Citizen Science Databases and Entomological Collections: Insights into Environmental Ranges and Potential Distribution of Gonzaga McLachlan, 1867 (Chrysopidae, Neuroptera)

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Biological collections and citizen science databases were pivotal in compiling distribution records, revealing novel data for several species. For instance, Gonzaga nigriceps was recorded for the first time in Northeastern Brazil, while Gonzaga palliceps had new records in the Federal District and São Paulo. Gonzaga torquatus extended its range to Colombia, Honduras, and Mexico. The study employed ecological niche models to infer the potential distribution of these species, highlighting areas of high environmental suitability in ecosystems such as moist and dry tropical forests, mangroves, and savannas. The analyses identified areas of high environmental suitability for the studied species, particularly in the Neotropical region, while also pinpointing knowledge gaps and unexplored potential habitat areas, such as in the subantarctic region of Patagonia. These findings are crucial for conservation, providing insights into the ecological requirements of the species and guiding preservation strategies in priority areas. The study underscores the ongoing importance of citizen science initiatives and the strengthening of biological collections for understanding and safeguarding Neotropical biodiversity, especially amidst climate change and habitat loss. This work contributes not only to the knowledge of Gonzaga species distributions but also to the application of predictive models in biodiversity, evolutionary, and conservation studies, encouraging future field research to validate the models and expand our understanding of these unique components of Neotropical biodiversity. citizen science conservation distribution modelling Leucochrysini Neuropterida Figures Figure 1 Figure 2 Introduction Estimates suggest that approximately 3 billion specimens have been accumulated over 250 years in natural history collections and museums (Arinõ 2010; Smith and Blagoderov 2012 ). These collections are vital repositories of data on biodiversity, ecology, behavior, biological interactions, and bionomics (Pérez-Lachaud and Lachaud 2017 ). They preserve unidentified specimens from historical expeditions or biological material that is now inaccessible due to collection challenges or landscape changes (Funk 2018 ). These collections form the foundation for understanding historical habitat changes, species distributions, and the effects of climate change in biodiversity studies (Lister 2011 ; Pérez-Lachaud and Lachaud 2017 ; Santos and Hoppe 2018 ). This extensive database supports numerous studies, providing crucial data for models and predictions of species distribution, phenological patterns, ecological models, and future impacts (Pérez-Lachaud and Lachaud 2017 ). Arthropods, particularly insects, are abundant in biological collections due to their small size, ease of collection and storage, and biodiversity representativeness (Kharouba et al. 2018 ). Insects play key roles in ecosystem functions and services vital to life and human well-being in terrestrial and freshwater ecosystems (Dangles and Casas 2019 ). Their richness, accounting for 50 to 70% of all described species, and their ecological roles mean that maintaining viable insect populations and understanding their biodiversity directly impacts agriculture, public health, natural resource use, and conservation (Dangles and Casas 2019 ). Despite their importance, insect population declines are increasingly evident due to anthropogenic landscape changes (Boyes et al. 2021 ; Wagner et al. 2021 ). There is also a silent extinction (Eisenhauer et al. 2019 ), with over 40% of insect species threatened with extinction (Sánchez-Bayo and Wyckhuys 2019 ), and some species going extinct before being formally described. The Neuroptera, a neglected but important insect order, is the most species-rich and habitat-diverse group within Neuropterida (Oswald and Machado 2018 ). They inhabit freshwater environments with bryozoans and sponges, and various terrestrial environments. Most larvae are generalist predators, with specialized mantispids targeting wasp nests and spider eggs (Contreras-Ramos and Rosas 2004). Chrysopidae adults are used in agricultural pest control (Oswald and Machado 2018 ). Among the Chrysopidae, the genus Gonzaga Navás, with eight described species, is the second largest in the tribe Leucochrysini in the New World (Tauber et al. 2008 ), with species distributed from Mexico to Brazil (Brooks and Barnard 1990 ). Records are concentrated in northwestern South America and southeastern Brazil (Table 1 ). Little is known about the distributional range, characterized by disjointed and sparse distribution records (Tauber et al. 2008 ). Table 1 Distributional records of Gonzaga species, locality, coordinates and references Species Locality Latitude Longitude Gonzaga amabilis 12 Ecuador: Rio Peripa -0.74167 -79.60000 Gonzaga callipterus 3 Brazil: Amazonas, Parintino [Parintins?] -2.60000 -56.73300 Gonzaga callipterus 3 Guyana: Gt. Falls 5.17651 -59.48075 Gonzaga nigriceps 14 Brasil: Rio de Janeiro, Magé -22.57333 -43.02570 Gonzaga nigriceps 14 Brazil: Alagoas, Pilar -9.60844 -35.91031 Gonzaga nigriceps 4 Brazil: Amazonas - [Vila de] Ega -3.33515 -64.71173 Gonzaga nigriceps 15 Brazil: Bahia, Camacan, RPPN Serra Bonita, Malaise 1 -15.39336 -39.56464 Gonzaga nigriceps 10 Brazil: Espírito Santo, Anchieta Restinga da APA Municipal da tartaruga -20.72139 -40.78139 Gonzaga nigriceps 15 Brazil: Pernambuco, Paulista, Aldeia KM14, Granja do Delegado, Ponto do Riacho -7.91900 -35.01900 Gonzaga nigriceps 15 Brazil: Pernambuco, Recife, Dois Irmãos, Ponto Morro -8.00547 -34.94208 Gonzaga nigriceps 13 Brazil: Rio de Janeiro - Conceição de Maracabu, Fazenda Carrapeta -22.16667 -41.86667 Gonzaga nigriceps 13 Brazil: Rio de Janeiro - Parque Estadual Desengano, Fazenda Babilônia -21.85000 -41.80000 Gonzaga nigriceps 13 Brazil: Rio de Janeiro - Parque Estadual Desengano, Sta. M. Madalena, Terras Frias -21.91667 -41.91667 Gonzaga nigriceps 13 Brazil: Rio de Janeiro - Sta. M. Madalena, Fazenda Sto Antônio de Imbé -22.00000 -41.86667 Gonzaga nigriceps 4 Brazil: Santa Catarina, Blumenau -26.93300 -49.05000 Gonzaga nigriceps 13 Colombia: Amazon - Letícia -4.20062 -69.94860 Gonzaga nigriceps 3 Guyana: [probable Gt. Falls, British Guiana, same collector and mouth of collection] 5.17651 -59.48075 Gonzaga nigriceps 4 Peru: Saracayon [probable Sarayacu sensu Hebard, 1923] -6.73300 -75.10000 Gonzaga nigriceps 3 Venezuela: Bolívar - Paraytepuy 4.63300 -61.50000 Gonzaga notatus 9 Peru: Iquitos -3.74800 -73.24700 Gonzaga palliatus 9 Brazil: Espirito Santo -20.00000 -40.75000 Gonzaga palliceps 5, 6 Brazil: Amazonas - [Vila de] Ega -3.33515 -64.71173 Gonzaga palliceps 14 Brazil: Brasília, Asa Norte Superquadra Norte 314 BL -15.74593 -47.89558 Gonzaga palliceps 14 Brazil: São Paulo, Laranjal Paulista -23.10740 -47.81675 Gonzaga palliceps 8 Costa Rica: Ebene von Limon bei Las Mercedes 10.16700 -83.61700 Gonzaga palliceps 11 Costa Rica: Límon, Hitoy Cerere Biological Reserve 9.64215 -83.08121 Gonzaga palliceps 11 Costa Rica: Límon, Pandora 9.73300 -82.96700 Gonzaga palliceps 8 Costa Rica: Limón, Reventazon (Hamburg Farm) 10.24646 -83.46421 Gonzaga palliceps 11 Costa Rica: Límon, Vale do Rio Carere 9.70287 -83.03613 Gonzaga palliceps 14 Costa Rica: Orosi, Cartago Province 9.79388 -83.85600 Gonzaga palliceps 11 Costa Rica: Puntarenas, Golfito 8.60000 -83.16700 Gonzaga palliceps 3 Guyana: Kartabo, Bartica District [information - Schwarz, 1938] 6.34460 -58.70190 Gonzaga soroanus 1 Cuba: Las Villas, Cienfuegos, Arboreto de Soledad 22.17622 -80.45884 Gonzaga soroanus 1 Cuba: Pinar del Rio, Las Animas 22.91700 -82.95000 Gonzaga soroanus 1 Cuba: Pinar del Rio, Soroa 22.80000 -83.01700 Gonzaga torquatus 9 Brazil: Espirito Santo -20.00000 -40.75000 Gonzaga torquatus 9 Brazil: Santa Catarina, Joinville -26.30000 -48.83300 Gonzaga torquatus 14 Colombia: Antioquia, Campamento 6.97950 -75.29660 Gonzaga torquatus 14 Colombia: Antioquia, El Santuario 6.09807 -75.27921 Gonzaga torquatus 14 Colombia: Antioquia, Piedemonte, Jardin, Parcelación Ecológica Piedemonte, Casa 12 5.59697 -75.81059 Gonzaga torquatus 14 Colombia: Cundinamarca, Nocaima, Terrazas de San Joaquin 5.06946 -74.38030 Gonzaga torquatus 14 Colombia: Magdalena, Ciénaga, San Javier 10.85493 -74.03228 Gonzaga torquatus 14 Colombia: Piedecuesta, Santander 6.98690 -73.05746 Gonzaga torquatus 11 Costa Rica: Liberia - Parque Nacional Sta Rosa - Estacão Santa Rosa 10.83641 -85.61549 Gonzaga torquatus 11 Costa Rica: Liberia - Parque Nacional Sta Rosa - Estacão Santa Rosa 10.83641 -85.61549 Gonzaga torquatus 11 Costa Rica: Liberia - Parque Nacional Sta Rosa - Estacão Santa Rosa 10.83641 -85.61549 Gonzaga torquatus 11 Costa Rica: Alajuela, Finca La Selva, Dos Rios 10.24357 -84.27047 Gonzaga torquatus 14 Costa Rica: Berlín, Provincia de Alajuela, San Ramón 10.01672 -84.46974 Gonzaga torquatus 14 Costa Rica: Buenos Aires, Punta Arenas, Chánguena 8.86169 -83.14305 Gonzaga torquatus 14 Costa Rica: Calle los Leyton, Provincia de Puntarenas, Monteverde 10.28339 -84.79761 Gonzaga torquatus 14 Costa Rica: Cartago Province 9.78346 -83.75259 Gonzaga torquatus 14 Costa Rica: Guanacaste Province 10.51212 -84.98871 Gonzaga torquatus 11 Costa Rica: Límon, Pandora 9.73300 -82.96700 Gonzaga torquatus 14 Costa Rica: Monteverde, Puntarenas Province 10.30631 -84.81319 Gonzaga torquatus 14 Costa Rica: Puntarenas Province 8.52412 -83.40119 Gonzaga torquatus 11 Costa Rica: Puntarenas, Osa Peninsula 8.55000 -83.50000 Gonzaga torquatus 14 Costa Rica: Rivas, San José Province 9.47216 -83.57744 Gonzaga torquatus 11 Costa Rica: San José 10.00000 -84.40000 Gonzaga torquatus 7 Guatemala: Bosque virgen del Peten, campo [La Pava], entre Plancha Piadra y ciudad de Flore 16.95993 -89.72552 Gonzaga torquatus 6 Guatemala: San Géronimo 15.05000 -90.20000 Gonzaga torquatus 14 Honduras: Francisco Morazón, San Antonio de Oriente 14.00770 -87.00715 Gonzaga torquatus 14 Honduras: Francisco Morazón, San Antonio de Oriente 14.03186 -87.07336 Gonzaga torquatus 14 Honduras: Olancho, Dulce Nombre de Culmí 15.25668 -85.31528 Gonzaga torquatus 14 Mexico: A Chipinque 123, Zona de La Sierra Madre, 66250 San Pedro Garza García, N.L. 25.61835 -100.35941 Gonzaga torquatus 14 Mexico: Agua Zarca, Qro. 21.21806 -99.09472 Gonzaga torquatus 14 Mexico: Calle Aguacatal, Coatepec, ver. 19.44353 -96.96766 Gonzaga torquatus 14 Mexico: Campeche, Los Tambores de Emiliano Zapata 17.99509 -89.31383 Gonzaga torquatus 14 Mexico: Chiapas, Ocosingo, Tres Lagunas 16.83690 -91.14338 Gonzaga torquatus 14 Mexico: Guadaloupe, Cascatas del Cerro de la silla 25.63038 -100.20858 Gonzaga torquatus 14 Mexico: Guadalupe, N.L. 25.63038 -100.20858 Gonzaga torquatus 14 Mexico: Santa Maria Yucuhiti, Oax. 17.05223 -97.81854 Gonzaga torquatus 14 Mexico: Xalisco, Sierra Madre Occidental pine-oak forests 21.48672 -104.99442 Gonzaga torquatus 2 Panama: Alajuela River 9.25600 -79.59312 Gonzaga torquatus 14 Panama: Cerro Azul, Panama City 9.26445 -79.41541 Gonzaga torquatus 2 Panama: Trinidad River 8.74657 -79.99564 Gonzaga torquatus 3 Venezuela: Carabobo - San Estehan 10.39650 -67.96429 1 = Aloya, 1968; 2 = Banks, 1914–1915; 3 = Banks, 1944 ; 4 = Gerstaecker, 1887; 5 = McLachlan, 1868; 6 = Navás, 1912–1913; 7 = Navás, 1927; 8 = Navás, 1928; 9 = Navás, 1929; 10 = Nóe et al. 2015; 11 = Penny, 2002 ; 12 = Tauber and Pantaleoni, 2018 ; 13 = Tauber et al. 2008 ; 14 = iNaturalist; 15 = Original Data (New distributional records) These specimens are rare in field collections and museums. Except for the generic revision of green lacewings by Brooks and Barnard ( 1990 ), Gonzaga has received little or no attention in modern systematic studies. Its composition and validity as genus are questioned due to its morphological similarity to the genus Leucochrysa McLachlan, 1868 (Tauber et al. 2008 ). The biodiversity knowledge shortfalls (KBS) of Gonzaga are particularly regrettable, as these characteristics could provide evidence to test whether Gonzaga forms a natural group. Thus, a comprehensive understanding of geographical distribution and environmental gradients is essential for understanding natural environments, recognizing patterns of species diversity, and planning conservation strategies (Myers et al. 2000 ; Lamoreux et al. 2006 ). Adequate knowledge of species distribution is also fundamental for evolutionary biology, phylogeography, and taxonomy studies (Chowdhury et al. 2023 ). In this context, the present study aims to provide a distributional database of Gonzaga species (with new distributional records based on material from entomological collections), establish environmental gradients based on known distributions, and infer the potential distribution of these species in the New World. Material and Methods For this purpose, a database was compiled through the primary literature (species description and distributional records), Global Biodiversity Information Facility (GBIF; https://www.gbif.org ), INaturalist ( https://www.inaturalist.org/ ), and original data obtained from specimens at the Museu de História Natural da Bahia (UFBA) and the Coleção Entomológica da Universidade Federal Rural de Pernambuco (CERPE) (Table 1 ). Specimens were identified in two ways: (i) organisms available in museums and collections were analyzed and identified based on the diagnostic characters of the species; (ii) organisms from INaturalist were analyzed based on photographs and identified based on the diagnostic characters of the species. Gazetteers and Google Maps© were used to register localization without coordinates. The centroid of the least comprehensive location was used. After the data compilation, a two steps filtering process was performed, (1) manual selection of the data with determined locality and species level; and (2) selection from the RStudio program (RStudio Team), discarding points that can generate an analysis bias (e.g., with equal coordinates or marine areas). After filtering, the database was used as input for niche modeling and to make a species distribution map. Environmental range data were obtained from BIO5 = Max Temperature of Warmest Month, BIO6 = Min Temperature of Coldest Month, BIO13 = Precipitation of Wettest Month, BIO14 = Precipitation of Driest Month and Elev = Elevation on a scale of 5 arc minutes, available in the online database WorldClim version 2.1 ( https://www.worldclim.org/data/worldclim21.html ). Based on this dataset, distribution value plots and boxplots were generated using the 'ggplot' function from the ggplot2 package in the R environment (R Core Team, 2021). Environmental data for distribution modelling were obtained from monthly climate data for 19 bioclimatic variables and elevation at a 5 arc-minute resolution, available from WorldClim version 2.1 ( https://www.worldclim.org/data/worldclim21.html ). The study region for each species was delimited to the New World (Nearctic and Neotropical regions), where environmental layers were masked and 1,000 random background points were sampled. We used the checkerboard 1 (k = 2) spatial partitioning method, which reduces spatial autocorrelation and provides a more realistic estimate of model performance, especially when extrapolation across geographic space is intended (Muscarella et al. 2014 ). To construct and evaluate the niche model, algorithms were selected to conduct using modeled response flexibility (L, LQ, H, LQH e LQHP) and penalty against complexity (1 to 2) for a 0.5 multiplier step value. Thus, MaxEnt based on the presence-background algorithm was successfully run and produced evaluation results for each species. The best model among these models was selected based on the lowest AICc value and delta AICc. Subsequently, based on these models, Maxent v.3.4.4 (Phillips et al. 2017) was run separately for each species. All analyses and model building were carried out using the R application Wallace 2 (Kass et al. 2023 ). Only models with Area Under Curve (Hanley and McNeil 1982 ) superior to 80% were considered for constructing suitability maps, using default limits of presence and absence. Maps of distribution, and environmental suitabilty were created using QGIS version 3.4.15 and finalized in Corel Draw 2019 (trial version). Results A total of 76 distribution records were found: 32 from iNaturalist, 41 from the literature (22 papers), and three new distribution records (two from CERPE and one from UFBA). The species Gonzaga nigriceps is reported for the first time in the Northeastern region of Brazil, specifically in the states of Alagoas (iNaturalist), Bahia (UFBA), and Pernambuco (CERPE). Gonzaga palliceps has new distribution records for the Federal District (Brasília, Brazil) and the state of São Paulo (iNaturalist). Finally, Gonzaga torquatus has new distribution records for Colombia, Honduras, and Mexico (iNaturalist) (Table 1). The species are distributed between Nuevo León state, Mexico (Sierra Madre Oriental Pine-Oak Forest), and Santa Catarina state, Brazil (Serra do Mar Coastal Forest). The species with the widest distribution range is Gonzaga torquatus , extending from Nuevo León state, Mexico (Sierra Madre Oriental Pine-Oak Forest) to Santa Catarina state, Brazil (Serra do Mar Coastal Forest) (Figures 1A and 2E). Gonzaga palliceps ranges from the province of Limón, Costa Rica (Isthmian-Atlantic Moist Forests) to São Paulo state, Brazil (Alto Paraná Atlantic Forests) (Figures 1A and 2C). Gonzaga nigriceps is distributed from Venezuela and Suriname (Guianan Highlands Moist Forests) to Santa Catarina state, Brazil (Serra do Mar Coastal Forest) (Figures 1A and 2A). All other species have a more restricted distribution, either as singletons like Gonzaga amabilis (Ecuador), Gonzaga notatus (Peru), and Gonzaga palliatus (Espírito Santo state, Brazil) or Gonzaga callipterus with two records (Suriname and Amazonas, Brazil) (Figure 1A) and Gonzaga soroanus with three records all from Cuba (Figures 1A and 1G). New distribution records are marked in bold in the distribution section, and there is an "*" in those from photographs from INaturalist that have been analyzed and identified by an expert (Dr. Caleb Califre Martins). The species are found at elevations ranging from 3 to 2,291 meters above sea level (m a.s.l.), with the highest concentration in areas below 500 m a.s.l. (Figure 1C). Recorded occurrence sites have monthly precipitation values ranging from 3 to 557 mm, with a mean of 37 mm in the driest month and 311 mm in the wettest month (Figure 1D). Temperatures in occurrence areas range from 5.9°C to 34.6°C, with a mean of 15.8°C in the coldest month and 30.0°C in the warmest month (Figure 1E). Gonzaga amabilis Navás, 1932:23 [Type locality: Ecuador, Rio Peripa? – Lost?; ♀]. References : Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]; Tauber and Pantaleoni 2018 [Taxonomy, designated Lectotype ♀]. Distribution : Ecuador. Bionomics : This species has known records at 90 m a.s.l. (Figure 1C) in the Western Ecuador Moist Forest, in areas with a range of monthly precipitation between 18 to 454 mm³ (Figure 1D), and a temperature between 19.8 to 30.3°C (Figure 1E). Remarks :This species present restrict distributional records. Gonzaga callipterus Banks, 1944:43 [Type locality: Guyana, Gt. Falls, MCZ; ?]. References : Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]. Distribution : Brazil (AM), Guyana. Bionomics : This species has known occurrence records between 3 to 363 m a.s.l. (Figure 1C) in the Guianan Highlands Moist Forest and Madeira-Tapajós Moist Forest, in areas with a range of monthly precipitation between 61 to 360 mm³ (Figure 1D), and a temperature between 19.8 to 33.3°C (Figure 1E). Remarks :This species present restrict distributional records. Gonzaga nigriceps (McLachlan, 1867):251 [Type locality: Brasilia [Brazil], [Villa de] Ega; ?, as Chrysopa nigriceps ]. References : Gerstaecker 1887:124 [Distribution, as Leucochrysa nigriceps ]; Navás 1912-1913:303 [Checklist, as Chrysopa nigriceps ]; Navás 1913:104 [Checklist, as Chrysopa nigriceps ]; Navás 1913:104 [Redescription, Taxonomy, Distribution, as Leucochrysa nigriceps ]; Navás 1912-1913:303 [Taxonomy, Distribution, as Leucochrysa nigriceps ]; Nakahara 1915:118 [Taxonomy, as Chrysopa nigriceps ]; Okamoto 1919:4 [Checklist, as Chrysopa nigriceps ]; Kimmins 1940:444 [Checklist, as Chrysopa nigriceps ]; Kimmins 1940:444 [Taxonomy, as Leucochrysa nigriceps ]; Kimmins 1940:444 [Checklist, as Nodita nigriceps ]; Banks 1944:34 [Distribution]; Penny 1977:22 [Checklist, as Chrysopa nigriceps ]; Penny 1977:22 [Distribution]; Penny 1977:22 [Checklist, as Leucochrysa nigriceps ]; Brooks and Barnard 1990:276 [Checklist, Gonzaga nigriceps comb. nov. ]; Whittington 2002:379 [Distribution]; El Hamouly and Fadl 2011:97 [Checklist, as Chrysopa nigriceps ]. Distribution : Brazil ( AL *, AM, BA , ES, PE , RJ, SC) Colombia, Ecuador, Guyana, Peru, Suriname and Venezuela. Bionomics : This species has known occurrence records between 27 to 953 m a.s.l. (Figure 1C) in the Alto Paraná Atlantic Forests, Bahia Coastal Forests, Guianan Highlands Moist Forests, Iquitos Varzeá, Pernambuco Coastal Forests, Purus Varzeá, Serra Do Mar Coastal Forests, Solimoes-Japurá Moist Forest, and Southern Atlantic Mangroves in areas with a range of monthly precipitation between 26 to 360 mm³ (Figure 1D), and a temperature between 8.7 to 33°C (Figure 1E). Specimens were collected using light pan and malaise traps set near aquatic environments, indicating a possible association with riparian forest habitats. Remarks : The fc.LQH_rm.1 model (AUC = 0.869; CBI = 0.620) highlighted its preference for environments with minimal dry-season precipitation (bio14), high wet-quarter precipitation (bio16), moderate isothermality (bio03), and thermal seasonality (bio04). Daily temperature range (bio02) negatively impacts suitability, indicating adaptation to stable microclimates. This species shows high environmental suitability on the Central American in Pacific Lowlands, Veracruz, and Yucatan Peninsula Province, and in South American in Guyana Pronvice, Amazon Basin, Atlantic Forest and east of Caatinga domain (Figure 2B). Gonzaga notatus Navás, 1929:861 [Type locality: Peru, Iquitos, Navás Collection; Lost?]. References : Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]. Distribution : Peru. Bionomics : This species has known records at 96 m a.s.l. (Figure 1C) in the Iquitos Várzea, in areas with a range of monthly precipitation between 185 to 312 mm³ (Figure 1D), and a temperature between 20.3 to 31.8°C (Figure 1E). Remarks :This species present restrict distributional records. Gonzaga palliatus Navás, 1929:860 [Type locality: Brazil: Espirito Santo – Navás Collection; Lost?]. References : Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]. Distribution : Brazil (ES). Bionomics : This species has known records at 771 m a.s.l. (Figure 1C) in the Bahia Costal Forest, in areas with a range of monthly precipitation between 50 to 203 mm³ (Figure 1D), and a temperature between 10.4 to 27.2°C (Figure 1E). Remarks :This species present restrict distributional records. Gonzaga palliceps (McLachlan, 1867:251) [Type locality: Type locality: Brasilia [Brazil], [Villa de] Ega, McLachlan Collection; Lost?]. References : Navás 1913:149 [Checklist, as Chrysopa palliceps ]; Navás 1913:149 [Redescription, Taxonomy, Distribution, as Leucochrysa palliceps ]; Navás 1928:126 [Available, First Description, as Nodita nevermanni ]; Banks 1944:20 [Distribution, as Nodita palliceps ]; Banks 1945:160 [Taxonomy, as Nodita nevermanni ]; Penny 1977:27 [Checklist, as Chrysopa palliceps ]; Penny 1977:27 [Checklist, as Leucochrysa palliceps ]; Penny 1977:26 [Distribution, as Nodita nevermanni ]; Penny 1977:27 [Distribution, as Nodita palliceps ]; Brooks and Barnard 1990:277 [Checklist, as Leucochrysa ( Nodita ) nevermanni ]; Brooks and Barnard 1990:277 [Checklist, as Leucochrysa ( Nodita ) palliceps ]; Penny 2001:12 [Taxonomy, as Leucochrysa ( Nodita ) nevermanni ]; Penny 2001:12 [Taxonomy, Leucochrysa ( Nodita ) palliceps ]; Penny in Penny 2002:191 [Redescription, Taxonomy, Distribution, Gonzaga palliceps comb. nov. ] Distribution : Brazil (AM, DF *, SP *), Costa Rica, and Guyana. Bionomics : This species has known occurrence records between 17 to 1071 m a.s.l. (Figure 1C) in the Alto Paraná Atlantic Forests, Cerrado, Guianan Moist Forests, Isthmian-Atlantic Moist Forests, Purus Varzeá, and Southern Mesoamerican Pacific Mangroves, in areas with a range of monthly precipitation between 8 to 424 mm³ (Figure 1D), and a temperature between 10.6 to 32.4°C (Figure 1E). Remarks : The fc.LQ_rm.1 model (AUC = 0.914; CBI = 0.838) identified isothermality (bio03), mean wet-quarter temperature (bio08), and precipitation seasonality (bio15) as positive predictors. Extreme hydrological conditions (bio13², bio16², bio19²) and daily temperature range (bio02) reduce suitability, reflecting sensitivity to abrupt fluctuations. This species shows high environmental suitability in the coastal tropical regions of Central and South American. Specifically, it is well-suited on the Central American in west (Pacific Lowlands), and Pacific dominion. In South American in coastal region of Boreal Brazilian dominion, Caatinga province and South American transition zone on Atacama and Desert provinces (Figure 2D). Gonzaga soroanus Alayo, 1968:60 [Type locality: Cuba: Las Villas, Cienfuegos, Arboreto de Soledad, CZACC, ?]. References : Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]. Distribution : Cuba. Bionomics : This species has known occurrence records between 35 to 293 m a.s.l. (Figure 1C) in the Cuban Dry Forests, in areas with a range of monthly precipitation between 20 to 219 mm³ (Figure 1D), and a temperature between 15.7 to 31.9°C (Figure 1E). Remarks : The fc.LQH_rm.2 model (AUC = 0.999; CBI = 1.000) showed exceptional accuracy, linking its distribution to mean warm-quarter temperature (bio10), minimal dry-month precipitation (bio14), and wet-month precipitation (bio13). Extreme thermal (bio04²) and hydrological variability (bio12², bio15², bio19²) negatively affect suitability, emphasizing reliance on climatically stable environments. This species shows high environmental suitability in Cuba Province, and central west of Yucatan Province (Figure 2H). Gonzaga torquatus Navás, 1913:318 [Type locality: Guatemala: San Géronimo – Navás Collection; Lost?]. References : Banks 1914–1915:624 [Redescription, Taxonomy, Distribution]; Banks 1914–1915:58 [Distribution]; Navás 1924:326 [Distribution]; Navás 1927:319 [Distribution]; Navás 1929:34 [Distribution]; Banks 1944:172 [Distribution]; Banks 1945:22 [Distribution]; Penny 1977:240 [Type Species Listed]; Monserrat 1985:276 [Checklist]; Brooks and Barnard 1990:578 [Distribution]; Oswald et al. 2002:191 [Redescription, Taxonomy, Distribution]; Penny in Penny 2002:171 [Checklist]. Distribution : Bazil (ES, SC), Colombia *, Costa Rica, Guatemala, Honduras *, Mexico *, Panamá, Venezuela. Bionomics : This species has known occurrence records between 16 to 2291 m a.s.l. (Figure 1C) in the Bahia Coastal Forest, Cauca Valley Montane Forest, Central American Dry, Montane and Pine-Oak Forests, Costa Rican Seasonal Moist Forests, Isthmian-Atlantic and Pacific Moist Forests, La Costa Xeric Shrublands, Magdalena Valley Montane Forests, Petán-Veracruz Moist Forests, Santa Marta Montane Forests, Sierra Madre Occidental, Oriental and Del Sur Pine-Oak Forests, Talamancan Montane Forests, Veracruz and Yucatán Moist Forests, in areas with a range of monthly precipitation between 3 to 557 mm³ (Figure 1D), and a temperature between 5.9 to 34.6°C (Figure 1E). Remarks: Gonzaga torquatus shows a disjunct distribution in Brazil (ES, SC), Colombia, Costa Rica, Guatemala, Honduras, Mexico, Panama, and Venezuela. The fc.LQ_rm.1 model (AUC = 0.920; CBI = 0.957) identified maximum warm-month temperature (bio05), isothermality (bio03), and cold-month temperature (bio09) as key predictors. Sensitivity to daily temperature range (bio02²) and hydrological extremes (bio17²), highlight ecological constraints. This species shows high environmental suitability in all areas bellow Mexican transition zone for Atlantic and Pacific coastal tropical regions of Central and South American. Specifically, it is well-suited on all Central American, and Pacific dominion. In South American in coastal region of Boreal Brazilian dominion, Caatinga province, All Panama dominion and South American transition zone on Atacama and Desert provinces (Figure 2F). Discussion The genus Gonzaga exhibits contrasting distribution patterns across Neotropics, with some species displaying broad geographic ranges and others showing extremely restricted distributions, rendering them highly vulnerable to extinction. Gonzaga 's specimens are rarely found in collections and have not received detailed systematic treatment recently (Tauber et al. 2008). The result of this is that in this work alone aggregated data from online databases, museum collections, and citizen science initiatives (INaturalist) account for 46% of known records, underscoring the critical need to strengthen these data sources, particularly in tropical regions characterized by high biodiversity and endemism (Brooks and Barnard 1990). This study substantially expanded the knowledge of the geographic distribution of the genus Gonzaga , highlighting the importance of integrating multiple data sources—citizen science (iNaturalist), scientific literature, and new field records—to reduce biogeographical knowledge gaps in Neotropical insects. Three species showed notable range expansions: Gonzaga nigriceps , recorded for the first time in northeastern Brazil (AL, BA, and PE); G. palliceps , now also found in the Federal District and São Paulo; and G. torquatus , with new records from Mexico, Honduras, and Colombia. These expansions reveal broader occurrence patterns than previously recognized for these species. The latitudinal distribution of the genus extends from Nuevo León, Mexico, to Santa Catarina, Brazil, encompassing various tropical and subtropical biomes across Central and South America. Among the species, G. torquatus has the widest distribution, followed by G. palliceps and G. nigriceps . In contrast, G. amabilis , G. notatus , G. palliatus , G. callipterus , and G. soroanus show highly restricted distributions, being known from only one or two localities. Environmental analyses indicate that most species occur at elevations below 500 m, with exceptions such as G. palliceps , which reach up to 1071 m a.s.l. The species inhabit areas with wide variation in precipitation (3–557 mm/month) and temperature (5.9–34.6 °C), although most are associated with warm, humid climates and low thermal variation. Models demonstrated high reliability (AUC > 0.86; CBI ≥ 0.62), with G. soroanus showing near-perfect validation (AUC = 0.999; CBI = 1.0), likely due to its restricted Cuban province distribution.The models highlight the Gonzaga species adaptability across diverse biomes, with high environmental suitability concentrated in the Neotropical region ( sensu Morrone et al. 2019). Ecological niche modeling supports these patterns, indicating high environmental suitability for G. nigriceps under diverse climatic conditions, while G. palliceps and G. soroanus show a greater dependence on stable microclimates, especially in tropical coastal regions of Central and South America. Suitable areas encompass tropical and subtropical moist and dry broadleaf forests, xeric shrublands, savannas, mangroves, and inland aquatic systems. Disjunct distributions between the Amazon and Atlantic Forests suggest historical influences, such as Pleistocene climatic fluctuations and the development of the Dry Diagonal. Unexplored regions—including the Atacama and Desert provinces, and coastal Atlantic areas of South America, particularly within the Amazon and Atlantic domains—also exhibit high environmental suitability, indicating potential distribution and highlighting these areas as priorities for future research efforts. Species with limited occurrence records (Figure 1A) are at elevated extinction risk, emphasizing the need to expand scientific collections and integrate citizen science data. To mitigate these threats, priority actions include: (1) conducting field surveys in undocumented high-suitability areas, such as the western Andes and Lesser Antilles; (2) monitoring hydrological and thermal thresholds to anticipate climate impacts; and (3) establishing cross-border conservation policies for species spanning multiple ecoregions. These measures are essential to address knowledge gaps, refine preservation strategies, and ensure the long-term survival of the Gonzaga genus in the face of rapid environmental change. Conclusions This study advanced the understanding of Gonzaga by clarifying current distribution patterns, identifying environmentally suitable areas, and revealing ecological tolerances and vulnerabilities across species. By integrating diverse data sources and ecological niche models, it highlights both the Gonzaga species adaptability to tropical environments and the need for targeted conservation. Despite these advances, critical gaps remain in taxonomy, phylogenetics, and biogeographic history, which limit our understanding of evolutionary processes and diversification patterns. Future efforts should prioritize integrative taxonomic revisions and phylogenetic analyses to test biogeographic hypotheses—such as the influence of the South American Dry Diagonal and potential trans-Andean dispersal. Ecological studies are also needed to investigate life-history traits that may explain range limitations. Ecological models proved reliable in identifying priority areas for future sampling and conservation, reinforcing the value of combining modeling, fieldwork, and citizen science to address biodiversity shortfalls and refine conservation strategies. Declarations Acknowledgements: We thank the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) for collecting permits. RP also thanks to the PRAPG-CAPES-88887.986811/2024-00 for the post-doctoral fellowship. We would also like to thank Prof. Dr. Adolfo Ricardo Calor of the Museu de História Natural da Bahia (UFBA), Bahia state, Brazil, for their support and donating some of the material used in this work. We both thank iNaturalist and Global Biodiversity Information Facility (GBIF), its creators, and all contributors for generating and sharing biodiversity data. The species records used in this study were accessed through the GBIF, which includes valuable citizen science contributions from iNaturalist. Funding The work was funded by post-doctoral fellowship of Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (PRAPG-CAPES-88887.986811/2024-00). Conflict of Interest The authors have no conflicts of interest to declare that are relevant of this work. Ethical approval and Informed consent Not Applicable. Author contribution RP and CCM conceived the study and defined its objectives. RP conducted the analyses, interpreted the results, and wrote. CCM identified the material and revised literature. PCG was responsible for the field collections, provided the specimens for analysis, and made the laboratory and museum facilities available. All authors revised the text and contributed with suggestions and corrections to the final version. Data Availability Statement Data is available in supplementary material. References Alayo AD (1968) Los neurópteros de Cuba (No. 2). Academia de Ciencias de Cuba, Havana Ariño AH (2010) Approaches to estimating the universe of natural history collections data. Biodivers Inf 7(2):81–92. https://doi.org/10.17161/bi.v7i2.3991 Banks N (1914–1915) New Neuropteroid Insects, Native and Exotic. Proc Acad Nat Sci Phila 66(3):608–632 Banks N (1944) Neuroptera of northern South America. Part III. Bol Entomol Venez 3:1–34 Banks N (1945) A review of Chrysopidae (Nohochrysidae) of Central America. Psyche 52:139–174 Boyes DH, Evans DM, Fox R et al (2021) Street lighting has detrimental impacts on local insect populations. Sci Adv 7(35):eabi8322. https://doi.org/10.1126/sciadv.abi8322 Brooks SJ, Barnard PC (1990) The green lacewings of the world: a generic review (Neuroptera: Chrysopidae). Bull Br Mus (Nat Hist) Entomol 59:117–286 Chowdhury S, Aich U, Rokonuzzaman M et al (2023) Increasing biodiversity knowledge through social media: A case study from tropical Bangladesh. Bioscience 73(6):453–459 Contreras-Ramos A, Rosas MV (2014) Biodiversity of Megaloptera and Raphidoptera in Mexico. Rev Mex Biodivers 85:257–263. https://doi.org/10.7550/rmb.32049 Dangles O, Casas J (2019) Ecosystem services provided by insects for achieving sustainable development goals. Ecosyst Serv 35:109–115. https://doi.org/10.1016/j.ecoser.2018.12.002 Eisenhauer N, Bonn A, Guerra CA (2019) Recognizing the quiet extinction of invertebrates. Nat Commun 10(1):50. https://doi.org/10.1038/s41467-018-07916-1 El-Hamouly H, Fadl HH (2011) Checklist of order Neuroptera in Egypt, with a key to families. Afr J Biol Sci 7(1):85–104 Funk VA (2018) Collections-based science in the 21st century. J Syst Evol 56(3):175–193. https://doi.org/10.1111/jse.12315 Gerstaecker A (1888) Weitere Beiträge zur Artenkenntniss des Neuroptera Megaloptera. Mitt Naturwiss Ver Neu-Vorpommern Rugen 19(1):89–130 Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143(1):29–36. https://doi.org/10.1148/radiology.143.1.7063747 Kass JM, Pinilla-Buitrago GE, Paz A et al (2023) Wallace 2: a shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions. Ecography 2023(3):e06547. https://doi.org/10.1111/ecog.06547 Kharouba HM, Lewthwaite JMM, Guralnick R et al (2018) Using insect natural history collections to study global change impacts: challenges and opportunities. Philos Trans R Soc B 374:20170405. https://doi.org/10.1098/rstb.2017.0405 Kimmins DE (1940) Notes on some types of Chrysopidæ (Neuroptera) in the British Museum Collections. J Nat Hist 5(29):442–449. https://doi.org/10.1080/00222934008527058 Kuhn M, Jackson S, Cimentada J et al (2022) Package Corrr Lamoreux JF, Morrison JC, Ricketts TH et al (2006) Global tests of biodiversity concordance and the importance of endemism. Nature 440(7081):212–214. https://doi.org/10.1038/nature04291 Lister AM (2011) Natural history collections as sources of long-term datasets. Trends Ecol Evol 26(4):153–154. https://doi.org/10.1016/j.tree.2010.12.009 Monserrat VJ (1985) Lista de los tipos de Mecoptera y Neuroptera (Insecta) de la colección L. Navás, depositados en el Museo de Zoología de Barcelona. Misc Zool 9:233–243 Morrone JJ, Escalante T, Rodríguez-Tapia G et al (2022) Biogeographic regionalization of the Neotropical region: New map and shapefile. Acad Bras Cienc 94:e20211167. https://doi.org/10.1590/0001-3765202220211167 Muscarella R, Galante PJ, Soley-Guardia M, Boria RA, Kass JM, Uriarte M, Anderson RP (2014) ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol Evol 5(11):1198–1205. https://doi.org/10.1111/2041-210X.12261 Myers N, Mittermeier RA, Mittermeier CG et al (2000) Biodiversity hotspots for conservation priorities. Nature 403(6772):853–858. https://doi.org/10.1038/35002501 Nakahara W (1915) A synonymic list of Japanese Chrysopidae, with descriptions of one new genus and three new species. Ann Entomol Soc Am 8(2):117–123. https://doi.org/10.1093/aesa/8.2.117 Navas L (1912–1913) Les Chrysopides (Ins. Nevr.) du Musee de Londres [Ia]. Ann Soc Sci Bruxelles 37(pt 2):292–330 Navas L (1913) Crisopidos sudamericanos. Broteria (Zool) 11:73–104 Navas L (1924) Crisopidos (Ins. Neur.) neotropicos [I]. Rev Chil Hist Nat 27:110–116 Navas L (1927) Insectos neotropicos. 3.a serie. Rev Chil Hist Nat 31:316–328 Navas L (1928) Insectos del Museo de Hamburgo. Primera [I] serie. Bol Soc Entomol Esp 11:59–67 90–100 Navas L (1929) Insecta nova. Series XIII. Mem Accad Pontif Nuovi Lincei 12:15–23 Okamoto H (1919) Studies on the Chrysopidae of Japan. Rep Hokkaido Agric Exp Stn 9:1–76 Oswald JD, Contreras-Ramos A, Penny ND (2002) Neuroptera (Neuropterida). In: Llorente BJ, Morrone JJ, González SE (eds) Biodiversidad, taxonomía y biogeografía de artrópodos de México: hacia una síntesis de su conocimiento, vol III. UNAM, México DF, pp 559–581 Oswald JD, Machado RJ (2018) Biodiversity of the Neuropterida (Insecta: Neuroptera: Megaloptera, and Raphidioptera). In: Foottit RG, Adler PH (eds) Insect biodiversity: science and society, vol 2. Wiley, Hoboken, pp 627–672 Penny ND (1977) Lista de megaloptera, neuroptera e raphidioptera do México, América Central, ilhas Caraíbas e América do Sul. Acta Amaz 7(4 Suppl 1):5–61 Penny ND (2001) New species of Chrysopidae (Neuroptera: Chrysopidae) from Costa Rica, with selected taxonomic notes and a neotype designation. Entomol News 112(1):1–14 Penny ND (2002) Family Chrysopidae. In: Penny ND (ed) A guide to the lacewings (Neuroptera) of Costa Rica . Proc Calif Acad Sci 53:187–227 Pérez-Lachaud G, Lachaud JP (2017) Hidden biodiversity in entomological collections: The overlooked co-occurrence of dipteran and hymenopteran ant parasitoids in stored biological material. PLoS ONE 12(9):e0184614. https://doi.org/10.1371/journal.pone.0184614 Phillips SJ (2017) A Brief Tutorial on Maxent. Disponível em: http://biodiversityinformatics.amnh.org/open_source/maxent/ . Acesso em: 23 mai. 2025 Sánchez-Bayo F, Wyckhuys KAG (2019) Worldwide decline of the entomofauna: A review of its drivers. Biol Conserv 232:8–27. https://doi.org/10.1016/j.biocon.2019.01.020 Santos BF, Hoppe JPM (2018) Filling gaps in species distributions through the study of biological collections: 415 new distribution records for Neotropical Cryptinae (Hymenoptera, Ichneumonidae). Rev Bras Entomol 62:288–291. https://doi.org/10.1016/j.rbe.2018.09.001 Shcheglovitova M, Anderson RP (2013) Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes. Ecol Model 269:9–17. https://doi.org/10.1016/j.ecolmodel.2013.08.011 Smith VS, Blagoderov V (2012) Bringing collections out of the dark. ZooKeys 209:1 Tauber CA, Albuquerque GS, Tauber MJ (2008) Gonzaga nigriceps (McLachlan) (Neuroptera: Chrysopidae): descriptions of larvae and adults, biological notes, and generic affiliation. Proc Entomol Soc Wash 110(2):417–438. https://doi.org/10.4289/07-045.1 Tauber CA, Pantaleoni RA (2018) Type specimens of Neotropical Chrysopidae (Neuroptera) in Italian museums. Trop Zool 31(4):177–199. https://doi.org/10.1080/03946975.2018.1493169 Wagner DL, Grames EM, Forister ML et al (2021) Insect decline in the Anthropocene: Death by a thousand cuts. Proc Natl Acad Sci USA 118(2):e2023989118. https://doi.org/10.1073/pnas.2023989118 Whittington AE (2002) Resources in Scottish neuropterology. 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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-6763568","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":466233447,"identity":"733a6bcb-242b-4253-95e9-9d12d95d9179","order_by":0,"name":"Rafael Pereira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYFACxgcMDAUMDGzsYJ4NSKTxAH4tzAYMDEDExgzmpYG0NBCnhQGi5TCYxKvFvP0w44cPBnfs+Zh5DD8XVJy3W9t+GGhLjU00Li0yZ5KZJWcYPEtsY+Yxlp5x5nbytjOJQC3H0nIbcGiRYMg/IM1jcDiBjZktQZq37Xay2QGgFsaGw7i18D9m/v3H4LA9UEvyb95/55LNzj8koEUimU2aweAwYxsz8zFp3oYDdmY3CNki8ZjNsgfsF+Zj1jOOJSeY3QDakoDPL/zJzDd+VNyxl29vbL5dUGNnb3Y+/eGDDzU2OLVAwQEwCYqaRLDKBPzKUbXYE1Y8CkbBKBgFIw0AAMgXXSjadAGpAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-7578-6042","institution":"Universidad Nacional Autonoma de Mexico","correspondingAuthor":true,"prefix":"","firstName":"Rafael","middleName":"","lastName":"Pereira","suffix":""},{"id":466233448,"identity":"bf12bd3e-7d15-408b-8bad-70c05f14019f","order_by":1,"name":"Caleb Califre Martins","email":"","orcid":"","institution":"UNESP Campus de Rio Claro: Universidade Estadual Paulista Julio de Mesquita Filho - Campus de Rio Claro","correspondingAuthor":false,"prefix":"","firstName":"Caleb","middleName":"Califre","lastName":"Martins","suffix":""},{"id":466233449,"identity":"1cc723f9-8137-4e90-999e-145ff57a5b65","order_by":2,"name":"Paschoal Coelho Grossi","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Paschoal","middleName":"Coelho","lastName":"Grossi","suffix":""}],"badges":[],"createdAt":"2025-05-28 02:54:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6763568/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6763568/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11756-025-02093-1","type":"published","date":"2026-02-09T15:57:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84252307,"identity":"3c9654a3-cebb-4c93-879c-876347ce4670","added_by":"auto","created_at":"2025-06-09 18:41:52","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1920023,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution records, high environmental suitability maps and environmental range of \u003cem\u003eGonzaga \u003c/em\u003especies. A. Distributional records map; B. high environmental suitability areas; C. Elevation range; D. Precipitation range; E. Temperature range.\u003c/p\u003e","description":"","filename":"Figure12.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6763568/v1/1352e94909aa332c25b9e16c.jpeg"},{"id":84251479,"identity":"6d510185-86d6-48e8-a411-4d51acc3ccae","added_by":"auto","created_at":"2025-06-09 18:33:52","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3213696,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution records and environmental suitability maps for \u003cem\u003eGonzaga \u003c/em\u003especies. A–B. \u003cem\u003e\u003cstrong\u003eGonzaga nigriceps\u003c/strong\u003e\u003c/em\u003e: A. Distribution and environmental suitability (weighted average), B. High environmental suitability (\u0026gt;0.5); B–D. \u003cem\u003e\u003cstrong\u003eGonzaga palliceps\u003c/strong\u003e\u003c/em\u003e: C. Distribution and environmental suitability (weighted average), D. High environmental suitability (\u0026gt;0.5); E–F.\u003cem\u003e\u003cstrong\u003e Gonzaga torquatus\u003c/strong\u003e\u003c/em\u003e: E. Distribution and environmental suitability (weighted average), F. High environmental suitability (\u0026gt;0.5); G–H. \u003cem\u003e\u003cstrong\u003eGonzaga soroanus\u003c/strong\u003e\u003c/em\u003e: G. Distribution and environmental suitability (weighted average), H. High environmental suitability (\u0026gt;0.5).\u003c/p\u003e","description":"","filename":"Figure2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6763568/v1/8eed131737beb02a5029335c.jpeg"},{"id":102785275,"identity":"025bfc40-3993-40d3-8846-b480f9f2668c","added_by":"auto","created_at":"2026-02-16 16:03:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6323441,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6763568/v1/f7cf0efd-d0ec-4158-91a6-ddaa4c4d6f2c.pdf"},{"id":84252308,"identity":"069dfae9-00a0-42cd-8362-964c9f49d7f9","added_by":"auto","created_at":"2025-06-09 18:41:52","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22440,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6763568/v1/1a9ea6b0cb9818a98cb99139.xlsx"}],"financialInterests":"","formattedTitle":"Citizen Science Databases and Entomological Collections: Insights into Environmental Ranges and Potential Distribution of Gonzaga McLachlan, 1867 (Chrysopidae, Neuroptera)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEstimates suggest that approximately 3\u0026nbsp;billion specimens have been accumulated over 250 years in natural history collections and museums (Arin\u0026otilde; 2010; Smith and Blagoderov \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These collections are vital repositories of data on biodiversity, ecology, behavior, biological interactions, and bionomics (P\u0026eacute;rez-Lachaud and Lachaud \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). They preserve unidentified specimens from historical expeditions or biological material that is now inaccessible due to collection challenges or landscape changes (Funk \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese collections form the foundation for understanding historical habitat changes, species distributions, and the effects of climate change in biodiversity studies (Lister \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; P\u0026eacute;rez-Lachaud and Lachaud \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Santos and Hoppe \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This extensive database supports numerous studies, providing crucial data for models and predictions of species distribution, phenological patterns, ecological models, and future impacts (P\u0026eacute;rez-Lachaud and Lachaud \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eArthropods, particularly insects, are abundant in biological collections due to their small size, ease of collection and storage, and biodiversity representativeness (Kharouba et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Insects play key roles in ecosystem functions and services vital to life and human well-being in terrestrial and freshwater ecosystems (Dangles and Casas \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their richness, accounting for 50 to 70% of all described species, and their ecological roles mean that maintaining viable insect populations and understanding their biodiversity directly impacts agriculture, public health, natural resource use, and conservation (Dangles and Casas \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite their importance, insect population declines are increasingly evident due to anthropogenic landscape changes (Boyes et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wagner et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There is also a silent extinction (Eisenhauer et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), with over 40% of insect species threatened with extinction (S\u0026aacute;nchez-Bayo and Wyckhuys \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and some species going extinct before being formally described.\u003c/p\u003e \u003cp\u003eThe Neuroptera, a neglected but important insect order, is the most species-rich and habitat-diverse group within Neuropterida (Oswald and Machado \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). They inhabit freshwater environments with bryozoans and sponges, and various terrestrial environments. Most larvae are generalist predators, with specialized mantispids targeting wasp nests and spider eggs (Contreras-Ramos and Rosas 2004). Chrysopidae adults are used in agricultural pest control (Oswald and Machado \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the Chrysopidae, the genus \u003cem\u003eGonzaga\u003c/em\u003e Nav\u0026aacute;s, with eight described species, is the second largest in the tribe Leucochrysini in the New World (Tauber et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), with species distributed from Mexico to Brazil (Brooks and Barnard \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Records are concentrated in northwestern South America and southeastern Brazil (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Little is known about the distributional range, characterized by disjointed and sparse distribution records (Tauber et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\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\u003eDistributional records of \u003cem\u003eGonzaga\u003c/em\u003e species, locality, coordinates and references\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga amabilis\u003c/em\u003e\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEcuador: Rio Peripa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.74167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-79.60000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga callipterus\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Amazonas, Parintino [Parintins?]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.60000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-56.73300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga callipterus\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuyana: Gt. Falls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.17651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-59.48075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrasil: Rio de Janeiro, Mag\u0026eacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-22.57333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-43.02570\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Alagoas, Pilar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.60844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-35.91031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Amazonas - [Vila de] Ega\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.33515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-64.71173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Bahia, Camacan, RPPN Serra Bonita, Malaise 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-15.39336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-39.56464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Esp\u0026iacute;rito Santo, Anchieta Restinga da APA Municipal da tartaruga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-20.72139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-40.78139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Pernambuco, Paulista, Aldeia KM14, Granja do Delegado, Ponto do Riacho\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.91900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-35.01900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Pernambuco, Recife, Dois Irm\u0026atilde;os, Ponto Morro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.00547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-34.94208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Rio de Janeiro - Concei\u0026ccedil;\u0026atilde;o de Maracabu, Fazenda Carrapeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-22.16667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-41.86667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Rio de Janeiro - Parque Estadual Desengano, Fazenda Babil\u0026ocirc;nia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-21.85000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-41.80000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Rio de Janeiro - Parque Estadual Desengano, Sta. M. Madalena, Terras Frias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-21.91667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-41.91667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Rio de Janeiro - Sta. M. Madalena, Fazenda Sto Ant\u0026ocirc;nio de Imb\u0026eacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-22.00000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-41.86667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Santa Catarina, Blumenau\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-26.93300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-49.05000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Amazon - Let\u0026iacute;cia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.20062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-69.94860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuyana: [probable Gt. Falls, British Guiana, same collector and mouth of collection]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.17651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-59.48075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeru: Saracayon [probable Sarayacu \u003cem\u003esensu\u003c/em\u003e Hebard, 1923]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.73300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-75.10000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga nigriceps\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVenezuela: Bol\u0026iacute;var - Paraytepuy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.63300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-61.50000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga notatus\u003c/em\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeru: Iquitos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.74800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-73.24700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliatus\u003c/em\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Espirito Santo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-20.00000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-40.75000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e5, 6\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Amazonas - [Vila de] Ega\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.33515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-64.71173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Bras\u0026iacute;lia, Asa Norte Superquadra Norte 314 BL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-15.74593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-47.89558\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: S\u0026atilde;o Paulo, Laranjal Paulista\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-23.10740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-47.81675\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Ebene von Limon bei Las Mercedes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.16700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.61700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: L\u0026iacute;mon, Hitoy Cerere Biological Reserve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.64215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.08121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: L\u0026iacute;mon, Pandora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.73300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-82.96700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Lim\u0026oacute;n, Reventazon (Hamburg Farm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.24646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.46421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: L\u0026iacute;mon, Vale do Rio Carere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.70287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.03613\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Orosi, Cartago Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.79388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.85600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Puntarenas, Golfito\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.60000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.16700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga palliceps\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuyana: Kartabo, Bartica District [information - Schwarz, 1938]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.34460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-58.70190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga soroanus\u003c/em\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCuba: Las Villas, Cienfuegos, Arboreto de Soledad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.17622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-80.45884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga soroanus\u003c/em\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCuba: Pinar del Rio, Las Animas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.91700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-82.95000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga soroanus\u003c/em\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCuba: Pinar del Rio, Soroa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.80000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.01700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Espirito Santo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-20.00000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-40.75000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil: Santa Catarina, Joinville\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-26.30000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-48.83300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Antioquia, Campamento\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.97950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-75.29660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Antioquia, El Santuario\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.09807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-75.27921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Antioquia, Piedemonte, Jardin, Parcelaci\u0026oacute;n Ecol\u0026oacute;gica Piedemonte, Casa 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.59697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-75.81059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Cundinamarca, Nocaima, Terrazas de San Joaquin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.06946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-74.38030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Magdalena, Ci\u0026eacute;naga, San Javier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.85493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-74.03228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia: Piedecuesta, Santander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.98690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-73.05746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Liberia - Parque Nacional Sta Rosa - Estac\u0026atilde;o Santa Rosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.83641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-85.61549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Liberia - Parque Nacional Sta Rosa - Estac\u0026atilde;o Santa Rosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.83641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-85.61549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Liberia - Parque Nacional Sta Rosa - Estac\u0026atilde;o Santa Rosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.83641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-85.61549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Alajuela, Finca La Selva, Dos Rios\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.24357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.27047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Berl\u0026iacute;n, Provincia de Alajuela, San Ram\u0026oacute;n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.01672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.46974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Buenos Aires, Punta Arenas, Ch\u0026aacute;nguena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.86169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.14305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Calle los Leyton, Provincia de Puntarenas, Monteverde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.28339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.79761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Cartago Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.78346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.75259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Guanacaste Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.51212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.98871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: L\u0026iacute;mon, Pandora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.73300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-82.96700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Monteverde, Puntarenas Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.30631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.81319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Puntarenas Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.52412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.40119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Puntarenas, Osa Peninsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.55000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.50000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: Rivas, San Jos\u0026eacute; Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.47216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-83.57744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica: San Jos\u0026eacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.00000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-84.40000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuatemala: Bosque virgen del Peten, campo [La Pava], entre Plancha Piadra y ciudad de Flore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.95993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-89.72552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuatemala: San G\u0026eacute;ronimo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.05000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-90.20000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonduras: Francisco Moraz\u0026oacute;n, San Antonio de Oriente\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-87.00715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonduras: Francisco Moraz\u0026oacute;n, San Antonio de Oriente\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.03186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-87.07336\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonduras: Olancho, Dulce Nombre de Culm\u0026iacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.25668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-85.31528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: A Chipinque 123, Zona de La Sierra Madre, 66250 San Pedro Garza Garc\u0026iacute;a, N.L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.61835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-100.35941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Agua Zarca, Qro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.21806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-99.09472\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Calle Aguacatal, Coatepec, ver.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.44353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-96.96766\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Campeche, Los Tambores de Emiliano Zapata\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.99509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-89.31383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Chiapas, Ocosingo, Tres Lagunas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.83690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-91.14338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Guadaloupe, Cascatas del Cerro de la silla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.63038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-100.20858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Guadalupe, N.L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.63038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-100.20858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Santa Maria Yucuhiti, Oax.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.05223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-97.81854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico: Xalisco, Sierra Madre Occidental pine-oak forests\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.48672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-104.99442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePanama: Alajuela River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.25600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-79.59312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePanama: Cerro Azul, Panama City\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.26445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-79.41541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePanama: Trinidad River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.74657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-79.99564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVenezuela: Carabobo - San Estehan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.39650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-67.96429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e1\u0026thinsp;=\u0026thinsp;Aloya, 1968; 2\u0026thinsp;=\u0026thinsp;Banks, 1914\u0026ndash;1915; 3\u0026thinsp;=\u0026thinsp;Banks, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1944\u003c/span\u003e; 4\u0026thinsp;=\u0026thinsp;Gerstaecker, 1887; 5\u0026thinsp;=\u0026thinsp;McLachlan, 1868; 6\u0026thinsp;=\u0026thinsp;Nav\u0026aacute;s, 1912\u0026ndash;1913; 7\u0026thinsp;=\u0026thinsp;Nav\u0026aacute;s, 1927; 8\u0026thinsp;=\u0026thinsp;Nav\u0026aacute;s, 1928; 9\u0026thinsp;=\u0026thinsp;Nav\u0026aacute;s, 1929; 10\u0026thinsp;=\u0026thinsp;N\u0026oacute;e et al. 2015; 11\u0026thinsp;=\u0026thinsp;Penny, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; 12\u0026thinsp;=\u0026thinsp;Tauber and Pantaleoni, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; 13\u0026thinsp;=\u0026thinsp;Tauber et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; 14\u0026thinsp;=\u0026thinsp;iNaturalist; 15\u0026thinsp;=\u0026thinsp;Original Data (New distributional records)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese specimens are rare in field collections and museums. Except for the generic revision of green lacewings by Brooks and Barnard (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), \u003cem\u003eGonzaga\u003c/em\u003e has received little or no attention in modern systematic studies. Its composition and validity as genus are questioned due to its morphological similarity to the genus \u003cem\u003eLeucochrysa\u003c/em\u003e McLachlan, 1868 (Tauber et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe biodiversity knowledge shortfalls (KBS) of \u003cem\u003eGonzaga\u003c/em\u003e are particularly regrettable, as these characteristics could provide evidence to test whether \u003cem\u003eGonzaga\u003c/em\u003e forms a natural group. Thus, a comprehensive understanding of geographical distribution and environmental gradients is essential for understanding natural environments, recognizing patterns of species diversity, and planning conservation strategies (Myers et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Lamoreux et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Adequate knowledge of species distribution is also fundamental for evolutionary biology, phylogeography, and taxonomy studies (Chowdhury et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, the present study aims to provide a distributional database of \u003cem\u003eGonzaga\u003c/em\u003e species (with new distributional records based on material from entomological collections), establish environmental gradients based on known distributions, and infer the potential distribution of these species in the New World.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eFor this purpose, a database was compiled through the primary literature (species description and distributional records), Global Biodiversity Information Facility (GBIF; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gbif.org\u003c/span\u003e\u003cspan address=\"https://www.gbif.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), INaturalist (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.inaturalist.org/\u003c/span\u003e\u003cspan address=\"https://www.inaturalist.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and original data obtained from specimens at the Museu de Hist\u0026oacute;ria Natural da Bahia (UFBA) and the Cole\u0026ccedil;\u0026atilde;o Entomol\u0026oacute;gica da Universidade Federal Rural de Pernambuco (CERPE) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Specimens were identified in two ways: (i) organisms available in museums and collections were analyzed and identified based on the diagnostic characters of the species; (ii) organisms from INaturalist were analyzed based on photographs and identified based on the diagnostic characters of the species.\u003c/p\u003e \u003cp\u003eGazetteers and Google Maps\u0026copy; were used to register localization without coordinates. The centroid of the least comprehensive location was used. After the data compilation, a two steps filtering process was performed, (1) manual selection of the data with determined locality and species level; and (2) selection from the RStudio program (RStudio Team), discarding points that can generate an analysis bias (e.g., with equal coordinates or marine areas). After filtering, the database was used as input for niche modeling and to make a species distribution map.\u003c/p\u003e \u003cp\u003eEnvironmental range data were obtained from BIO5\u0026thinsp;=\u0026thinsp;Max Temperature of Warmest Month, BIO6\u0026thinsp;=\u0026thinsp;Min Temperature of Coldest Month, BIO13\u0026thinsp;=\u0026thinsp;Precipitation of Wettest Month, BIO14\u0026thinsp;=\u0026thinsp;Precipitation of Driest Month and Elev\u0026thinsp;=\u0026thinsp;Elevation on a scale of 5 arc minutes, available in the online database WorldClim version 2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldclim.org/data/worldclim21.html\u003c/span\u003e\u003cspan address=\"https://www.worldclim.org/data/worldclim21.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Based on this dataset, distribution value plots and boxplots were generated using the 'ggplot' function from the ggplot2 package in the R environment (R Core Team, 2021).\u003c/p\u003e \u003cp\u003eEnvironmental data for distribution modelling were obtained from monthly climate data for 19 bioclimatic variables and elevation at a 5 arc-minute resolution, available from WorldClim version 2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldclim.org/data/worldclim21.html\u003c/span\u003e\u003cspan address=\"https://www.worldclim.org/data/worldclim21.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The study region for each species was delimited to the New World (Nearctic and Neotropical regions), where environmental layers were masked and 1,000 random background points were sampled. We used the checkerboard 1 (k\u0026thinsp;=\u0026thinsp;2) spatial partitioning method, which reduces spatial autocorrelation and provides a more realistic estimate of model performance, especially when extrapolation across geographic space is intended (Muscarella et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo construct and evaluate the niche model, algorithms were selected to conduct using modeled response flexibility (L, LQ, H, LQH e LQHP) and penalty against complexity (1 to 2) for a 0.5 multiplier step value. Thus, MaxEnt based on the presence-background algorithm was successfully run and produced evaluation results for each species. The best model among these models was selected based on the lowest AICc value and delta AICc. Subsequently, based on these models, Maxent v.3.4.4 (Phillips et al. 2017) was run separately for each species. All analyses and model building were carried out using the R application Wallace 2 (Kass et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Only models with Area Under Curve (Hanley and McNeil \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1982\u003c/span\u003e) superior to 80% were considered for constructing suitability maps, using default limits of presence and absence. Maps of distribution, and environmental suitabilty were created using QGIS version 3.4.15 and finalized in Corel Draw 2019 (trial version).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 76 distribution records were found: 32 from iNaturalist, 41 from the literature (22 papers), and three new distribution records (two from CERPE and one from UFBA). The species \u003cem\u003eGonzaga nigriceps\u003c/em\u003e is reported for the first time in the Northeastern region of Brazil, specifically in the states of Alagoas (iNaturalist), Bahia (UFBA), and Pernambuco (CERPE). \u003cem\u003eGonzaga palliceps\u003c/em\u003e has new distribution records for the Federal District (Brasília, Brazil) and the state of São Paulo (iNaturalist). Finally, \u003cem\u003eGonzaga torquatus\u003c/em\u003e has new distribution records for Colombia, Honduras, and Mexico (iNaturalist) (Table 1).\u003c/p\u003e\n\u003cp\u003eThe species are distributed between Nuevo León state, Mexico (Sierra Madre Oriental Pine-Oak Forest), and Santa Catarina state, Brazil (Serra do Mar Coastal Forest). The species with the widest distribution range is \u003cem\u003eGonzaga torquatus\u003c/em\u003e, extending from Nuevo León state, Mexico (Sierra Madre Oriental Pine-Oak Forest) to Santa Catarina state, Brazil (Serra do Mar Coastal Forest) (Figures 1A and 2E). \u003cem\u003eGonzaga palliceps\u003c/em\u003e ranges from the province of Limón, Costa Rica (Isthmian-Atlantic Moist Forests) to São Paulo state, Brazil (Alto Paraná Atlantic Forests) (Figures 1A and 2C). \u003cem\u003eGonzaga nigriceps\u003c/em\u003e is distributed from Venezuela and Suriname (Guianan Highlands Moist Forests) to Santa Catarina state, Brazil (Serra do Mar Coastal Forest) (Figures 1A and 2A). All other species have a more restricted distribution, either as singletons like \u003cem\u003eGonzaga amabilis\u003c/em\u003e (Ecuador), \u003cem\u003eGonzaga notatus\u003c/em\u003e (Peru), and \u003cem\u003eGonzaga palliatus\u003c/em\u003e (Espírito Santo state, Brazil) or \u003cem\u003eGonzaga callipterus\u003c/em\u003e with two records (Suriname and Amazonas, Brazil) (Figure 1A) and \u003cem\u003eGonzaga soroanus\u003c/em\u003e with three records all from Cuba (Figures 1A and 1G).\u003c/p\u003e\n\u003cp\u003eNew distribution records are marked in bold in the distribution section, and there is an \"*\" in those from photographs from INaturalist that have been analyzed and identified by an expert (Dr. Caleb Califre Martins). \u0026nbsp;The species are found at elevations ranging from 3 to 2,291 meters above sea level (m a.s.l.), with the highest concentration in areas below 500 m a.s.l. (Figure 1C). Recorded occurrence sites have monthly precipitation values ranging from 3 to 557 mm, with a mean of 37 mm in the driest month and 311 mm in the wettest month (Figure 1D). Temperatures in occurrence areas range from 5.9°C to 34.6°C, with a mean of 15.8°C in the coldest month and 30.0°C in the warmest month (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga amabilis\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eNavás, 1932:23\u003c/strong\u003e [Type locality: Ecuador, Rio Peripa? – Lost?; ♀].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist]; Tauber and Pantaleoni 2018 [Taxonomy, designated Lectotype ♀].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Ecuador.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known records at 90 m a.s.l. (Figure 1C) in the Western Ecuador Moist Forest,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ein areas with a range of monthly precipitation between 18 to 454 mm³ (Figure 1D), and a temperature between 19.8 to 30.3°C (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e:This species present restrict distributional records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga callipterus\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eBanks, 1944:43\u003c/strong\u003e[Type locality: Guyana, Gt. Falls, MCZ; ?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Brazil (AM), Guyana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known occurrence records between 3 to 363 m a.s.l. (Figure 1C) in the Guianan Highlands Moist Forest and Madeira-Tapajós Moist Forest, in areas with a range of monthly precipitation between 61 to 360 mm³ (Figure 1D), and a temperature between 19.8 to 33.3°C (Figure 1E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e:This species present restrict distributional records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga nigriceps\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(McLachlan, 1867):251\u003c/strong\u003e [Type locality: Brasilia [Brazil], [Villa de] Ega; ?, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e:\u0026nbsp;Gerstaecker 1887:124 [Distribution, as \u003cem\u003eLeucochrysa nigriceps\u003c/em\u003e]; Navás 1912-1913:303 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Navás 1913:104 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Navás 1913:104 [Redescription, Taxonomy, Distribution, as \u003cem\u003eLeucochrysa nigriceps\u003c/em\u003e]; Navás 1912-1913:303 [Taxonomy, Distribution, as \u003cem\u003eLeucochrysa nigriceps\u003c/em\u003e]; Nakahara 1915:118 [Taxonomy, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Okamoto 1919:4 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Kimmins 1940:444 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Kimmins 1940:444 [Taxonomy, as \u003cem\u003eLeucochrysa nigriceps\u003c/em\u003e]; Kimmins 1940:444 [Checklist, as \u003cem\u003eNodita nigriceps\u003c/em\u003e]; Banks 1944:34 [Distribution]; Penny 1977:22 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e]; Penny 1977:22 [Distribution]; Penny 1977:22 [Checklist, as \u003cem\u003eLeucochrysa nigriceps\u003c/em\u003e]; Brooks and Barnard 1990:276 [Checklist, \u003cem\u003eGonzaga nigriceps\u003c/em\u003e \u003cstrong\u003ecomb. nov.\u003c/strong\u003e]; Whittington 2002:379 [Distribution]; El Hamouly and Fadl 2011:97 [Checklist, as \u003cem\u003eChrysopa nigriceps\u003c/em\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Brazil (\u003cstrong\u003eAL\u003c/strong\u003e*, AM, \u003cstrong\u003eBA\u003c/strong\u003e, ES, \u003cstrong\u003ePE\u003c/strong\u003e, RJ, SC) Colombia, Ecuador, Guyana, Peru, Suriname and Venezuela.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known occurrence records between 27 to 953 m a.s.l. (Figure 1C) in the Alto Paraná Atlantic Forests, Bahia Coastal Forests, Guianan Highlands Moist Forests, Iquitos Varzeá, Pernambuco Coastal Forests, Purus Varzeá, Serra Do Mar Coastal Forests, Solimoes-Japurá Moist Forest, and Southern Atlantic Mangroves in areas with a range of monthly precipitation between 26 to 360 mm³ (Figure 1D), and a temperature between 8.7 to 33°C (Figure 1E).\u0026nbsp;Specimens were collected using light pan and malaise traps set near aquatic environments, indicating a possible association with riparian forest habitats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e: The fc.LQH_rm.1 model (AUC = 0.869; CBI = 0.620) highlighted its preference for environments with minimal dry-season precipitation (bio14), high wet-quarter precipitation (bio16), moderate isothermality (bio03), and thermal seasonality (bio04). Daily temperature range (bio02) negatively impacts suitability, indicating adaptation to stable microclimates. This species shows high environmental suitability on the Central American in Pacific Lowlands, Veracruz, and Yucatan Peninsula Province, and in South American in Guyana Pronvice, Amazon Basin, Atlantic Forest and east of Caatinga domain \u0026nbsp; (Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga notatus\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eNavás, 1929:861\u003c/strong\u003e [Type locality: Peru, Iquitos, Navás Collection; Lost?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Peru.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known records at 96 m a.s.l. (Figure 1C) in the Iquitos Várzea, in areas with a range of monthly precipitation between 185 to 312 mm³ (Figure 1D), and a temperature between 20.3 to 31.8°C (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e:This species present restrict distributional records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga palliatus\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eNavás, 1929:860\u003c/strong\u003e[Type locality: Brazil: Espirito Santo – Navás Collection; Lost?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Brazil (ES).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known records at 771 m a.s.l. (Figure 1C) in the Bahia Costal Forest, in areas with a range of monthly precipitation between 50 to 203 mm³ (Figure 1D), and a temperature between 10.4 to 27.2°C (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e:This species present restrict distributional records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga palliceps\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(McLachlan, 1867:251)\u003c/strong\u003e[Type locality: Type locality: Brasilia [Brazil], [Villa de] Ega, McLachlan Collection; Lost?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Navás 1913:149 [Checklist, as \u003cem\u003eChrysopa palliceps\u003c/em\u003e]; Navás 1913:149 [Redescription, Taxonomy, Distribution, as \u003cem\u003eLeucochrysa palliceps\u003c/em\u003e]; Navás 1928:126 [Available, First Description, as \u003cem\u003eNodita nevermanni\u003c/em\u003e]; Banks 1944:20 [Distribution, as \u003cem\u003eNodita palliceps\u003c/em\u003e]; Banks 1945:160 [Taxonomy, as \u003cem\u003eNodita nevermanni\u003c/em\u003e]; Penny 1977:27 [Checklist, as \u003cem\u003eChrysopa palliceps\u003c/em\u003e]; Penny 1977:27 [Checklist, as \u003cem\u003eLeucochrysa palliceps\u003c/em\u003e]; Penny 1977:26 [Distribution, as \u003cem\u003eNodita nevermanni\u003c/em\u003e]; Penny 1977:27 [Distribution, as \u003cem\u003eNodita palliceps\u003c/em\u003e]; Brooks and Barnard 1990:277 [Checklist, as \u003cem\u003eLeucochrysa\u003c/em\u003e (\u003cem\u003eNodita\u003c/em\u003e) \u003cem\u003enevermanni\u003c/em\u003e]; Brooks and Barnard 1990:277 [Checklist, as \u003cem\u003eLeucochrysa\u003c/em\u003e (\u003cem\u003eNodita\u003c/em\u003e) \u003cem\u003epalliceps\u003c/em\u003e]; Penny 2001:12 [Taxonomy, as \u003cem\u003eLeucochrysa\u003c/em\u003e (\u003cem\u003eNodita\u003c/em\u003e) \u003cem\u003enevermanni\u003c/em\u003e]; Penny 2001:12 [Taxonomy, \u003cem\u003eLeucochrysa\u003c/em\u003e (\u003cem\u003eNodita\u003c/em\u003e) \u003cem\u003epalliceps\u003c/em\u003e]; Penny in Penny 2002:191 [Redescription, Taxonomy, Distribution, \u003cem\u003eGonzaga palliceps\u003c/em\u003e \u003cstrong\u003ecomb. nov.\u003c/strong\u003e]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Brazil (AM, \u003cstrong\u003eDF\u003c/strong\u003e*, \u003cstrong\u003eSP\u003c/strong\u003e*), Costa Rica, and Guyana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known occurrence records between 17 to 1071 m a.s.l. (Figure 1C) in the Alto Paraná Atlantic Forests, Cerrado, Guianan Moist Forests, Isthmian-Atlantic Moist Forests, Purus Varzeá, and Southern Mesoamerican Pacific Mangroves, in areas with a range of monthly precipitation between 8 to 424 mm³ (Figure 1D), and a temperature between 10.6 to 32.4°C (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e: The fc.LQ_rm.1 model (AUC = 0.914; CBI = 0.838) identified isothermality (bio03), mean wet-quarter temperature (bio08), and precipitation seasonality (bio15) as positive predictors. Extreme hydrological conditions (bio13², bio16², bio19²) and daily temperature range (bio02) reduce suitability, reflecting sensitivity to abrupt fluctuations. This species shows high environmental suitability in the coastal tropical regions of Central and South American. Specifically, it is well-suited on the Central American in west (Pacific Lowlands), and Pacific dominion. In South American in coastal region of Boreal Brazilian dominion, Caatinga province and South American transition zone on Atacama and Desert provinces (Figure 2D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga soroanus\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eAlayo, 1968:60\u003c/strong\u003e[Type locality: Cuba: Las Villas, Cienfuegos, Arboreto de Soledad, CZACC, ?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Penny 1977 [Distribution]; Brooks and Barnard 1990 [Checklist].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Cuba.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known occurrence records between 35 to 293 m a.s.l. (Figure 1C) in the Cuban Dry Forests, in areas with a range of monthly precipitation between 20 to 219 mm³ (Figure 1D), and a temperature between 15.7 to 31.9°C (Figure 1E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e: The fc.LQH_rm.2 model (AUC = 0.999; CBI = 1.000) showed exceptional accuracy, linking its distribution to mean warm-quarter temperature (bio10), minimal dry-month precipitation (bio14), and wet-month precipitation (bio13). Extreme thermal (bio04²) and hydrological variability (bio12², bio15², bio19²) negatively affect suitability, emphasizing reliance on climatically stable environments. This species shows high environmental suitability in Cuba Province, and central west of Yucatan Province (Figure 2H).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Navás, 1913:318\u003c/strong\u003e[Type locality: Guatemala: San Géronimo – Navás Collection; Lost?].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e: Banks 1914–1915:624 [Redescription, Taxonomy, Distribution]; Banks 1914–1915:58 [Distribution]; Navás 1924:326 [Distribution]; Navás 1927:319 [Distribution]; Navás 1929:34 [Distribution]; Banks 1944:172 [Distribution]; Banks 1945:22 [Distribution]; Penny 1977:240 [Type Species Listed]; Monserrat 1985:276 [Checklist]; Brooks and Barnard 1990:578 [Distribution]; Oswald et al. 2002:191 [Redescription, Taxonomy, Distribution]; Penny in Penny 2002:171 [Checklist].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e: Bazil (ES, SC), \u003cstrong\u003eColombia\u003c/strong\u003e*, Costa Rica, Guatemala, \u003cstrong\u003eHonduras\u003c/strong\u003e*, \u003cstrong\u003eMexico\u003c/strong\u003e*, Panamá, Venezuela.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBionomics\u003c/strong\u003e: This species has known occurrence records between 16 to 2291 m a.s.l. (Figure 1C) in the Bahia Coastal Forest, Cauca Valley Montane Forest, Central American Dry, Montane and Pine-Oak Forests, Costa Rican Seasonal Moist Forests, Isthmian-Atlantic and Pacific Moist Forests, La Costa Xeric Shrublands, Magdalena Valley Montane Forests, Petán-Veracruz Moist Forests, Santa Marta Montane Forests, Sierra Madre Occidental, Oriental and Del Sur Pine-Oak Forests, Talamancan Montane Forests, Veracruz and Yucatán Moist Forests, in areas with a range of monthly precipitation between 3 to 557 mm³ (Figure 1D), and a temperature between 5.9 to 34.6°C (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks:\u0026nbsp;\u003c/strong\u003e\u003cem\u003eGonzaga torquatus\u003c/em\u003e shows a disjunct distribution in Brazil (ES, SC), Colombia, Costa Rica, Guatemala, Honduras, Mexico, Panama, and Venezuela. The fc.LQ_rm.1 model (AUC = 0.920; CBI = 0.957) identified maximum warm-month temperature (bio05), isothermality (bio03), and cold-month temperature (bio09) as key predictors. Sensitivity to daily temperature range (bio02²) and hydrological extremes (bio17²), highlight ecological constraints. This species shows high environmental suitability in all areas bellow Mexican transition zone for Atlantic and Pacific coastal tropical regions of Central and South American. Specifically, it is well-suited on all Central American, and Pacific dominion. In South American in coastal region of Boreal Brazilian dominion, Caatinga province, All Panama dominion and South American transition zone on Atacama and Desert provinces (Figure 2F).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe genus \u003cem\u003eGonzaga\u003c/em\u003e exhibits contrasting distribution patterns across Neotropics, with some species displaying broad geographic ranges and others showing extremely restricted distributions, rendering them highly vulnerable to extinction. \u003cem\u003eGonzaga\u003c/em\u003e's specimens are rarely found in collections and have not received detailed systematic treatment recently (Tauber et al. 2008). The result of this is that in this work alone aggregated data from online databases, museum collections, and citizen science initiatives (INaturalist) account for 46% of known records, underscoring the critical need to strengthen these data sources, particularly in tropical regions characterized by high biodiversity and endemism (Brooks and Barnard 1990). This study substantially expanded the knowledge of the geographic distribution of the genus \u003cem\u003eGonzaga\u003c/em\u003e, highlighting the importance of integrating multiple data sources—citizen science (iNaturalist), scientific literature, and new field records—to reduce biogeographical knowledge gaps in Neotropical insects.\u003c/p\u003e\n\u003cp\u003eThree species showed notable range expansions: \u003cem\u003eGonzaga nigriceps\u003c/em\u003e, recorded for the first time in northeastern Brazil (AL, BA, and PE); \u003cem\u003eG. palliceps\u003c/em\u003e, now also found in the Federal District and São Paulo; and \u003cem\u003eG. torquatus\u003c/em\u003e, with new records from Mexico, Honduras, and Colombia. These expansions reveal broader occurrence patterns than previously recognized for these species. The latitudinal distribution of the genus extends from Nuevo León, Mexico, to Santa Catarina, Brazil, encompassing various tropical and subtropical biomes across Central and South America. Among the species, \u003cem\u003eG. torquatus\u003c/em\u003e has the widest distribution, followed by \u003cem\u003eG. palliceps\u003c/em\u003e and \u003cem\u003eG. nigriceps\u003c/em\u003e. In contrast, \u003cem\u003eG. amabilis\u003c/em\u003e, \u003cem\u003eG. notatus\u003c/em\u003e, \u003cem\u003eG. palliatus\u003c/em\u003e, \u003cem\u003eG. callipterus\u003c/em\u003e, and \u003cem\u003eG. soroanus\u003c/em\u003e show highly restricted distributions, being known from only one or two localities. Environmental analyses indicate that most species occur at elevations below 500 m, with exceptions such as \u003cem\u003eG. palliceps\u003c/em\u003e, which reach up to 1071 m a.s.l. The species inhabit areas with wide variation in precipitation (3–557 mm/month) and temperature (5.9–34.6 °C), although most are associated with warm, humid climates and low thermal variation.\u003c/p\u003e\n\u003cp\u003eModels demonstrated high reliability (AUC \u0026gt; 0.86; CBI ≥ 0.62), with \u003cem\u003eG. soroanus\u003c/em\u003e showing near-perfect validation (AUC = 0.999; CBI = 1.0), likely due to its restricted Cuban province distribution.The models highlight the \u003cem\u003eGonzaga\u003c/em\u003e species adaptability across diverse biomes, with high environmental suitability concentrated in the Neotropical region (\u003cem\u003esensu\u0026nbsp;\u003c/em\u003eMorrone et al. 2019). Ecological niche modeling supports these patterns, indicating high environmental suitability for \u003cem\u003eG. nigriceps\u003c/em\u003e under diverse climatic conditions, while \u003cem\u003eG. palliceps\u003c/em\u003e and \u003cem\u003eG. soroanus\u003c/em\u003e show a greater dependence on stable microclimates, especially in tropical coastal regions of Central and South America.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSuitable areas encompass tropical and subtropical moist and dry broadleaf forests, xeric shrublands, savannas, mangroves, and inland aquatic systems. Disjunct distributions between the Amazon and Atlantic Forests suggest historical influences, such as Pleistocene climatic fluctuations and the development of the Dry Diagonal. Unexplored regions—including the Atacama and Desert provinces, and coastal Atlantic areas of South America, particularly within the Amazon and Atlantic domains—also exhibit high environmental suitability, indicating potential distribution and highlighting these areas as priorities for future research efforts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecies with limited occurrence records (Figure 1A) are at elevated extinction risk, emphasizing the need to expand scientific collections and integrate citizen science data. To mitigate these threats, priority actions include: (1) conducting field surveys in undocumented high-suitability areas, such as the western Andes and Lesser Antilles; (2) monitoring hydrological and thermal thresholds to anticipate climate impacts; and (3) establishing cross-border conservation policies for species spanning multiple ecoregions. These measures are essential to address knowledge gaps, refine preservation strategies, and ensure the long-term survival of the \u003cem\u003eGonzaga\u003c/em\u003e genus in the face of rapid environmental change.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study advanced the understanding of \u003cem\u003eGonzaga\u003c/em\u003e by clarifying current distribution patterns, identifying environmentally suitable areas, and revealing ecological tolerances and vulnerabilities across species. By integrating diverse data sources and ecological niche models, it highlights both the \u003cem\u003eGonzaga\u003c/em\u003e species adaptability to tropical environments and the need for targeted conservation. Despite these advances, critical gaps remain in taxonomy, phylogenetics, and biogeographic history, which limit our understanding of evolutionary processes and diversification patterns. Future efforts should prioritize integrative taxonomic revisions and phylogenetic analyses to test biogeographic hypotheses\u0026mdash;such as the influence of the South American Dry Diagonal and potential trans-Andean dispersal. Ecological studies are also needed to investigate life-history traits that may explain range limitations. Ecological models proved reliable in identifying priority areas for future sampling and conservation, reinforcing the value of combining modeling, fieldwork, and citizen science to address biodiversity shortfalls and refine conservation strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe thank the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) for collecting permits. RP also thanks to the PRAPG-CAPES-88887.986811/2024-00 for the post-doctoral fellowship. We would also like to thank Prof. Dr. Adolfo Ricardo Calor of the Museu de História Natural da Bahia (UFBA), Bahia state, Brazil, for their support and donating some of the material used in this work. We both thank iNaturalist and Global Biodiversity Information Facility (GBIF), its creators, and all contributors for generating and sharing biodiversity data. The species records used in this study were accessed through the GBIF, which includes valuable citizen science contributions from iNaturalist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was funded by post-doctoral fellowship of Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (PRAPG-CAPES-88887.986811/2024-00).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare that are relevant of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and Informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRP and CCM conceived the study and defined its objectives. RP conducted the analyses, interpreted the results, and wrote. CCM identified the material and revised literature. PCG was responsible for the field collections, provided the specimens for analysis, and made the laboratory and museum facilities available. All authors revised the text and contributed with suggestions and corrections to the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available in supplementary material.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlayo AD (1968) Los neur\u0026oacute;pteros de Cuba (No. 2). Academia de Ciencias de Cuba, Havana\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAri\u0026ntilde;o AH (2010) Approaches to estimating the universe of natural history collections data. Biodivers Inf 7(2):81\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17161/bi.v7i2.3991\u003c/span\u003e\u003cspan address=\"10.17161/bi.v7i2.3991\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanks N (1914\u0026ndash;1915) New Neuropteroid Insects, Native and Exotic. \u003cem\u003eProc Acad Nat Sci Phila\u003c/em\u003e 66(3):608\u0026ndash;632\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanks N (1944) Neuroptera of northern South America. Part III. Bol Entomol Venez 3:1\u0026ndash;34\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanks N (1945) A review of Chrysopidae (Nohochrysidae) of Central America. Psyche 52:139\u0026ndash;174\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyes DH, Evans DM, Fox R et al (2021) Street lighting has detrimental impacts on local insect populations. Sci Adv 7(35):eabi8322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/sciadv.abi8322\u003c/span\u003e\u003cspan address=\"10.1126/sciadv.abi8322\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks SJ, Barnard PC (1990) The green lacewings of the world: a generic review (Neuroptera: Chrysopidae). Bull Br Mus (Nat Hist) Entomol 59:117\u0026ndash;286\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChowdhury S, Aich U, Rokonuzzaman M et al (2023) Increasing biodiversity knowledge through social media: A case study from tropical Bangladesh. Bioscience 73(6):453\u0026ndash;459\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eContreras-Ramos A, Rosas MV (2014) Biodiversity of Megaloptera and Raphidoptera in Mexico. Rev Mex Biodivers 85:257\u0026ndash;263. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7550/rmb.32049\u003c/span\u003e\u003cspan address=\"10.7550/rmb.32049\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDangles O, Casas J (2019) Ecosystem services provided by insects for achieving sustainable development goals. Ecosyst Serv 35:109\u0026ndash;115. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecoser.2018.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.ecoser.2018.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEisenhauer N, Bonn A, Guerra CA (2019) Recognizing the quiet extinction of invertebrates. Nat Commun 10(1):50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41467-018-07916-1\u003c/span\u003e\u003cspan address=\"10.1038/s41467-018-07916-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl-Hamouly H, Fadl HH (2011) Checklist of order Neuroptera in Egypt, with a key to families. Afr J Biol Sci 7(1):85\u0026ndash;104\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFunk VA (2018) Collections-based science in the 21st century. J Syst Evol 56(3):175\u0026ndash;193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jse.12315\u003c/span\u003e\u003cspan address=\"10.1111/jse.12315\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGerstaecker A (1888) Weitere Beitr\u0026auml;ge zur Artenkenntniss des Neuroptera Megaloptera. Mitt Naturwiss Ver Neu-Vorpommern Rugen 19(1):89\u0026ndash;130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143(1):29\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1148/radiology.143.1.7063747\u003c/span\u003e\u003cspan address=\"10.1148/radiology.143.1.7063747\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKass JM, Pinilla-Buitrago GE, Paz A et al (2023) Wallace 2: a shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions. Ecography 2023(3):e06547. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ecog.06547\u003c/span\u003e\u003cspan address=\"10.1111/ecog.06547\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKharouba HM, Lewthwaite JMM, Guralnick R et al (2018) Using insect natural history collections to study global change impacts: challenges and opportunities. Philos Trans R Soc B 374:20170405. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rstb.2017.0405\u003c/span\u003e\u003cspan address=\"10.1098/rstb.2017.0405\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKimmins DE (1940) Notes on some types of Chrysopid\u0026aelig; (Neuroptera) in the British Museum Collections. J Nat Hist 5(29):442\u0026ndash;449. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00222934008527058\u003c/span\u003e\u003cspan address=\"10.1080/00222934008527058\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuhn M, Jackson S, Cimentada J et al (2022) Package Corrr\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamoreux JF, Morrison JC, Ricketts TH et al (2006) Global tests of biodiversity concordance and the importance of endemism. Nature 440(7081):212\u0026ndash;214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nature04291\u003c/span\u003e\u003cspan address=\"10.1038/nature04291\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLister AM (2011) Natural history collections as sources of long-term datasets. Trends Ecol Evol 26(4):153\u0026ndash;154. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tree.2010.12.009\u003c/span\u003e\u003cspan address=\"10.1016/j.tree.2010.12.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMonserrat VJ (1985) Lista de los tipos de Mecoptera y Neuroptera (Insecta) de la colecci\u0026oacute;n L. Nav\u0026aacute;s, depositados en el Museo de Zoolog\u0026iacute;a de Barcelona. Misc Zool 9:233\u0026ndash;243\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorrone JJ, Escalante T, Rodr\u0026iacute;guez-Tapia G et al (2022) Biogeographic regionalization of the Neotropical region: New map and shapefile. Acad Bras Cienc 94:e20211167. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0001-3765202220211167\u003c/span\u003e\u003cspan address=\"10.1590/0001-3765202220211167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuscarella R, Galante PJ, Soley-Guardia M, Boria RA, Kass JM, Uriarte M, Anderson RP (2014) ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol Evol 5(11):1198\u0026ndash;1205. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/2041-210X.12261\u003c/span\u003e\u003cspan address=\"10.1111/2041-210X.12261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMyers N, Mittermeier RA, Mittermeier CG et al (2000) Biodiversity hotspots for conservation priorities. Nature 403(6772):853\u0026ndash;858. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/35002501\u003c/span\u003e\u003cspan address=\"10.1038/35002501\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakahara W (1915) A synonymic list of Japanese Chrysopidae, with descriptions of one new genus and three new species. Ann Entomol Soc Am 8(2):117\u0026ndash;123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/aesa/8.2.117\u003c/span\u003e\u003cspan address=\"10.1093/aesa/8.2.117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1912\u0026ndash;1913) Les Chrysopides (Ins. Nevr.) du Musee de Londres [Ia]. \u003cem\u003eAnn Soc Sci Bruxelles\u003c/em\u003e 37(pt 2):292\u0026ndash;330\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1913) Crisopidos sudamericanos. Broteria (Zool) 11:73\u0026ndash;104\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1924) Crisopidos (Ins. Neur.) neotropicos [I]. Rev Chil Hist Nat 27:110\u0026ndash;116\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1927) Insectos neotropicos. 3.a serie. Rev Chil Hist Nat 31:316\u0026ndash;328\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1928) Insectos del Museo de Hamburgo. Primera [I] serie. Bol Soc Entomol Esp 11:59\u0026ndash;67 90\u0026ndash;100\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas L (1929) Insecta nova. Series XIII. Mem Accad Pontif Nuovi Lincei 12:15\u0026ndash;23\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkamoto H (1919) Studies on the Chrysopidae of Japan. Rep Hokkaido Agric Exp Stn 9:1\u0026ndash;76\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOswald JD, Contreras-Ramos A, Penny ND (2002) Neuroptera (Neuropterida). In: Llorente BJ, Morrone JJ, Gonz\u0026aacute;lez SE (eds) Biodiversidad, taxonom\u0026iacute;a y biogeograf\u0026iacute;a de artr\u0026oacute;podos de M\u0026eacute;xico: hacia una s\u0026iacute;ntesis de su conocimiento, vol III. UNAM, M\u0026eacute;xico DF, pp 559\u0026ndash;581\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOswald JD, Machado RJ (2018) Biodiversity of the Neuropterida (Insecta: Neuroptera: Megaloptera, and Raphidioptera). In: Foottit RG, Adler PH (eds) Insect biodiversity: science and society, vol 2. Wiley, Hoboken, pp 627\u0026ndash;672\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenny ND (1977) Lista de megaloptera, neuroptera e raphidioptera do M\u0026eacute;xico, Am\u0026eacute;rica Central, ilhas Cara\u0026iacute;bas e Am\u0026eacute;rica do Sul. Acta Amaz 7(4 Suppl 1):5\u0026ndash;61\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenny ND (2001) New species of Chrysopidae (Neuroptera: Chrysopidae) from Costa Rica, with selected taxonomic notes and a neotype designation. Entomol News 112(1):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenny ND (2002) Family Chrysopidae. In: Penny ND (ed) \u003cem\u003eA guide to the lacewings (Neuroptera) of Costa Rica\u003c/em\u003e. Proc Calif Acad Sci 53:187\u0026ndash;227\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eP\u0026eacute;rez-Lachaud G, Lachaud JP (2017) Hidden biodiversity in entomological collections: The overlooked co-occurrence of dipteran and hymenopteran ant parasitoids in stored biological material. PLoS ONE 12(9):e0184614. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0184614\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0184614\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhillips SJ (2017) A Brief Tutorial on Maxent. Dispon\u0026iacute;vel em: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://biodiversityinformatics.amnh.org/open_source/maxent/\u003c/span\u003e\u003cspan address=\"http://biodiversityinformatics.amnh.org/open_source/maxent/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Acesso em: 23 mai. 2025\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Bayo F, Wyckhuys KAG (2019) Worldwide decline of the entomofauna: A review of its drivers. Biol Conserv 232:8\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biocon.2019.01.020\u003c/span\u003e\u003cspan address=\"10.1016/j.biocon.2019.01.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos BF, Hoppe JPM (2018) Filling gaps in species distributions through the study of biological collections: 415 new distribution records for Neotropical Cryptinae (Hymenoptera, Ichneumonidae). Rev Bras Entomol 62:288\u0026ndash;291. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.rbe.2018.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.rbe.2018.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShcheglovitova M, Anderson RP (2013) Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes. Ecol Model 269:9\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolmodel.2013.08.011\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolmodel.2013.08.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith VS, Blagoderov V (2012) Bringing collections out of the dark. ZooKeys 209:1\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTauber CA, Albuquerque GS, Tauber MJ (2008) \u003cem\u003eGonzaga nigriceps\u003c/em\u003e (McLachlan) (Neuroptera: Chrysopidae): descriptions of larvae and adults, biological notes, and generic affiliation. Proc Entomol Soc Wash 110(2):417\u0026ndash;438. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4289/07-045.1\u003c/span\u003e\u003cspan address=\"10.4289/07-045.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTauber CA, Pantaleoni RA (2018) Type specimens of Neotropical Chrysopidae (Neuroptera) in Italian museums. Trop Zool 31(4):177\u0026ndash;199. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/03946975.2018.1493169\u003c/span\u003e\u003cspan address=\"10.1080/03946975.2018.1493169\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWagner DL, Grames EM, Forister ML et al (2021) Insect decline in the Anthropocene: Death by a thousand cuts. Proc Natl Acad Sci USA 118(2):e2023989118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.2023989118\u003c/span\u003e\u003cspan address=\"10.1073/pnas.2023989118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhittington AE (2002) Resources in Scottish neuropterology. Acta Zool Acad Sci Hung 48(2):371\u0026ndash;387\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biologia","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"biol","sideBox":"Learn more about [Biologia](http://link.springer.com/journal/11756)","snPcode":"11756","submissionUrl":"https://www.editorialmanager.com/biol/default2.aspx","title":"Biologia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"citizen science, conservation, distribution modelling, Leucochrysini, Neuropterida","lastPublishedDoi":"10.21203/rs.3.rs-6763568/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6763568/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the geographic distribution, environmental ranges and environmental potential of \u003cem\u003eGonzaga\u003c/em\u003e species (Chrysopidae, Neuroptera) across the Neotropical region. Biological collections and citizen science databases were pivotal in compiling distribution records, revealing novel data for several species. For instance, \u003cem\u003eGonzaga nigriceps\u003c/em\u003e was recorded for the first time in Northeastern Brazil, while \u003cem\u003eGonzaga palliceps\u003c/em\u003e had new records in the Federal District and S\u0026atilde;o Paulo. \u003cem\u003eGonzaga torquatus\u003c/em\u003e extended its range to Colombia, Honduras, and Mexico. The study employed ecological niche models to infer the potential distribution of these species, highlighting areas of high environmental suitability in ecosystems such as moist and dry tropical forests, mangroves, and savannas. The analyses identified areas of high environmental suitability for the studied species, particularly in the Neotropical region, while also pinpointing knowledge gaps and unexplored potential habitat areas, such as in the subantarctic region of Patagonia. These findings are crucial for conservation, providing insights into the ecological requirements of the species and guiding preservation strategies in priority areas. The study underscores the ongoing importance of citizen science initiatives and the strengthening of biological collections for understanding and safeguarding Neotropical biodiversity, especially amidst climate change and habitat loss. This work contributes not only to the knowledge of \u003cem\u003eGonzaga\u003c/em\u003e species distributions but also to the application of predictive models in biodiversity, evolutionary, and conservation studies, encouraging future field research to validate the models and expand our understanding of these unique components of Neotropical biodiversity.\u003c/p\u003e","manuscriptTitle":"Citizen Science Databases and Entomological Collections: Insights into Environmental Ranges and Potential Distribution of Gonzaga McLachlan, 1867 (Chrysopidae, Neuroptera)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 18:33:48","doi":"10.21203/rs.3.rs-6763568/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-10-25T01:01:19+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-04T06:33:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-30T09:46:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biologia","date":"2025-05-28T18:02:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biologia","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"biol","sideBox":"Learn more about [Biologia](http://link.springer.com/journal/11756)","snPcode":"11756","submissionUrl":"https://www.editorialmanager.com/biol/default2.aspx","title":"Biologia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"423c7e71-58c6-4ff5-8afa-75125b9734fd","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:01:11+00:00","versionOfRecord":{"articleIdentity":"rs-6763568","link":"https://doi.org/10.1007/s11756-025-02093-1","journal":{"identity":"biologia","isVorOnly":false,"title":"Biologia"},"publishedOn":"2026-02-09 15:57:45","publishedOnDateReadable":"February 9th, 2026"},"versionCreatedAt":"2025-06-09 18:33:48","video":"","vorDoi":"10.1007/s11756-025-02093-1","vorDoiUrl":"https://doi.org/10.1007/s11756-025-02093-1","workflowStages":[]},"version":"v1","identity":"rs-6763568","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6763568","identity":"rs-6763568","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}