversity and abundance in transformed ecosystems in semi-arid regions such as Dodoma. The diversity and abundance of insects have long served as a crucial indicator of the ecological health of many ecosystems [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Insect diversity and abundance were used by [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]to predict the ecological health of salt wetlands in the Setif Area of Algeria. Semi-arid landscapes present unique ecological constraints, including low and erratic rainfall, high temperatures, and sparse vegetation cover, all of which shape insect community dynamics. In such environments, agroforestry may play a disproportionately important role by enhancing habitat heterogeneity, moderating microclimatic extremes, and providing continuous floral, structural, and trophic resources that support diverse insect guilds. Understanding insect responses to agroforestry in these fragile ecosystems is therefore essential for designing land-use systems that maintain ecological functioning and resilience.\\u003c/p\\u003e \\u003cp\\u003eThe variety and availability of host plants, the environment, and the physiological status of the vegetation in agroforestry are all related to insect biodiversity [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Because host plants serve as both acceptable oviposition sites for adult females and prospective food sources for the young, their availability and an insect's capacity to locate them are crucial for a species' survival [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAlthough many studies have documented variations in insect diversity across forests, wetlands, rangelands, monoculture farms, and untouched natural ecosystems, fewer have focused specifically on the conservation potential of newly established agroforestry systems arising from land-use changes. This gap is especially evident in semi-arid regions, where ecosystem conversion is often viewed as a way to expand agricultural land and infrastructure. Additionally, agroforestry is increasingly promoted as a climate-resilient land-use option in these semi-arid areas. Understanding its conservation potential is therefore essential for proper planning and sustainability. This study addresses this gap by examining how agroforestry practices influence insect diversity and abundance in areas modified for building construction and infrastructure development within the University of Dodoma. It compares insect communities across four land-use types\\u0026mdash;newly established agroforestry systems, afforested forests, bushland, and shrubland\\u0026mdash;to evaluate the conservation value of agroforestry relative to other semi-arid habitats.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Description of the Study Area\\u003c/h2\\u003e \\u003cp\\u003eThe research was conducted at the University of Dodoma (UDOM), located in the Dodoma region, about 8 km to the east of the city center (Fig.\\u0026nbsp;1). The University is located at 6\\u0026deg;10\\u0026prime;23\\\"S and 35\\u0026deg;44\\u0026prime;31\\\" E in the Dodoma District. UDOM covers approximately 6,000 acres. UDOM is situated in a semi-arid area with low, unimodal annual rainfall of approximately 550\\u0026ndash;600 mm between December and April [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. With an annual average temperature of 29.0\\u0026deg;C, the mean daily temperature is lowest in July (13.1\\u0026deg;C) and highest in November (30.6\\u0026deg;C) (Kayombo et al., 2020). Dry savanna shrub-thicket vegetation with sporadic trees and grassland areas characterizes UDOM. 21% of the country's total land area, or 193,604 km2, is covered by dry savanna. During the dry season, the bush becomes leafless, while during the wet season it flourishes with abundant life, making the whole area brilliant green. The study was specifically conducted at the College of Natural and Mathematical Sciences (CNMS), where part of its land has been cleared to make way for buildings and other infrastructure, another part of land has been cleared but is now covered with exotic trees, another area has been covered in fruit trees integrated with annual crops (agroforestry), and the remaining area is still covered in unaltered bushland and shrubland. There are also some areas of open grassland\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Study Design\\u003c/h2\\u003e \\u003cp\\u003eThe study area was divided into four study sites: agroforestry practiced area (here referred to as agroforestry), afforested area (here referred to as afforested), intact bushy area (here referred to as bushland), open shrubby region, and area with no grasses (shrubland). Each site was divided into two transects of 100 m each, spaced 50 m apart [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Pitfall trap points were placed along each transect at intervals of 20 meters, totaling 5 points per transect. Ten pitfall traps measuring 6 cm x 12 cm and 1lt in volume were placed at a distance of 20 m between each spot. In this instance, 5 samples were collected at each transect during each emptying session, for a total of 120 samples. The pitfall traps were filled with a 0.25 solution of soap to restrain the trapped insects [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Data Collection\\u003c/h2\\u003e \\u003cp\\u003eFor three consecutive days, the pitfalls were emptied every 24 hours, yielding a total of 30 samples at each study site (n\\u0026thinsp;=\\u0026thinsp;120 samples across all sites over three days). The insects were temporarily stored in a plastic collecting bag before being preserved in 70% alcohol. [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], and then they were transported to the CNMS laboratory for identification, which was conducted using a guidebook [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Data analysis\\u003c/h2\\u003e \\u003cp\\u003eA nonparametric test (Kruskal-Wallis test) was used to evaluate variation in insect abundance among the four study sites because the data were non-normally distributed. The diversity of the study sites was assessed using the Shannon-Weiner index and evenness. Using a permutation test on the Shannon-Weiner index, differences in diversity across the four study sites were identified. Using a generalized linear model (GLM), the impact of other factors on diversity and abundance was assessed. In all analyses, the statistical software package PAST version 4.03 was used. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Insect Abundance\\u003c/h2\\u003e \\u003cp\\u003eBased on 120 samples, the study region had 2,889 insects overall. Of these, the most insects were found in afforested land (mean\\u0026thinsp;=\\u0026thinsp;16.28876), followed by agroforestry areas (15.28973), shrubland (13.87674), and bushland (9.075471). The Kruskal-Wallis test revealed no statistically significant difference in insect abundance across the four sites (H\\u0026thinsp;=\\u0026thinsp;0.6858, p\\u0026thinsp;=\\u0026thinsp;0.86). In the study area, Aranea spp. were quite common (29.70%, n\\u0026thinsp;=\\u0026thinsp;858), followed by \\u003cem\\u003ePachycondyla tarsata\\u003c/em\\u003e (27.13%, n\\u0026thinsp;=\\u0026thinsp;784) and \\u003cem\\u003eLepisiola\\u003c/em\\u003e spp. (26.83%, n\\u0026thinsp;=\\u0026thinsp;775). \\u003cem\\u003eAmitermes\\u003c/em\\u003e spp., \\u003cem\\u003eEpioscopomantis chalybea\\u003c/em\\u003e, \\u003cem\\u003eGryllacnididae\\u003c/em\\u003e spp., \\u003cem\\u003eCeroctis\\u003c/em\\u003e spp., \\u003cem\\u003eJapygidae\\u003c/em\\u003e spp., \\u003cem\\u003eStenocara\\u003c/em\\u003e spp., \\u003cem\\u003eMeliponula\\u003c/em\\u003e spp., and \\u003cem\\u003eMymicaria natalensis\\u003c/em\\u003e were the least numerous species in the research areas, with n\\u0026thinsp;=\\u0026thinsp;2 and 0.04%, respectively.\\u003c/p\\u003e \\u003cp\\u003eBased on the relative abundance of each species at a given location, Pachycondyla tarsata (17.44%) and Lepisiota spp. (12.32%) were found to be particularly numerous. Both bushland (7.68%) and shrubland (10.18%) were found to have higher abundances of Araneae spp.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDescriptive summary of the abundance of insects across the four habitats\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAbundance\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePercentage\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eMean\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAfforested land\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e863\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e30.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e810\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e28.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e481\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e16.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e735\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e25.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e13.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2889\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eStatistics\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c4\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eH\\u0026thinsp;=\\u0026thinsp;15.28973, p\\u0026thinsp;=\\u0026thinsp;0.86\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Species richness\\u003c/h2\\u003e \\u003cp\\u003eAcross the research area, a total of 53 insect species from 16 orders were found. The shrubland had the highest number of species recorded (67.92%, n\\u0026thinsp;=\\u0026thinsp;36), followed by the afforested land area (64.15%, n\\u0026thinsp;=\\u0026thinsp;34), while the bushland and agroforestry had the lowest number of species (54.72%, n\\u0026thinsp;=\\u0026thinsp;29). Lepisiota spp, Patchycondyla tarsata, and Araneae spp are a few of the species that exhibit high distribution in the research area. Amitermes spp., Epioscopomantis chalybea, and Gryllacrididae spp., on the other hand, are less common in the research area. It was shown that the variation in species richness distribution across the four habitats was not statistically significant(p\\u0026thinsp;=\\u0026thinsp;0.756).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDescriptive summary of the insects\\u0026rsquo; richness across the four habitats\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNumber of species\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePercentage\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAfforested land\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e34\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e64.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e54.72\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e54.72\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e67.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eStatistics\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003csup\\u003e\\u003cem\\u003eχ2\\u003c/em\\u003e\\u003c/sup\\u003e \\u003cem\\u003e= 1.187, p\\u0026thinsp;=\\u0026thinsp;0.756\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Insect Species Diversity\\u003c/h2\\u003e \\u003cp\\u003eAmong the four habitats assessed, Shrubland exhibited the highest Shannon diversity (1.859) and the greatest Hill number for effective species richness (Hill q1\\u0026thinsp;=\\u0026thinsp;6.416), indicating a more even and compositionally rich assemblage. Bushland showed similarly elevated diversity (Shannon\\u0026thinsp;=\\u0026thinsp;1.803; Hill q1\\u0026thinsp;=\\u0026thinsp;6.069), with the highest Simpson index (0.717) after Shrubland, reflecting a relatively low dominance structure.\\u003c/p\\u003e \\u003cp\\u003eIn contrast, Afforested sites supported intermediate levels of diversity (Shannon\\u0026thinsp;=\\u0026thinsp;1.573; Hill q1\\u0026thinsp;=\\u0026thinsp;4.819), while agroforestry systems had the lowest diversity across all indices (Shannon\\u0026thinsp;=\\u0026thinsp;1.507; Hill q1\\u0026thinsp;=\\u0026thinsp;4.513). Hill q2 values, which emphasize abundant taxa, followed the same pattern, ranging from 3.991 in Shrubland to 2.403 in Agroforestry.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDescriptive summary of insects\\u0026rsquo; diversity across the four habitats\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat_type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eShannon\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSimpson\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eHill_q1\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eHill_q2\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAfforested\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.573\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.697\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.819\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.301\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.507\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.584\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.513\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.403\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.803\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.717\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.069\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.528\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.859\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.416\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.991\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 Species diversity indices\\u003c/h2\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e presents the diversity indices for the four habitats in our study area. Regarding overall species diversity, shrubland has the highest Shannon Weiner (H') and Gini Simpson (GS) indices, with values of 1.86 and 0.75, respectively. The lowest species diversity indices were recorded for agroforestry (Shannon-Weiner, H' = 1.51; Simpson 1-D\\u0026thinsp;=\\u0026thinsp;0.58). According to the findings, there were significant differences in species diversity between agroforestry and all other habitats (Shannon index, p\\u0026thinsp;=\\u0026thinsp;0.0001; Simpson's index, p\\u0026thinsp;=\\u0026thinsp;0.0001).\\u003c/p\\u003e \\u003cp\\u003eAgroforestry had the lowest species richness (Margalef index D\\u0026thinsp;=\\u0026thinsp;4.18), whereas shrubland had the highest (D\\u0026thinsp;=\\u0026thinsp;5.30). Similarly, the shrubland had a higher species richness estimate (46.11) than the other sites (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Only the difference in species richness between shrubland and agroforestry was statistically significant (Margallef, p\\u0026thinsp;=\\u0026thinsp;0.05).\\u003c/p\\u003e \\u003cp\\u003eThe degree of species evenness was greatest in bushland (eH/S\\u0026thinsp;=\\u0026thinsp;0.21), followed by shrubland (e\\u0026thinsp;=\\u0026thinsp;0.18), agroforestry (e\\u0026thinsp;=\\u0026thinsp;0.16), and an afforested site (e\\u0026thinsp;=\\u0026thinsp;0.14), with bushland having the highest level. Moreover, the equitability J index indicates that shrubland has higher evenness, whereas afforested sites have lower evenness (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Between agroforestry and bushland, the observed variation in evenness was statistically significant (p\\u0026thinsp;=\\u0026thinsp;0.06, p\\u0026thinsp;=\\u0026thinsp;0.0006 for equitability), and between agroforestry and shrubland, p\\u0026thinsp;=\\u0026thinsp;0.0002 for equitability.\\u003c/p\\u003e \\u003cp\\u003eAbout species dominance, further analysis revealed that shrubland agroforestry sites had the highest levels (Dominance D\\u0026thinsp;=\\u0026thinsp;0.42, Berger-Parker D\\u0026thinsp;=\\u0026thinsp;0.62) and the lowest levels (Dominance D\\u0026thinsp;=\\u0026thinsp;0.25, Berger-Parker D\\u0026thinsp;=\\u0026thinsp;0.40). The differences in species dominance between afforested, bushland, and shrubland, and agroforestry were all statistically significant (Dominance p\\u0026thinsp;=\\u0026thinsp;0.0001; Berger-Parker p\\u0026thinsp;=\\u0026thinsp;0.0001).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eSpecies Diversity Indices for the four study sites.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eTaxa_S\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAfforested\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e29\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e34\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e29\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e36\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndividuals\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e810\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e863\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e481\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e735\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDominance_D\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.4161\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.303\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.2834\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.2506\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSimpson_1-D\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.5839\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.697\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.7166\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.7494\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShannon_H\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.507\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.573\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.803\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.859\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEvenness_e^H/S\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.1556\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.1417\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.2093\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.1782\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBrillouin\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.451\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.518\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.715\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.788\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMenhinick\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.019\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.157\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.322\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.328\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMargalef\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.181\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.881\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.534\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5.303\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEquitability_J\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.4476\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.446\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.5355\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.5187\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFisher_alpha\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5.879\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7.063\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.783\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7.929\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBerger-Parker\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6222\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.4125\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.4615\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChao-1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e39.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e46.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.5 Effects of habitats on insect abundance\\u003c/h2\\u003e \\u003cp\\u003eTo determine how each study site affected insect abundance, the association between each site's abundance (independent variable) and the dependent variable was examined. Findings indicate that whereas afforested and bushlands exhibit a negative link to the insect's abundance, agroforestry and shrubland show a positive correlation (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e)\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results showing the influence of ecological habitats on insect abundance across study sites.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ec/n\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eCoefficients: Estimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eStd. Error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003ez value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eP-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e \\u003cp\\u003eEcological habitats (Study sites)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.9252647\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0539530\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e35.684\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-16 ***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0070040\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0001233\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e56.797\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-16 ***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAfforested\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.0044536\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0005600\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-7.953\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-15 ***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.0442972\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0023509\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e-18.843\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-16 ***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0529511\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0023420\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e22.609\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-16 ***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.6 Effects of habitats on insect richness\\u003c/h2\\u003e \\u003cp\\u003eRegression analysis revealed no significant differences in insect richness among Agroforestry, Bushland, and Shrubland habitats relative to Afforested sites (Agroforestry: Estimate = \\u0026minus;\\u0026thinsp;0.124, p\\u0026thinsp;=\\u0026thinsp;0.656; Bushland: Estimate = \\u0026minus;\\u0026thinsp;0.024, p\\u0026thinsp;=\\u0026thinsp;0.931; Shrubland: Estimate\\u0026thinsp;=\\u0026thinsp;0.022, p\\u0026thinsp;=\\u0026thinsp;0.932). The intercept (Estimate\\u0026thinsp;=\\u0026thinsp;3.068, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) indicates that Afforested habitats supported significantly higher insect richness overall. Thus, while Afforested sites exhibited a robust baseline richness, other habitat types did not differ significantly from this reference.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results assessing the effect of habitat type on insect species richness.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEstimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eStd. error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eStatistic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep.value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3.068\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.192\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.972\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2e-16***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.124\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.277\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.446\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.656\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.024\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.273\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.086\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.931\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.0223\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.271\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.085\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.932\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003eNotes: \\u003cem\\u003eThe intercept indicates baseline habitat richness (afforested), while agroforestry, bushland, and shrubland habitats showed no statistically significant deviations from the baseline (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.7 Effects of habitats on insects\\u0026rsquo; diversity\\u003c/h2\\u003e \\u003cp\\u003eLinear models assessing the effects of habitat type on insect diversity revealed no significant differences among Agroforestry, Bushland, and Shrubland relative to Afforested sites across all indices. For Shannon diversity (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e), the intercept representing Afforested habitats was significant (Estimate\\u0026thinsp;=\\u0026thinsp;1.514, p\\u0026thinsp;=\\u0026thinsp;0.009), while Agroforestry (p\\u0026thinsp;=\\u0026thinsp;0.904), Bushland (p\\u0026thinsp;=\\u0026thinsp;0.586), and Shrubland (p\\u0026thinsp;=\\u0026thinsp;0.667) showed no significant effects. Similarly, Simpson diversity (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e) was significant in Afforested habitats (Estimate\\u0026thinsp;=\\u0026thinsp;0.633, p\\u0026thinsp;=\\u0026thinsp;0.048), but non-significant across the other habitat types. Hill numbers (q1 and q2; Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003e) confirmed this pattern: Afforested habitats exhibited significant baseline diversity (Hill_q1: Estimate\\u0026thinsp;=\\u0026thinsp;1.547, p\\u0026thinsp;=\\u0026thinsp;0.006; Hill_q2: Estimate\\u0026thinsp;=\\u0026thinsp;1.195, p\\u0026thinsp;=\\u0026thinsp;0.015), whereas Agroforestry, Bushland, and Shrubland did not differ significantly from the reference. Overall, Afforested habitats supported consistently higher insect diversity, while other habitats showed no meaningful deviations from this baseline.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab7\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 7\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results evaluating the effect of habitat type on Shannon diversity of insects.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEstimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eStd. error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eStatistic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep.value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.514\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.316\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.794\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.009***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.058\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.447\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.129\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.904\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.265\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.448\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.592\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.586\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.207\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.447\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.464\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.667\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003e\\u003cb\\u003eNotes\\u003c/b\\u003e: \\u003cem\\u003eThe intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not show statistically significant differences compared to the baseline (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab8\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 8\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results assessing the effect of habitat type on Simpson diversity of insects.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEstimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eStd. error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eStatistic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep.value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.633\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.320\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.976\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.048**\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.381\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.444\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.857\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.392\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.128\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.457\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.280\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.780\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.226\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.461\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.492\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.623\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003eNotes: \\u003cem\\u003eThe intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not show statistically significant differences compared to the baseline (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab9\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 9\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results for Hill q₁ diversity indices across habitat types.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEstimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eStd. error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eStatistic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep.value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.547\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.293\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.282\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.006***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.054\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.414\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.131\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.902\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.246\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.414\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.593\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.585\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.174\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.414\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.420\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.696\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003eNotes: \\u003cem\\u003eThe intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not exhibit statistically significant differences compared to the baseline (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab10\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 10\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGeneralized Linear Model (GLM) results for Hill q₂ diversity indices across habitat types.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHabitat Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEstimate\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eStd. error\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eStatistic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep.value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e(Intercept)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.195\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.294\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.058\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.015**\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgroforestry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.046\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.416\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-0.111\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.917\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBushland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.074\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.416\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.179\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.867\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eShrubland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.176\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.416\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.423\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.694\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003eNotes: \\u003cem\\u003eThe intercept represents baseline habitat diversity (afforested), while agroforestry, bushland, and shrubland habitats did not exhibit statistically significant differences compared to the baseline (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1 Species abundance\\u003c/h2\\u003e \\u003cp\\u003eFindings indicate that the abundance is highest in afforested areas, followed by agroforestry areas, and lowest in bushland areas. Unlike afforested and agroforestry sites, where trees and crops are artificially managed to prevent predator development, the presence of insect predators in the bushy area may be responsible for the low insect numbers in the bushland. The findings of the present study are in contrast with those of a study by [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]which claimed that converting natural ecosystems to alternative land uses leads to declines in insect populations. According to [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] and [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e], afforestation, however, provides microhabitats for a variety of faunal species, including insects. Further literature explains that variations in environmental conditions, the time of year when insects were collected, and the presence of vulnerable hosts in the research location can all be linked to variations in observed abundance. [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2 Species richness\\u003c/h2\\u003e \\u003cp\\u003eAccording to this study, shrubland had the highest species richness while agroforestry had the lowest. Compared with young afforested and agroforestry ecosystems, the shrubland ecosystem is more complex and has several feeding niches, which are major contributors to its higher species richness. In his study on the impact of afforestation on coleopteran abundance and diversity, [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e], reported similar findings. He said that the shrubland's omnivorous, phytophagous, and predatory beetle species all lived there, making the environment more stable. Similar to this observation,[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e] and[\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e] high insect species richness as a sign of a more complex food web structure, which is frequently associated with established and stable ecosystems.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3 Species diversity\\u003c/h2\\u003e \\u003cp\\u003eThe shrubland and afforested areas had the highest insect diversity, whereas the bushland and agroforestry sites had the lowest. This pattern may be explained by the availability of a variety of resources, such as food for various species, and by the shrubland's more favorable environment for more species than at the other sites. It is important to keep in mind that areas planted solely with trees have lower layers covered in grasses and other shorter plants that resemble shrubland. According to a study by [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e], maintaining a diverse understory of native species increases wildlife populations and ecological diversity. Despite access to a variety of resources, agroforestry is considered to support a limited number of insect species. This can be explained by various factors, such as the age of the trees, frequent management measures that disrupt some species, leading to their emigration or relocation to surrounding areas [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe bushland and shrubland had higher evenness indices than the agroforestry and afforested areas, which both had lower evenness. This finding indicates that some species are more dominant in agroforestry and wooded areas due to resource conditions that favor them. For instance, \\u003cem\\u003ePachycondyla tarsata\\u003c/em\\u003e, \\u003cem\\u003eLepisiota\\u003c/em\\u003e spp., and \\u003cem\\u003eAraneae\\u003c/em\\u003e spp. appear to have high dominance in bushland, agroforestry, and planted areas, respectively. According to the study's findings, shrubland has a lower species dominance index than agroforestry (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). Lower species evenness and diversity in agroforestry are a result of the inverse relationship between the dominance index and other diversity indices. This finding is consistent with a study by [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e], which found that coleopteran evenness was higher in grasslands and lower in a three-year tree plantation. In addition, a study by[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] produced findings that were similar to those of the current study. The study claims that many species of Scarabaeidae and Scarabaeinae preferred wooded patches, such as bushland, over grassland and cultivated sites in semi-arid Tanzania, resulting in greater species richness and evenness.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.4 Effects of habitats on species abundance and diversity\\u003c/h2\\u003e \\u003cp\\u003eTo assess the impact of each site on the insect abundance and diversity, a correlation test was conducted. The findings revealed a favorable relationship between shrubland and agroforestry in terms of insect abundance. This shows that while afforested and bushland areas lead to a decline in insect abundance, agroforestry and shrubland areas increase it. Ecologically, agroforestry is an agroecosystem composed of numerous components that are coordinated to provide diverse microhabitats, which, in turn, support a variety of insect species. According to[\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e] microhabitats that were ideal for many different beetle species. This study's findings, which suggested that afforested areas may negatively affect insect abundance, are at odds with these findings. This deviation can be explained by the fact that the age of the afforested site matters for insect abundance and distribution [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. Interestingly, only the afforested site had a significant positive influence on insect diversity indices, meaning that although afforestation harbors a small total number of species, these species are distributed across many insect taxa. This might be contributed to by the presence of a few predators in the newly established afforested sites. On the other hand, shrublands are characterized by numerous niches due to the variety of vegetation structures and the ecosystem's age [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. Overall, the gradient in diversity metrics (Shrubland\\u0026thinsp;\\u0026gt;\\u0026thinsp;Bushland\\u0026thinsp;\\u0026gt;\\u0026thinsp;Afforested\\u0026thinsp;\\u0026gt;\\u0026thinsp;Agroforestry) suggests that more structurally complex or less intensively managed habitats support richer and more even insect communities. Similar findings were reported by [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e], who claimed that animal and insect species diversity has been shown to correspond to the structural complexity of habitats and the diversity of vegetation forms.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"5. Conclusion\",\"content\":\"\\u003cp\\u003eOf the four study locations, the agroforestry site had the second-highest insect abundance, but it had low overall insect species diversity, species richness, and evenness. Also, across the three locations, agroforestry showed the highest level of species domination. The correlation analysis, however, revealed a strong association between agroforestry and insect abundance, indicating that agroforestry helps boost insect populations. Findings also demonstrate that agroforestry approaches may offer an environment conducive to insect survival and reproduction. The dominance of some species, such \\u003cem\\u003ePachycondyla tarsata\\u003c/em\\u003e, which was discovered to be extremely common in agroforestry, reveals this. The age of the ecosystem and management strategies were found to affect insect diversity and abundance. Although our study provides robust baseline data, seasonal variation and functional diversity were not assessed. Future research should explore how insect diversity translates into ecosystem services such as pollination and nutrient cycling, and how agroforestry practices within semi-arid areas can be optimized to balance biodiversity conservation with household livelihoods.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch3\\u003eAcknowledgments.\\u003c/h3\\u003e\\n\\u003cp\\u003eThe authors of this work are grateful to the University of Dodoma for letting us carry out this investigation on one of its properties. They also acknowledge the assistance from the Department of Biology, notably during data collection and analysis.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eJ.M.M designed and conducted the study, collected and analyzed the data, and drafted the manuscript. K.N and N.M provided ongoing guidance, critical feedback, and substantial revisions throughout the development of the manuscript. All authors read and approved the final version.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data are available upon request.\\u003c/p\\u003e\\n\\u003ch3\\u003eEthics approval and consent to participate: Not applicable. \\u003c/h3\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eThis study involved only invertebrate insects. Ethical approval was therefore not required. Field sampling was conducted in accordance with local regulations and standard entomological practices. No vertebrate animals were involved.\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNot applicable.\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA\\u003cem\\u003euthors have no financial or non‑financial competing interests to declare in regard to this study.\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent to Publish\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eAll the authors have agreed to the publication of the manuscript\\u003c/em\\u003e\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eMusgrave E. \\u003cem\\u003eAn Ecological Assessment of Insect Diversity at Organic Central Coast Vegetable Farms on Two Spatial Scales\\u003c/em\\u003e. 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Open J Ecol. 2015;05:352\\u0026ndash;60.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Agroforestry, Insects’ abundance, Insect diversity, semi-arid ecosystems\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9232955/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9232955/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThis study investigated insect diversity and abundance to understand how agroforestry impacts biodiversity in transformed semi-arid ecosystems. Insects were collected using pitfall traps across areas with only trees (afforested), areas practicing agroforestry (agroforestry), areas with few remaining shrubs (shrubland), and untouched bushy areas (bushland). A total of 2,889 insects were collected. Shrubland had the lowest insect abundance but the highest diversity, while afforested land showed the highest abundance. Despite differences in diversity and richness, statistical tests revealed no significant variation among sites. Agroforestry had lower species diversity and richness compared to shrublands. Evenness was higher in bushland than in agroforestry and shrubland. These results suggest that agroforestry supports more insects but fewer species, possibly due to management practices and the type of trees integrated, which might favor specialist species. Further research is needed to understand how age and agroforestry components influence insect diversity in semi-arid regions.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Effects of Agroforestry Practices on Insect Conservation in Transformed Ecosystems of the Semi-Arid Area, Dodoma, Tanzania\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-04-24 07:01:39\",\"doi\":\"10.21203/rs.3.rs-9232955/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"13299d09-5ba6-48d5-82d6-600e665fcb87\",\"owner\":[],\"postedDate\":\"April 24th, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"decision\",\"content\":\"Rejected\",\"date\":\"2026-05-07T15:00:42+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-07T15:11:14+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-04-24 07:01:39\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9232955\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9232955\",\"identity\":\"rs-9232955\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}