DOI: 10.5061/dryad.jwstqjqm5
title: Land use and cover changes and sand fly (Diptera: Psychodidae) assemblages in an emerging focus of leishmaniasis

description: The dataset documents the relationship between changes in land use and
 occupation and the diversity and abundance of phlebotomines, the vectors
 of leishmaniasis, in a rural area of the municipality of Codó, Maranhão.
 It integrates spatial and entomological information collected between 2012
 and 2023, providing a comprehensive basis for environmental,
 epidemiological and vector management analyses. The land use and
 occupation data was obtained from Sentinel-2 satellite images, processed
 in QGIS software (version 3.10) and classified using the Orfeo Toolbox
 Processing (OTB) tool. The images represent the years 2012, 2014, 2021 and
 2023 and include variables such as the density and fragmentation of
 vegetation cover, as well as the expansion of built-up areas. This
 information was made available in geospatial formats, such as Geotiff and
 shapefiles, allowing detailed analysis of temporal changes in the
 landscape. Entomological data was collected bimonthly between August 2022
 and June 2023. Phlebotomines were captured using CDC and Shannon traps
 (white and black) installed in peri- and extra-domicile environments. The
 set includes information on species identification, number of individuals
 captured by trap type and environment, as well as data on total and
 relative abundance. This data is organized in CSV files and descriptive
 reports. A total of 3,375 phlebotomines were captured, of which
 Psychodopygus wellcomei was the most abundant species (78.19%), followed
 by Nyssomyia whitmani (7.53%). Ny. whitmani predominated in the
 peridomicile (84.97%), while Ps. wellcomei was more frequent in the
 extradomicile (96.51%). This set of data is of high scientific relevance,
 providing unprecedented support for studies on the relationship between
 habitat fragmentation and disease vector dynamics. It also has great
 potential for reuse and can be applied in various areas, such as public
 health planning, teaching and research. It can support the development of
 vector surveillance and control strategies, as well as serving as a basis
 for predictive models of leishmaniasis transmission. The data is made
 available in accordance with ethical and legal standards. It does not
 include sensitive or identifiable information about human beings,
 guaranteeing compliance with applicable legislation. The entomological
 collections were carried out with the authorization of regulatory bodies
 and in compliance with Brazilian environmental legislation. To access the
 data, it is necessary to request permission and ensure proper citation of
 the original study. This dataset is a valuable resource for understanding
 the interactions between anthropogenic changes in the landscape and vector
 dynamics. It offers insights into environmental impacts and enables more
 effective approaches to leishmaniasis control in tropical rural areas,
 contributing to the advancement of public health and environmental
 conservation policies.
description: <strong>Study area</strong> This
 study was conducted in the Santana IV rural settlement, Codó (04°27′12.8″S
 43°53′01.7″W), Eastern Mesoregion of Maranhão State, Brazil (Figure 1).
 The municipality has an area of 4364.5 km<sup>2</sup> and an
 estimated population of 114,275 people, with a population density of 26.20
 people/km<sup>2</sup> (IBGE, 2022). Vegetation cover varies
 according to relief characteristics, proximity to watercourses, and the
 extent of anthropic transformations. The predominant vegetation type is
 open forest/babassu forest, occupying the entire valley of the Itapecuru
 River. The main tree species are babassu palm (<em>Attalea
 speciosa</em> Mart. ex Spreng.) and carnauba [<em>Copernicia
 prunifera</em> (Miller) H.E.Moore]. Another common type of
 vegetation cover is <em>campo cerrado</em>, found mainly in
 the east, northwest, and southwest parts of the municipality (Correia
 Filho et al., 2011a). The climate is semi-humid,
 transitioning to semi-arid with precipitation. According to the Köppen
 classification, the climate is of the Aw type, with rainy summers and dry
 winters. The driest month has less than 60 mm rainfall. Temperatures in
 the coldest month remain above 18 °C. The annual average temperature is
 about 27 °C, and the maximum temperature is 36 °C. Air humidity reaches
 high values during the rainy season, indicating that this parameter is
 directly related to the rainfall regime of the region. The average annual
 rainfall is approximately 1200 mm, with the wettest quarter being January,
 February, and March (Lima, 1998; Correia Filho et al., 2011b).
 Five sampling points were located in peridomestic environments
 (Animal shelter backyard): P1 (04°55′062″S 043°89′450″W), P2 (04°55′402″S
 043°89′822″W), P3 (04°55′474″S 043°90′048″W), P4 (04°54′959″S
 043°90′936″W), and P5 (04°55′161″S 043°91′053″W). These areas were close
 to houses, debris, and waste. The soil was moist, and various domestic
 animals were observed, such as dogs, cats, pigs, cattle, chickens,
 guineafowl (<em>capotes</em>), horses, and geese. Samplings
 were also performed in extradomestic environments located at least 500 m
 away from peridomestic sampling points. Extradomestic environments were
 characterized by primary forests (fragmented) with the presence of fruit
 trees (cashew and mango trees) and shaded soil, with the presence of wet
 litter and bogs in the vicinity of the Saco River.  
 <strong>Sand fly collection and
 identification</strong> Sand flies were captured
 at the five sampling points (P1 to P5) in the dry (August to December
 2022) and wet (February to June 2023) periods. In alternate months, two
 Centers for Disease Control and Prevention (CDC) light traps were
 installed per sampling point, one in a peridomestic environment (near
 residences where animals are raised) and another in an extradomestic
 environment (within a fragment of closed vegetation), totaling 10 traps.
 Traps were kept in the field for two consecutive nights, being installed
 at 18:00 h and removed the next day at 6:00 h. Active sampling was
 performed from 18:00 to 21:00 h using white and black Shannon traps
 (Galati et al., 2001). Captured sand flies were taken
 to the Medical Entomology Laboratory, Caxias Campus, Maranhão State
 University (UEMA), for sex discrimination, clearing, and dissection. All
 collected sand flies (males and females) were dissected by removing the
 head, thorax, and the last three segments of the abdomen and mounted on a
 glass slide with Canada balsam for species identification. The rest of the
 body was individually stored dry at −20 °C in a 1.5 mL tube for future
 molecular studies. Species were identified using the updated version of
 the classification system proposed by Galati (2024). Genus abbreviations
 follow Marcondes (2007). <strong>Data
 analysis</strong> For the time-scale analysis of
 land use and cover in the Santana IV settlement, Sentinel 2 satellite
 imagery was acquired over sand fly sampling points in 2012, 2014, 2021,
 and 2023. Images were downloaded from the LandView website. The analyzed
 years were chosen because they were within a 12-year time frame. Image
 treatment for visualization of landscape changes was carried out using
 Quantum GIS (QGIS) software free version 3.10 based on image features and
 characteristics. Shapefile files were obtained from the Brazilian
 Institute of Geography and Statistics (IBGE) database to delimit sampling
 points. Orfeo Toolbox, an open-source project native to QGIS for
 state-of-the-art remote sensing, was used to classify images. Developed by
 the open-source geospatial community, Orfeo Toolbox can process
 high-resolution optical, multispectral, and radar images on a terabyte
 scale. For analysis of sand fly assemblages, relative
 abundance was estimated as a percentage of the total number of collected
 individuals. Species richness was estimated from the number of identified
 species. The abundance and diversity of sand flies captured in the dry and
 wet seasons in peridomestic and extradomestic environments were measured
 by the Shannon diversity index (SHDI). Cluster analysis was performed to
 compare the composition of sand fly populations between dry and wet
 periods based on the presence and absence of species, using Jaccard's
 similarity index (Ludwig & Reynolds, 1988). Rarefaction curves for
 the dry and wet periods were constructed by extrapolating the expected
 number of species to larger sample sizes. These curves were used to
 estimate species richness in each period and compare the completeness of
 samples. The effects of temperature, relative humidity, peridomestic
 conditions, and extradomestic conditions on abundance and diversity were
 examined using generalized linear mixed models (GLMMs) at the 5%
 significance level. Temperature (°C) and relative humidity (%) were
 measured by using a digital thermohygrometer (IHT-2200, Instrutemp) at
 each sampling point when traps were installed and removed. The constancy
 index (CI) was calculated by the equation CI = <em>P</em> ×
 100/<em>N</em>, where <em>P</em> is the number of
 collections in which the species was present and <em>N</em> is
 the total number of months in which the species was collected. CI values
 were used to group species into three categories: constant (CI
 <strong>≥ </strong>50%), accessory (25% &lt; CI &lt;
 50%), and accidental (CI ≤ 25%) (Silveira Neto et al., 1976). Data
 analysis was conducted using specific packages for R software version
 4.3.1 (2023).
 <strong>REFERENCES</strong>
 Correia Filho, F. L., Gomes, É. R., Nunes, O. O., & Lopes
 Filho, J. B. (2011a). <em>Projeto cadastro de fontes de
 abastecimento por água subterrânea: estado do Maranhão: relatório
 diagnóstico do município de Codó</em>. CPRM. Available from:  https://rigeo.sgb.gov.br/handle/doc/15443 Correia Filho, F. L., Gomes, É. R., Nunes, O. O., & Lopes Filho, J. B. (2011b). <em>Projeto cadastro de fontes de abastecimento por água subterrânea: estado do Maranhão: relatório diagnóstico do município de Açailândia</em>. CPRM. Available from: https://rigeo.sgb.gov.br/handle/doc/15303 Galati, E. A. B. <em>Phlebotominae (Diptera, Psychodidae): Classificação, morfologia, Terminologia e Identificação De Adultos, Apostila – Disciplina PSP5127-1 Bioecologia e Identificação De Phlebotominae</em>. Public Heath School. University of São Paulo, 2024. Available from: https:/www.fsp.usp.br/egalati/        Galati, E. A. B., Nunes, V. L. B., Dorval, M. E. C., Cristaldo, G., Rocha, H. C., Gonçalves-Andrade, R. M., & Naufel, G. (2001). Attractiveness of black Shannon trap for phlebotomines. <em>Memórias do Instituto Oswaldo Cruz</em>, <em>96</em>(5), 641-647. Available from:  https://doi.org/10.1590/S0074-02762001000500008 IBGE. Instituto Brasileiro de Geografia e Estatística. (2022). <em>Censo Demográfico</em>. Available from: https://www.ibge.gov.br/cidades-e-estados/ma.html Lima, A. A. C. (1998). Solos e aptidão edafoclimática para a cultura do cajueiro no município de Codó, Maranhão. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Centro Nacional de Pesquisa de Agroindústria Tropical Ministério da Agricultura e do Abastecimento. Comunicado Técnico, (16), 1 – 4. Available from: https://ainfo.cnptia.embrapa.br/digital/bitstream/CNPAT-2010/5349/1/Ct-016.pdf Ludwig, J. A., & Reynolds, J. F. (1988). <em>Statistical ecology: a primer in methods and computing</em> (Vol. 1). John Wiley & Sons. Available from: https://books.google.com.br/books?hl=pt-BR&lr=&id=sNsRYBixkpcC&oi=fnd&pg=PA3&dq=LUDWIG,+J.A.%3B+REYNOLDS,+J.F.+Statistical+ecology:+a+primer+on+methods+and+computing.+Wiley,+New+York,+1988&ots=mEzObVU5uW&sig=VF-GQi8tSxMRmcnu1ebpi3dLhMw#v=onepage&q=LUDWIG%2C%20J.A.%3B%20REYNOLDS%2C%20J.F.%20Statistical%20ecology%3A%20a%20primer%20on%20methods%20and%20computing.%20Wiley%2C%20New%20York%2C%201988&f=false Marcondes, C. B. (2007). A proposal of generic and subgeneric abbreviations for phlebotomine sandflies (Diptera: Psychodidae: Phlebotominae) of the world. <em>Entomological News</em>, <em>118</em>(4), 351-356. Available from: https://doi.org/10.3157/0013-872X(2007)118[351:APOGAS]2.0.CO;2 Silveira-Neto, S., Nakano, O., Barbin, D., & Villa Nova, N. A. (1976). Manual de ecologia dos insetos. Agronômica Ceres. Available from:  https://books.google.com.br/books/about/Manual_de_ecologia_dos_insetos.html?hl=pt-PT&id=4XPuGwAACAAJ&redir_esc=y
description: # Land use and cover changes and sand fly (Diptera: Psychodidae)
 assemblages in an emerging focus of leishmaniasis
 [https://doi.org/10.5061/dryad.jwstqjqm5](https://doi.org/10.5061/dryad.jwstqjqm5) ## Description of the data and file structure **README: Sand fly survey data and statistical analysis** We sent the table with the data from the phlebotomine species survey (**Sand_fly_survey_results_table.zip**), the data used in the statistical analyses (**raw_data_analyzes_statistics.zip**), data used to generate graphs (**Dados_para_gráficos.xlsx**) and a summary of the data generated from the statistical analyses (**summary_phlebotomine_results_statistical_analysis.zip**). Descriptions **Sand_fly_survey_results_table.zip** * Species: currently accepted scientific names of sand fly species; * ♂: Male gender symbol; * ♀: Female gender symbol; * N: Number of specimens; * Capture method: Capture methods used to obtain phlebotomine species; **raw_data_analyzes_statistics.zip (Raw_data_number_of_fleb_shdi; Raw_data_number_of_fleb_data; statistical_analysis_phlebotomine_survey_cdct_summ_trap; statistical_analysis_phlebotomine_survey_shan_summ_trap)** * In this file there are four spreadsheets with the data from the statistical analysis in spreadsheets generated by the R program, evaluating the diversity and abundance of sandflies, sandflies/date, and sandflies/temperature and humidity. * **Raw_data_number_of_fleb_shdi**: The data provided refers to ecological and environmental measurements and analyses. Below is a description of the columns and what they represent: **Month:** Represents the month in which the data was collected (example: April, August, December, February). **Method**: Identifies the method used to collect the data (example: CDC or Shannon, probably referring to traps or sampling methods). **Perimeter**: Can indicate the location or configuration of the collection point (example: Extra or Peri, which can mean “extradomiciliary” and “peridomiciliary”). **Color**: Refers to a specific characteristic of Shannon's method, the color of the trap (example: White or Black). **SHDI**: Shannon Diversity Index, used to measure species diversity. **Temperature**: Indicates the average temperature recorded at the time of collection (in °C, example: 29.1, 28.9). **Humidity**: Indicates the relative humidity of the air (in %, example: 76.7, 55.8). **Abundance**: Total number of individuals collected (example: 136, 113). **Season**: Identifies the season (rainy or dry). * **Raw_data_number_of_fleb_data**: The data presented is intended to characterize the capture and identification of sandflies: **Point**: Represents the specific place or point where the collection was made (example: Point 1). **Month**: Indicates the month in which the collection took place (example: April, August). **Method**: Refers to the capture method used (example: CDC, which is a type of trap). **Perimeter**: Identifies the location relative to the human environment, such as Extra (extradomiciliary) or Peri (peridomiciliary). **Color**: Contains no values in the data presented (NA), but can be used to categorize traps of different colors. **Species**: Indicates the species of phlebotomine captured (e.g. Brumptomyia brumpti, Psychodopygus série chagasi). **Sex**: Specifies the sex of the specimen captured (F for female, M for male). **Temperature**: Records the average temperature at the time of collection (in °C, example: 29.1, 28.9). **Humidity**: Indicates the relative humidity of the air during collection (in %, example: 76.7, 55.8). **Abundance**: Number of specimens collected of the species in question (example: 1, 3). * **statistical_analysis_phlebotomine_survey_cdct_summ_trap:** The data presented aims to characterize the capture and identification of sandflies. **Point**: Represents the specific place or point where the collection was made (example: Point 1). **Month**: Indicates the month in which the collection took place (example: April, August). **Method**: Refers to the capture method used (example: CDC, which is a type of trap). **Perimeter**: Identifies the location relative to the human environment, such as Extra (extradomiciliary) or Peri (peridomiciliary). **Color**: Contains no values in the data presented (NA), but can be used to categorize traps of different colors. **Species**: Indicates the species of phlebotomine captured (e.g. Brumptomyia brumpti, Psychodopygus série chagasi). **Sex**: Specifies the sex of the specimen captured (F for female, M for male). **Temperature**: Records the average temperature at the time of collection (in °C, example: 29.1, 28.9). **Humidity**: Indicates the relative humidity of the air during collection (in %, example: 76.7, 55.8). **Abundance**: Number of specimens collected of the species in question (example: 1, 3). * The data includes the identification of phlebotomine species, including some classified as “unidentified” or genus (Nyssomyia sp.). * Environmental conditions (temperature and humidity) are detailed, allowing correlation with species abundance and diversity. * The sex categories allow analysis of the proportion of males and females in the samples. **statistical_analysis_phlebotomine_survey_shan_summ_trap** * Color: Category based on color. Black: Color “black”. White: Color “white”. Season: Season of the year. Dry: Dry season. Wet: Rainy season. Variable: Variables analyzed. SHDI: Shannon Diversity Index (species diversity). Temperature: Average temperature (°C). Humidity: Relative humidity (%). Abundance: Number of individuals collected. **n**: Number of samples analyzed (always 3). Statistical measures **min**: Minimum value. **max**: Maximum value. **median**: Median (central value of the data). **q1** (Quartile 1): Value below which 25% of the smallest values lie. **q3** (Quartile 3): Value below which are 75% of the smallest values. **iqr** (Interquartile Range): Difference between the third and first quartile (q3 - q1). **mad** (Median Absolute Deviation): Dispersion around the median. **mean**: Average of the values. **sd** (Standard Deviation): Variability of the data around the mean. **se** (Standard Error): Error in estimating the mean. **ci** (Confidence Interval): Interval within which the true mean should lie. Summary and Observations **SHDI (Shannon Diversity Index):** **Black**: Lower diversity in the Wet season, with average values of 0.62, indicating less variation in species. Higher diversity in the dry season (Dry), with an average of 1.067. **White**: Slightly higher diversity in the rainy season (Wet) compared to Black, but lower in the dry season, with average values of 0.616 (Wet) and 1.153 (Dry). **Temperature**: No great variations between seasons and colors, with averages around 28°C for both categories. **Humidity**: Significantly higher in the rainy season, ranging from 57.9% (Dry) to 64.2% (Wet) for both colors. **Abundance:** **Black**: Dry season: Low abundance, with an average of 7.5 individuals. **Rainy season**: Extremely high values (average of 653,333 individuals), showing marked seasonality. **White**: Dry season: Higher abundance than Black, with an average of 25,667 individuals. **Rainy season**: Increased abundance, but still lower than Black, with an average of 158,333 individuals. **The data shows that:** **Seasonality**: The rainy season is associated with greater humidity and abundance of individuals, especially for the Black group. **Diversity**: Species diversity (SHDI) tends to be higher in the dry season, regardless of color, suggesting that more generalist species dominate in the rainy season. **Difference by Color**: Black shows greater abundance in the rainy season, while White has greater relative diversity (SHDI) in the dry season. **Data_for_graphing.xlsx** * **Spreadsheet 1 (Planilha1)**: The data presented describes the relative distribution (%) of different phlebotomine species between the peridomiciliary (near human dwellings) and extradomiciliary (outdoor and wild areas) environments. A detailed analysis follows: \- The proportions reflect the predominance of each species in one or both environments. -Some species have an exclusive distribution in one environment, while others are present in both. * **Spreadsheet 2 (Planilha2)**. The data presented describes the relative abundance (%) of phlebotomines during different months of the year (August, October, December, February, April and June), as well as the percentage constancy index (%CI) for each species. A detailed analysis follows: -Constancy Index (CI%): Reflects the frequency with which each species was recorded throughout the year. Species with a high CI% (≥ 50%) are considered constant, while lower values indicate accidental or accessory species. -Monthly Distribution: Shows the seasonality of each species. * **Spreadsheet 3 (Planilha3).** Phlebotomine density **Peak in April/2023**: The density reached 2142 (64.4% of the total), suggesting that this is the month of greatest phlebotomine activity. **Lowest in August/2022**: Only 83 (2.5%), indicating low activity during this period. Seasonal pattern: **Gradual increase**: From August/2022 to February/2023, there was a progressive increase in density. **Decrease after April**: In June/2023, density fell to 409. Temperature (°C) **Limited variation**: Temperature values fluctuate between 28°C and 30°C, with no significant changes. The average annual temperature is approximately 28.67°C, suggesting that there has not been much direct influence of this variable on density. Relative humidity (%) **Increase in humidity and density**: Phlebotomine density increases remarkably between February (74%) and April (77%), accompanied by an increase in humidity. April/2023, with the highest density (2142), also has the highest humidity value (77%). Drop in June: Humidity reaches its lowest value (42%), coinciding with the drop in density (409). **summary_phlebotomine_results_statistical_analysis.xlsx** * In summary form, the spreadsheet shows the results of the formulas used in the R program to verify the relationship between phlebotomine diversity, abundance and uniformity and collection environments. * Model family: Generalized Poisson (link = log). Formula: Abundance ~ Season + Perimeter + Temperature + Humidity + (1 | Month) Dependent variable: Abundance (phlebotomine count). Independent variables: Season: Comparison between rainy and dry periods. Perimeter: Local (Peridomicile vs Extradomicile). Temperature: Values in °C. Humidity: Percentage. Random effect: Included for the “Month” factor.           Missing data: NA **Code/Software** R is required to obtain the data summary_phlebotomine_results_statistical_analysis.zip; Microsoft Excel can be used to visualize Sand_fly_survey_results_table.zip, raw_data_analyses_statistics.rar, Data_for_graphics.xlsx and summary_phlebotomine_results_statistical_analysis.zip; for this one Images_of_the_data_and_statistical_analysis.zip any image viewer can be used.