A peer-reviewed open-access journal ZooKeys 1080: 21—52 (2022) AERA AE #ZooKeys https:/ / ZOO keys. pensoft.net Launched to accelerate biodiversity research Seasonal and microclimatic effects on leaf beetles (Coleoptera, Chrysomelidae) in a tropical forest fragment in northeastern Mexico José Norberto Lucio-Garcia', Uriel Jeshua Sanchez-Reyes', Jorge Victor Horta-Vega', Jesus Lumar Reyes-Mufioz’, Shawn M. Clark’, Santiago Nifio-Maldonado* I Zecnolégico Nacional de México-Instituto Tecnolégico de Cd. Victoria, Blvd. Emilio Portes Gil No. 1301, CP 87010. Cd. Victoria, Tamaulipas, México 2 Facultad de Ciencias Biolégicas, Universidad Juarez del Estado de Durango. Av. Universidad S/N, Fracc. Filadelfia, 35010 Gomez Palacio, Durango, Mexico 3 Brigham Young University, Life Science Museum, Provo, Utah 84602, USA 4 Universidad Auténoma de Tamaulipas, Facultad de Ingenieria y Ciencias, Centro Universitario Victoria, C.P 87149. Cd. Victoria, Tamaulipas, México Corresponding author: Santiago Nifio-Maldonado (coliopteranino@hotmail.com) Academic editor: D. D. McKenna | Received 14 October 2021 | Accepted 9 December 2021 | Published 4 January 2022 http://zoobank.org/EDOFO3A2-C3FB-4CD7-9D6C-082ADD35A5C4 Citation: Lucio-Garcia JN, Sanchez-Reyes UJ, Horta-Vega JV, Reyes-Mufioz JL, Clark SM, Nifio-Maldonado S (2022) Seasonal and microclimatic effects on leaf beetles (Coleoptera, Chrysomelidae) in a tropical forest fragment in northeastern Mexico. ZooKeys 1080: 21-52. https://doi.org/10.3897/zookeys. 1080.76522 Abstract Leaf beetles (Coleoptera: Chrysomelidae) constitute a family of abundant, diverse, and ecologically important herbivorous insects, due to their high specificity with host plants, a close association with vegetation and a great sensitivity to microclimatic variation (factors that are modified gradually during the rainy and dry seasons). Therefore, the effects of seasonality (rainy and dry seasons) and microclimate on the community attributes of chrysomelids were evaluated in a semideciduous tropical forest fragment of northeastern Mexico. Monthly sampling was conducted, between March 2016 and February 2017, with an entomological sweep net in 18 plots of 20 x 20 m, randomly distributed from 320 to 480 m a.s.l. Seven microclimatic variables were simultaneously recorded during each of the samplings, using a portable weather station. In total, 216 samples were collected at the end of the study, of which 2,103 specimens, six subfamilies, 46 genera, and 71 species were obtained. The subfamily Galerucinae had the highest number of specimens and species in the study area, followed by Cassidinae. Seasonality caused significant changes in the abundance and number of leaf beetle species: highest richness was recorded in the rainy season, Copyright José Norberto Lucio-Garcia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 22 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) with 60 species, while the highest diversity (lowest dominance and highest H’ index) was obtained in the dry season. Seasonal inventory completeness of leaf beetles approached (rainy season) or was higher (dry season) than 70%, while the faunistic similarity between seasons was 0.63%. The outlying mean index was significant in both seasons; of the seven microclimatic variables analyzed, only temperature, heat index, evapotranspiration and wind speed were significantly related to changes in abundance of Chrysomelidae. Association between microclimate and leaf beetles was higher in the dry season, with a difference in the value of importance of the abiotic variables. The results indicated that each species exhibited a different response pattern to the microclimate, depending on the season, which suggests that the species may exhibit modifications in their niche requirements according to abiotic conditions. However, the investigations must be replicated in other regions, in order to obtain a better characterization of the seasonal and microclimatic influence on the family Chrysomelidae. Keywords Abiotic factors, community response, ecological niche, phytophagous insects, seasonal changes Introduction Accelerated loss of biological diversity, as well as the alterations in native ecosystems as a result of human activities, are among the most important environmental issues at a global level (Challenger and Dirzo 2009). These include land cover fragmentation, overexploitation of natural resources, pollution, and climate change (Hautier et al. 2015). Abiotic modification produces direct effects on organisms, affecting physiology, behavior, and reproduction (Uribe-Botero 2015). Changes in precipitation and increased environmental temperature (Schaefer et al. 2008) are likely to cause alterations in abundance and even loss of species (Brook et al. 2008), as well as changes in their geographical distribution (Parmesan and Yohe 2003; Root et al. 2003). However, these responses are variable, based on the type of organism and its niche breadth (Vieé et al. 2009). Therefore, changes in climatic abiotic variables are key factors in the composition and structure of biological communities, besides other ecological aspects (Pimm 2007), such as seasonal changes during wet and dry seasons (Wolda 1988; Rzedowski 2006). An aspect of greatest influence on these communities is the microclimate (Cloudsley- Thompson 1962). This is the result of local spatial and seasonal variations in climate and has been shown to play an important role in the dynamics of metapopulations (Checa et al. 2014). Likewise, it is essential for the survival and development of the species, affecting larval diapause or growth, or indirectly modifying the availability of food resources (Currano et al. 2008; DeLucia et al. 2008). The microclimate is related to seasonal variations in the communities of phytophagous insects (Chen et al. 1999), but its specific influence has been scarcely studied. Phytophagous insects are among the most important trophic groups that respond significantly to climatic changes. Their presence is key in natural or anthropic ecosys- tems, either playing a relevant role in nutrient cycling processes, or in the diet of other organisms (Iannacone and Alvarifio 2006). Furthermore, their physiological processes are determined by the conditions of the environment (Régniére 2009). Seasonal and microclimatic effects on leaf beetles Chrysomelidae 23 Leaf beetles (Coleoptera: Chrysomelidae) constitute a model family to evaluate the seasonal effects of abiotic variation on herbivorous insect communities, since they occupy one of the first places in worldwide diversity (Santiago-Blay 1994). Most chrysomelid species exhibit phytophagous feeding habits and a close relationship with their host plants, as well as a great sensitivity to microclimatic variation (Nifo- Maldonado and Sanchez-Reyes 2017). Also, they are considered to be a group with important potential for monitoring natural areas (Furth et al. 2003). ‘The present study was carried out in a semideciduous tropical forest (STF) fragment in the municipality of Victoria, Tamaulipas, in northeastern Mexico. ‘The area is included in the biogeographic province of the Sierra Madre Oriental and is located within one of the 15 panbiogeographic nodes of Mexico (Morrone and Marquez 2008). ‘Therefore, it constitutes a region with a high priority for conservation (CONABIO etal. 2007). Despite this, there are no studies in STF evaluating the effect of seasonality and microclimate on the family Chrysomelidae. It is important to recognize the factors that restrict the distribution of the species, and thus further delimit efficient conservation strategies of this important area. Based on the above, the objectives of this study were 1) to prepare a faunistic list of chrysomelid species, 2) to compare their richness, abundance, and diversity between seasons, 3) to define the abiotic variables seasonally related to the presence and abundance of the species, and 4) to delimit the breadth niche and categorize the leaf beetles as specialists or generalists, based on their variation related to the seasonal abiotic environment. Materials and methods Study area The study area of semideciduous tropical forest (STF) is located in the Ejido Santa Ana, municipality of Victoria, in the center of the state of Tamaulipas, northeastern Mexico 23°52'4.27"N, 99°13'51.37"W and 23° 47'23.06"N, 99°18'10.22"W (DMS) (Fig. 1). It is included in the biogeographic province of the Sierra Madre Oriental (SMO), converging to the south with Peregrina Canyon, within the Natural Protected Area (NPA) “Altas Cumbres.” Two climate groups characteristic of Tamaulipas were observed in the area: 1) Semi- warm, sub-humid, with summer rains, averaging temperatures between 16.4 °C and 29.2 °C, and 2) Semi-warm, semi-dry subtype, with average temperatures from 15.1 °C to 22.9 °C. The average annual precipitation is 577 mm, with May to October as the wettest months (rainy season) and November to April having the lowest precipitation (dry season) (Gobierno del Estado 2015). Regarding the semideciduous tropical forest, it is the second richest ecosystem in plant species of the state of Tamaulipas and is located between 350 and 500 m a.s.l, comprising areas adjacent to the margin of rivers and streams. Therefore, this habitat conserves higher environmental humidity for most of the year, protecting it from sudden climatic changes, such as sudden temperature differences (Garcia-Morales et al. 2014). 24 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) 99°18'0"W 99° 16'0"W 99°14'0"W 99°12'0"W 99°10'0"W Santa Ana 23°52'0"N 23°52'0"N 23°50'0"N 23°50'0"N Victoria City 23°48'0"N 23°48'0"N 99° 18'0"W 99° 16'0"W 99° 14'0"W 0 1.75 35 7 10.5 Km 99°12'0"W 99°10'0"W H Sampling plots Elevation (mas!) Ml 307 - 388 MM 600 - 689 MM 845-924 1,086 - 1,172 CJ NPA Altas Cumbres MD 169-244 (9388 - 493 9 689 - 766 MMB 924- 1,004 MM 1,172 - 1,264 (J urban areas 244-307 [493 - 600 MMM 766 - 845 BM 1,004 - 1,086 MMMM 1,264 - 2,144 Figure |. Location of the study area. A Ejido Santa Ana (red point) in Tamaulipas State, Mexico B NPA Altas Cumbres (red polygon) within Victoria municipality in Tamaulipas C Distribution of the sampling plots (blue squares) in the semideciduous tropical forest. Sampling A total of 18 plots measuring 20 x 20 m (400 m’) was randomly established over an approximate land area of 5 km’. Plots were distributed in areas of dense herbaceous and shrub vegetation, separated at least by 10 meters from the main road, in order to minimize anthropogenic influence. Each plot was measured and delimited with a 50 m tape, using trunks, trees, or branches as vertices; the center of the plot was georefer- enced with a Garmin Etrex 30 GPS and then marked with a brightly colored ribbon to facilitate its location in the field. Beetles were sampled with an entomological sweep net of 60 cm length and 40 cm rim diameter. In each plot (sample unit), 200 net beats were made, covering all the sampling area zigzageging on the understory vegetation. The contents of the net were placed inside a polyethylene bag with 70% alcohol and a collecting label data. All of the 18 plots were sampled from 10:00 to 17:00 hours, once a month, from March 2016 to February 2017. Sample bags were processed in the Entomology Laboratory of the Facultad de Ing- enieria y Ciencias, Universidad Auténoma de Tamaulipas. Each sample was placed in a tray with water, plant debris were then removed using entomological forceps, and the insect specimens were afterwards placed in small bottles with 70% alcohol. Later, the contents of each bottle were analyzed in a Petri dish, using a stereoscopic microscope to identify the specimens; chrysomelids were dried on absorbent paper and mounted in opaline triangles, following the methodology of Triplehorn and Johnson (2005). Taxonomic determination of subfamilies was carried out using the keys of Triplehorn and Johnson (2005), while genera and/or species were identified by consulting various Seasonal and microclimatic effects on leaf beetles Chrysomelidae 25 authors (Wilcox 1972; Scherer 1983; White 1993; Flowers 1996; Riley et al. 2002; Staines 2002), as well as by comparison with previously identified specimens. Microclimatic variables were recorded using a Kestrel 3500 portable meteorologi- cal station, with which the following variables were evaluated: maximum wind speed (m/s), average wind speed (m/s), temperature (°C), relative humidity (%), heat index (°C), dew point (°C) and evapotranspiration (°C). Abiotic data collection was carried out in each plot, simultaneously with the sampling of leaf beetles (once a month for each plot, during the period from March 2016 to February 2017). Data analysis Statistical differences in abundance and number of species between seasons were calcu- lated with a non-parametric Mann-Whitney test and a diversity permutation test, respec- tively. Both analyses were conducted using PAST 3.17 software (Hammer et al. 2017). Seasonal estimated richness was determined using Chao 1, Chao 2, Jackknife 1 and ACE non-parametric estimators. These indices are recommended for the min- imum estimate of richness and useful as a complementary measure in biodiversity analyzes (Gotelli and Colwell 2011). Chao 1 considers the abundance of rare species (singletons and doubletons). Chao 2 is robust for presence-absence data. Jackknife 1 is a conservative index based on incidence data of those species found only in a single sample, while ACE is an index that considers the abundance of species represented by 1-10 individuals (Magurran 2004). The estimators were calculated by means of 100 randomizations without replacement in the software EstimateS 9.1.0 (Colwell 2013), based on the abundance of the recorded species. In addition, the Clench model was used to calculate the estimated species richness, following the methods proposed by Jiménez-Valverde and Hortal (2003). This procedure was performed in STATISTICA 8.0 (StatSoft, Inc. 2007). Alpha diversity was estimated using Shannon's entropy index (H’) and Simpson's dominance index (D). Both values were transformed to the effective number of species (true diversity), through the Hill numbers of order (q) 1 and 2, respectively (Jost 2006). To measure beta diversity, the Bray-Curtis similarity index was used, which relates the abundance of the shared species with the total abundance in two samples. Therefore, it constitutes a robust measure for the analysis of biotic similarity between communities (Magurran 2004). All diversity analyses were carried out with PAST software. Association between leaf beetle species and the environmental abiotic variables, as well as the measure of niche breadth, were calculated with the Outlying Mean Index (OMI). ‘This index identifies the niche of the species, or marginality, according to the average distance between the abiotic resources used by each species (centroid) with respect to the total resources available (microclimate) in the area. It gives a more even weight to all sampling units, including those with a low number of species or individuals (Dolédec et al. 2000). First, the OMI assesses the contribution of the abiotic variables to the niche separation of the species by computing a Principal Component Analysis, and higher correlation values (loadings) are interpreted at each of the most 26 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) important axes. Then, a total Inertia (InerO) value is obtained, which is a measure proportional to the average marginality of the species and represents a quantification of the influence of environmental variables on the separation of the species niche. Lastly, the analysis decomposes the inertia associated with the distribution of a species (InerO) into three main parameters: Marginality, Tolerance (T1), and Residual Tolerance (T2) (Dolédec et al. 2000). Marginality represents the deviation of the environmental conditions used by a spe- cies with respect to the average environment for the entire study area. Species with high OMI values have marginal niches (occur in atypical habitats, and are influenced by a specific subset of environment variables), while those with low values have non-margin- al niches (common species occurring in typical habitats, without a specific response to environment variables). Tolerance (T1) measures the dispersion of the assessment units that contain a species along an environmental gradient (the range of habitat of the spe- cies), and it is analogous to the concept of niche breadth: high tolerance values represent greater niche breadth, and the species are distributed in habitats with widely variable conditions (generalist); contrarily, low tolerance values indicate a smaller niche width where a species is distributed in habitats with a limited range of conditions (specialists). Finally, T2 is defined as the variance in the species niche that is not considered by the marginality axes, and it is useful for determining the reliability of a set of environmental conditions for the definition of the niche of each species (Dolédec et al. 2000). Statistical significance of the OMI was determined with a Monte Carlo test, in which the observed marginalities are compared with 10,000 random permutations, in order to reject the null hypothesis that species are equally distributed in relation to (not influenced by) environmental variables (Dolédec et al. 2000). All OMI analyses were carried out in ADE-4 software (Thioulouse et al. 1997), and they were calculated separately for the rainy and dry seasons. Data input consisted of a matrix with the abundances of each of the species in each month/season and a matrix with the values of the seven environmen- tal variables registered in each of the sampling plots. Ordination graphics of centroids and loadings were generated in the same software and later exported to Corel DRAW X3 to be edited. Environmental ranges of species were calculated for each of the significant variables using the Kriging interpolation technique, which is a geostatistical method that quantifies spatial autocorrelation for the prediction and generation of continuous sur- faces (Murillo et al. 2012). Procedures were carried out in ArcGis 10.2.2 (ESRI 2014). Results Overall response of leaf beetles in the semideciduous tropical forest During the study, 2,103 specimens of Chrysomelidae were obtained, involving six subfamilies, 47 genera and 71 species (Appendix 1: Table Al). Galerucinae were most abundant (1,628 specimens = 77%), followed by Cassidinae (410 = 19.44%). Among the other four subfamilies, only 65 specimens (3%) were collected throughout the year, Seasonal and microclimatic effects on leaf beetles Chrysomelidae 27 being 36 in Eumolpinae, 14 in Criocerinae, nine in Chrysomelinae, and six in Crypto- cephalinae. Regarding total richness, Galerucinae represented 51% (36 species), Cas- sidinae 17% (12 species), Eumolpinae 11% (eight species), Chrysomelinae 8% (six species), Criocerinae 7% (five species), and Cryptocephalinae 6% (four species). Species that dominated in abundance in the study area were Centralaphthona diversa (Baly, 1877) (629 individuals), Monomacra bumeliae (Schaeffer, 1905) (528 individuals), Heterispa vinula (Erichson, 1847) (311 individuals), and Margaridisa sp. 1 (147 individ- uals), which together represent 77% (1,615 individuals) of the total abundance recorded. In addition, the community included 67 species with very low abundances, from which 25 (37%) correspond to singletons and nine to doubletons (13%). The dominance value (D) in the study area was 0.1998, which represents a true diversity (1/D) of 5.005. For the Shannon index (H’), a value of 2.221 was registered, with true diversity (e') of 9.217. Seasonal variation Seasonal differences in abundance of the leaf beetle community were statistically sig- nificant (Mann-Whitney U = 4039; p < 0.0001). The highest number of specimens was recorded during the rainy season (1,242 specimens, involving 41 genera), followed by the dry season (861, involving 30 genera). According to the permutation test, sig- nificant differences were also found in the number of species and diversity. Highest species richness was recorded in the rainy season. In contrast, the lowest dominance and highest diversity were obtained in the dry season (Table 1). Estimated species richness according to the non-parametrical estimators in the rainy season ranged between 85 and 100 species; therefore, the observed richness represents between 59.66 and 69.96% of completeness. For the dry season, the estimated richness varied from 48 to 56 species, indicating a completeness from 70.49 to 82.85% (Table 2). Inventory reliability with Clench’s model was higher during the dry season, with a completeness of 81% and a lower slope value, compared with the rainy season (Table 2). The best represented subfamily during the rainy season was Galerucinae (943 spec- imens, 32 species), followed by Cassidinae (260, 11 species). This same pattern was reflected in the dry season: Galerucinae with 685 specimens (21 species), followed by Cassidinae with 150 specimens (7 species). The remainder of the subfamilies had lower abundances and number of species for both seasons (Table 3). Faunistic similarity according to the Bray-Curtis index was 0.63%. A high proportion of the species composition shared between seasons involved Galerucinae, including Acrocyum dorsale Jacoby, 1885, C. diversa, Epitrix sp. 1, Margaridisa sp. 1, Table |. Diversity permutation test for species richness and alpha diversity of leaf beetles between seasons. Season Rainy Dry p Observed species richness 60 40 0.0132 Simpson index (D) 0.228 0.175 0.0001 Shannon index (H’) 2.062 2.232 0.0229 28 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Table 2. Chrysomelid estimated species richness and sampling completeness during the rainy and dry seasons. Estimator Rainy % of completeness Dry % of completeness Chao 1 97.53 61.52 55.11 72.58 Chao 2 90.44 66.34 56.74 70.49 Jack 1 85.76 69.96 55.88 75.64 Ace 100.56 59.66 48.28 82.85 Clench model (slope) 0.1561 — 0.077 - Clench model (estimated richness) 82 73 50 81 % was obtained on the basis of observed species richness. Table 3. Number of specimens and species registered by subfamily and season in the semideciduous tropical forest. Season Rainy Dry Subfamily Specimens Species Specimens Species Galerucinae 943 32 685 21 Cassidinae 260 11 150 7 Eumolpinae 25 7 11 5 Criocerinae 7 3 7 2 Chrysomelinae 5 5 4 3 Cryptocephalinae 2 2 4 2 and Monomacra bumeliae. The proportion was also high for Cassidinae, involving Brachycoryna pumila Guérin-Méneville, 1844, Helocassis crucipennis (Boheman, 1855), and Heterispa vinula (Erichson, 1847). Response of Chrysomelidae to seasonal microclimatic variation The OMI analysis for the rainy season indicated a significant deviation between the abiotic conditions used by the leaf beetles and the average total microclimatic conditions (Monte Carlo test, p = 0.047). Of the 60 species registered in this season, only six showed a significant association. Centralaphthona diversa and M. bumeliae obtained low marginality values, which represents a wider niche breadth, and they were thus considered to be generalist species (Table 4); abundance of these species was equally distributed in almost all samples (Fig. 2). The rest of the species presented high marginality and lower tolerance values, which indicates a smaller niche breadth, and they were therefore categorized as specialists. Labidomera suturella Guérin-Meéneville, 1838 was the species with the highest marginality and the lowest tolerance, followed by Walterianella sp. 1, Zenocolaspis inconstans (Lefevre, 1878) and Alagoasa trifasciata (Fabricius, 1801) (Table 4). The aforementioned species had lower abundance, 1-15 specimens, in a minor number of samples (Fig. 2). In the case of the dry season, marginality was significant (Monte Carlo test, p = 9.017) for only seven of the 40 registered species. Two were considered as generalists, with low marginality values; of these, B. pumila presented the highest tolerance, while Seasonal and microclimatic effects on leaf beetles Chrysomelidae 29 -0.30 Figure 2. Individual dispersion of leaf beetle species whose association for microclimatic variables was significant in the rainy season A Alagoasa trifasciata B Centralaphthona diversa C Labidomera suturella D Monomacra bumeliae E Walterianella sp. 1 F Zenocolaspis inconstans. At each species panel: the gray circles represent the presence of the species in the sample, and the size of the circle is proportional to its abundance; straight lines represent vectors and indicate the dispersion of the species from the aver- age position (centroid) towards each of the evaluation units where it was recorded; and ellipses repre- sent the concentration of 95% of the specimens of the species. G canonical correlation values (loadings) between microclimatic variables and the abundance of Chrysomelidae. Abbreviations: MW: Maximum wind speed, AW: average wind speed, Tem: temperature, RH: relative humidity, HI: heat index, DP: dew point, Ev: evapotranspiration. 30 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Table 4. Parameters of the Outlying Mean Index (OMI) for the significant species of Chrysomelidae (p < 0.05) from each season. Values for the non-significant species are presented in Appendix 1: Tables A2, A3. Key: InerO: Total Inertia, T1: Tolerance, T2: Residual tolerance, p: probability. Season Species InerO OMI T1 T2 p Rainy Alagoasa trifasciata (Fabricius, 1801) 5.199 2.521 0.9 1.778 0.0037 Rainy Centralaphthona diversa (Baly, 1877) 6.011 0.2003 2.14 3.671 0.0168 Rainy Labidomera suturella Guérin-Méneville, 1838 23.86 23.86 7.889E-31 — -7889-31 0.0409 Rainy Monomacra bumeliae (Schaeffer, 1905) 6.991 0.4444 1.699 4.894 0.0007 Rainy Walterianella sp. 1 7.257 Do 1.494 0.512 0.0193 Rainy Zenocolaspis inconstans (Lefevre, 1878) 6.561 4.146 0.233 2.182 0.0172 Dry Acallepitrix sp. 7 8.299 6.09 0.423 1.786 0.0169 Dry Alagoasa trifasciata (Fabricius, 1801) 7.092 6.523 0.038 0.530 0.0469 Dry Brachycoryna pumila Guérin-Méneville, 1838 9.761 2.114 5.087 2.56 0.0258 Dry Centralaphthona diversa (Horn, 1889) 8.056 0.2969 2.788 4.971 0.0415 Dry Chaetocnema sp. 1 10.03 6.778 1.714 1.539 0.0083 Dry Epitrix sp. 1 7.5 3.023 1.432 3.045 0.0073 Dry Syphrea sp. | 11.29 9.965 0.204 1.12 0.0106 C. diversa showed the lowest marginality (Table 4). Abundance of both species was uniformly distributed in almost all samples (Fig. 3). The other five chrysomelids had high marginality and low tolerance values (specialists): the highest marginality and lowest tolerance occurred in A. trifasciata, and it was consequently the species most specialized to microclimatic conditions during the dry season in the semideciduous tropical forest. In descending order, Syphrea sp. 1, Chaetocnema sp. 1, Acallepitrix sp. 7, and Epitrix sp. 1 (Table 4) were species recorded in few samples, with abundances between four and 18 specimens (Fig. 3). Heat index, evapotranspiration and temperature were the microclimatic variables most related with the abundance of leaf beetle species during the rainy season and were represented in Axis 1 of the OMI analysis (Eigenvalue = 4.9077, inertia = 55.74%). In Axis 2 (Eigenvalue = 2.6344, inertia = 29.92%) the most important variable was the average wind speed (Table 5). For the dry season, evapotranspiration, tempera- ture, and heat index in Axis 1 (Eigenvalue = 7.9982, inertia = 75.67%) were the mi- croclimatic variables most associated with the changes in abundance of leaf beetles. Maximum wind speed had the highest correlation in Axis 2 (Eigenvalue = 1.7084, inertia = 0.1616%) (Table 5). The association of the species with the environmental variables was determined based on the positions of the centroids and their closeness with respect to Axes 1 and 2. Those species that were located very close to the origin of both axes were considered to be related to average microclimatic values. For the rainy season, A. trifasciata and Z. inconstans, were related with low values of average wind speed (1.06—2.12 m/s), as well as high values of heat index (39.61—43.89 °C), evapotranspiration (27.24— 29.02 °C) and temperatures (30.47—35.42 °C). Walterianella sp. | presented a similar microclimatic pattern, with a positive correlation with Axis 1 (high values of heat index from 43.89 to 48.18 °C, evapotranspiration from 24.24 to 29.02 °C, and tem- perature from 32.94 to 35.42 °C), although it was associated with average to high Seasonal and microclimatic effects on leaf beetles Chrysomelidae el, -0.15 Figure 3. Individual dispersion of leaf beetle species whose association for microclimatic variables was significant in the dry season A Acallepitrix sp. 7 B Alagoasa trifasciata C Brachycoryna pumila D Cen- tralaphthona diversa E Chaetocnema sp. | F Epitrix sp. 1 G Syphrea sp. 1. At each species panel: tiny, black dots represent the sampling units; gray circles represent the presence of the species in the sample, and the size of the circle is proportional to its abundance; straight lines represent vectors and indicate the disper- sion of the species from the average position (centroid, pointed to by the red arrow) towards each of the sampling units where it was recorded; and ellipses represent the concentration of 95% of the specimens of the species. H canonical correlation values (loadings) between microclimatic variables and the abundance of Chrysomelidae. Abbreviations: MW: Maximum wind speed, AW: average wind speed, Tem: tempera- ture, RH: relative humidity, HI: heat index, DP: dew point, Ev: evapotranspiration. 32 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Table 5. Canonical correlation values (loadings) between the seven microclimatic variables and the abundance of chrysomelid species during both seasons. Significant values are marked (*). Rainy season Dry season Microclimatic variables Axis 1 Axis 2 Axis 1 Axis 2 Maximum wind speed (m/s) 0.075 0.299 -0.274 OF 71% Average wind speed (m/s) 0.136 0.301* -0.278 0.143 Temperature (°C) 0.345* 0.042 0.375* 0.192 Relative humidity (%) -0.084 -0.201 0.2481 -0.119 Heat Index (°C) 0.380* -0.040 0.371* 0.154 Dew Point (°C) 0.275 -0.173 0.368 -0.001 Evapotranspiration (°C) 0.345* -0.091 0.413* 0.035 values of wind speed (2.12—4.24 m/s). In the case of L. suturella, this species was located in areas with lower values of heat index (18.20—22.48 °C), evapotranspira- tion (16.60-18.37 °C), and temperature (18.10—20.57 °C), but higher wind speed (1.06—2.12 m/s). Lastly, C. diversa and M. bumeliae did not follow a specific pattern in relation to the significant variables in any axis since they were at the origin of the niche dispersion (Fig. 4). During the dry season, the average distribution of Syphrea sp. 1, Acallepitrix sp. 7, and Epitrix sp. 1 was correlated with areas of lower evapotranspiration (13—16.82 °C), temperature (16.30-19.69 °C) and heat index (16.60—22.20 °C) in Axis 1. Similarly on Axis 2, these species predominated under conditions of low to average maximum wind speed (1.42—2.84 m/s). Chaetocnema sp. | occurred in conditions of low evapo- transpiration (13-14.91 °C) and low temperature (21.39-—23.09 °C), as well as low heat index (19.40—22.20 °C), but this species was associated with high values of maxi- mum wind speed (1.42—2.13 m/s). Alagoasa trifasciata was the species with the low- est tolerance value; so, its centroid was positioned in areas with high evapotranspira- tion values (22.56—24.47 °C), high temperature (24.79—26.49 °C), high heat index (30.60—33.40 °C), and low maximum wind speed (0—0.71 m/s). Finally, the centroid of the distribution of B. pumila and C. diversa was significantly associated with average microclimatic conditions, since their distribution included areas with high and low values for the heat index, as well as for the other variables (Fig. 5). Discussion Faunistic inventory and chrysomelid biodiversity Prior to this study, 2,660 species of Chrysomelidae had been recorded from Mexico (Nifio-Maldonado and Sanchez-Reyes 2017) and 257 from the state of Tamaulipas (Nifio-Maldonado et al. 2014). Accordingly, results in the STF of the study area represent 2.7% of the leaf beetle biodiversity reported for the country, and 27.6% for the state. Our study revealed Diachus chlorizans (Suffrian, 1852) as a new country record for Mexico, and Diabrotica biannularis Harold, 1875 as a new state record for Seasonal and microclimatic effects on leaf beetles Chrysomelidae 33 Heat index (°C) Temperature (“C) Mm is2-224 | MM 18.1 - 20.5 Gl 22.4 - 26.7 HB 20.5 - 23.0 3267 -31.0 GB 23.0 - 25.5 (31.0 -35.3 * ime) (525.5 -27.9 135.3 - 39.6 . (27.9 - 30.4 39.6 - 43.8 GH 30.4-32.9 43.8 - 48.1 4, MM 32.9 - 35.4 48.1 -52.4 ——————— MH 35.4 -37.8 Maximum wind (m/s) - 18.3 0.00 - 1.06 3-20. GB 1.06 - 2.12 1-219 at MH 2.12 -3.18 9- 23.6 : 5 MM 3.18 - 4.24 6 - 25.4 4-272 2 - 29.0 0 - 30.7 Mi 4.24-5.31 MMB 5.31 - 6.37 Ml 6.37 - 7.43 MM 7.43 - 8.49 Axis 2. Eigenvalue: 2.6344. Inertia: 29.92% Axis 1. Eigenvalue: 4.9077. Inertia: 55.74% Figure 4. Environmental ranges of leaf beetles during the rainy season. Abbreviations: Labi sutu (Ladi- domera suturella), Centra dive (Centralaphthona diversa), Mono bume (Monomacra bumeliae), Walte sp. 1 (Walterianella sp. 1), Alag trif (Alagoasa trifasciata), Zeno inco (Zenocolaspis inconstans). Tamaulipas. These records were previously published in preliminary works from the study area (Lucio-Garcia et al. 2019). The number of taxa recorded in this research is lower compared to similar studies in northeastern Mexico, such as those conducted at El Cielo Biosphere Reserve (RBEC) (Nifio-Maldonado et al. 2005), the Cafidén de la Peregrina (CDP) (Sanchez-Reyes et al. 2014) and the Sierra de San Carlos (SDSC) (Sanchez-Reyes et al. 2016a). Nifio- Maldonado et al. (2005) reported 105 species in different elevational strata of STF. Lower values were found in two fragments of this vegetation in the Peregrina Canyon, where 85 (Sanchez-Reyes et al. 2014) and 37 species (Martinez-Sanchez 2016) were recorded. Other patches of STF were evaluated in the Cafién del Novillo (21 species) and Cerro El Diente (five species), also in Tamaulipas. The lower number in the pre- sent study can be attributed to the spatial scale and number of environments evaluated in these other investigations, which are greater compared to the STF of this work. For example, analyzing elevation gradients, different types of vegetation or biogeographic islands with extreme conservation status may result in the observed differences in fau- na. On basis of the aforementioned numbers, the chrysomelid richness for the current 34 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Evapotranspiration (°C) " et | | Temperature (°C) HE 13.00 - 14.91 HE 18.73 - 20.65 MM 24.47 - 26.38 a ME 16.30 - 17.99 7) 21.39 - 23.09 MM 26.49 - 28.19 HE 14.91 - 16.82 HE 20.65 - 22.56 MM 26.38 - 28.29 " HE 17.99 - 19.69 [I 23.09 - 24.79 MM 28.19 - 29.89 HM 16.82 - 18.73 MM 22.56 - 24.47 HS 19.69 - 21.39 BE 24.79 - 26.49 Heat index (°C) Maximum wind (m/s) HE 16.60 - 19.40 [J 25.00 - 27.80 33.40 - 36.20 (J0-0.71 Mll2.13-2.84 MMM 4.27 - 4.98 (19.40 - 22.20 EE 27.80 - 30.60 [_) 36.20 - 38.99 in 0.71 - 1.42 MM 2.84 - 3.56 Ml 4.98 - 5.69 (] 22.20 - 25.00 [El 30.60 - 33.40 “ Wl 142 - 2.13 MN 3.56 - 4.27 Axis 2. Egenvalue: 1.7084. Inertia: 0.16% Axis 1. Eigenvalue: 7.9982. Inertia: 75.67% Figure 5. Environmental ranges of leaf beetles during the dry season. Abbreviations: Chae sp. 1 (Chaetoc- nema sp. 1), Syph sp. 1 (Syphrea sp. 1), Acall sp. 7 (Acallepitrix sp. 7), Brach pumi (Brachycoryna pumila), Epit sp. 1 (Epitrix sp. 1), Centra dive (Centralaphthona diversa), Alag trif (Alagoasa trifasciata). research is above other STF fragments in northeastern Mexico, and it represents 68.2% of the most biodiverse site. Regarding true diversity, the numbers of equally dominant (1/D) and typical (e") species in this study were lower than those observed in Peregrina Canyon (Sanchez-Reyes et al. 2014), although they were higher than those observed in STF fragments from Canin del Novillo (Martinez-Sanchez 2016) or Cerro El Diente (Sanchez-Reyes et al. 2015b). Galerucine dominance as observed in our study has also been reported in other studies in northeastern Mexico (Nifio-Maldonado et al. 2005; Furth 2009; Furth 2013; Sanchez-Reyes et al. 2013; Sanchez-Reyes et al. 2014; Bouzan et al. 2015; Flinte et al. 2017; Lucio-Garcia et al. 2019, 2020), and this may be due to the subfamily’s high num- ber of species (Riley et al. 2002), with specimens found in all ecosystems during most parts of the year (Furth 2013; Sanchez-Reyes et al. 2013). In contrast, the subfamily com- position of this study is quite different from that in tropical forests. In the Chamela re- gion, on the Pacific side of Mexico, 49 species of Cassidinae were listed (Noguera 1988). As a whole, the aforementioned results highlight the great importance of the study area, since it was possible to find a large percentage of species within a smaller expanse when compared to larger space-temporal gradients or natural protected areas. This can be attributed to the geographic location of the studied STF within a region with a high conservation priority (CONABIO et al. 2007). The area, although adjacent to the Altas Cumbres Natural Protected Area, constitutes a mosaic with fragments of dif- ferent durations since last disturbance, and this may favor the presence of a complex Seasonal and microclimatic effects on leaf beetles Chrysomelidae 35 community of species (Sanchez-Reyes et al. 2017). Furthermore, the STF is one of the ecosystems with the highest biodiversity of plants (Rzedowski 2006; Garcia-Morales et al. 2014), and it is one of the most important in terms of chrysomelid species richness in Mexico (Noguera 1988; Burgos-Solorio and Anaya-Rosales 2004; Nifio-Maldonado et al. 2005; Lucio-Garcia et al. 2019). The combination of environmental factors in the STF results in a great diversification of plants, providing a wide range of food re- sources, which could lead to the high number of leaf beetles in this plant community in Tamaulipas and other states of Mexico. Seasonal variation On a temporal scale, the chrysomelid community followed a seasonal pattern, where the rainy season was the most favorable for the presence of this group in the study area. Increase in abundance and species richness during this season has also been found in numerous studies worldwide, including studies in Tamaulipas and other parts of Mex- ico (Petitpierre et al. 2000; Esker et al. 2002; Burgos-Solorio and Anaya-Rosales 2004; Koji and Nakamura 2006; Furth 2009; Martinez-Sanchez et al. 2009; Purth 2013; Sanchez-Reyes et al. 2015b; Sanchez-Reyes et al. 2016a; Sandoval-Becerra et al. 2016; Sen and G6ék 2016; Miwa and Meinke 2017; Lucio-Garcia et al. 2019). Results of the richness estimators support these patterns, because the percentage of completeness during rains is lower when compared to the dry season. Thus, in certain areas, the high- est activity of chrysomelids is restricted to the rainy season, while inactivity increases during drought conditions (Noguera 1988; Furth 2013). This is due to the association of chrysomelids with the quality and availability of their host plants (Rehounek 2002; Sen and Gék 2016), which are some of the most important elements in their diet (Avila and Postali-Parra 2003), as well as with the abundance of young foliage (Basset and Samuelson 1996), variables that are increased during the period of highest rainfall. In addition, there is more vegetation cover producing shade, creating microenviron- ments that could be more favorable to maintaining a high population density (Hill and Hill 2001), with the climatic conditions of humidity necessary for the adult beetles to emerge and fly (Yanes-Gémez and Morén 2010). However, in other geographic regions, such as the subtropical areas of Brazil, the highest abundance has occurred in the dry season, specifically within the subfami- lies Galerucinae, Cassidinae and Chrysomelinae (Linzmeier and Ribeiro-Costa 2008; Flinte et al. 2011; Bouzan et al. 2015; Flinte et al. 2017). In addition, in some areas of northeastern Mexico, greater numbers of species and specimens have also been re- corded during the dry season (Sanchez-Reyes et al. 2014). These discrepancies can be attributed to the climatic and biogeographic differences between plant communities. For example, in cloud forests, dry periods are shorter and less intense, causing a favora- ble increase in specimens of some Coleoptera families (Pedraza et al. 2010). Although soil moisture and precipitation are reduced in these areas, the cloudiness in the form of mist reduces evaporation, providing water during periods of low rain; in consequence, marked deficiency of humidity in these forests is rare. In other tropical forests near the 36 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) study area, the dry season is not as severe, for example in the Peregrina Canyon, where a higher abundance of adult chrysomelids often occurs concentrated in refuges dur- ing this season, while the larval stages are more abundant during the rains (Sanchez- Reyes et al. 2014). On the contrary, differences in geographic position, latitude and elevation influence the contrast that exists between the dry and rainy seasons in other fragments of the same type of vegetation in northeastern Mexico. In the study area, there are well-defined periods of high temperature and precipitation, in addition to a non-continuous flow of water currents during the year, which lead to a more severe dry season. Similar and more extreme cases exist in tropical dry forests from the south or Pacific coast of Mexico, where the plants lose their leaves completely during the dry season, resulting in a notable absence of chrysomelids (Noguera 1988). Likewise, these climatic variations and their effects on the phenology of the host plants are probably the main drivers of the temporal dynamics in these beetles (Flinte et al. 2017). Unlike other investigations where the greatest diversity also occurs in the wet sea- son (Sanchez-Reyes et al. 2016a), in this work, the low abundance and species rich- ness resulted in a high diversity in the dry season, by decreasing the dominance and increasing the effective number of species (Magurran 2004). Therefore, the dry season is of great importance for the chrysomelid community in the STF of the study area, since the prevailing conditions increase the evenness of the chrysomelid community. Species may exploit food resources in a more efficient way during this season, achiev- ing a balance in their populations and reducing the dominance of most species, thus suggesting an adaptation of Chrysomelidae to acute drought conditions. This could be noted also when observing the high percentage of faunistic similarity between seasons, which indicates that most of the leaf beetles are the same in both periods. Therefore, it is possible that their resource acquirement changes and consequently their abundances are modified during the seasonal variations. Moreover, 31 species were registered ex- clusively for the rainy season, while only 11 for the dry season. Together, these results highlight the relevance of areas where there is a marked temporal or seasonal heteroge- neity, since it can generate unique species compositions. Response of Chrysomelidae to seasonal microclimatic changes In this research, the niches of chrysomelid species were examined by means of the Outlying Mean Index. This showed that the variations in the abundance of leaf beetles were significantly related to the microclimatic changes in each season. Factors that influence the distribution of phytophagous insects are a combination of geographic and environmental elements (Wasowska 2004; Andrew and Hughes 2005; Lassau et al. 2005; Baselga and Jiménez-Valverde 2007). It has also been shown that leaf beetles present different degrees of association with the microclimatic conditions of the habi- tats where they develop (Sanchez-Reyes et al. 2016b; Sandoval-Becerra et al. 2017), and this is demonstrated in our study. However, the variation explained by the analysis and the correlation values of the variables were higher in the dry season, suggesting a stronger association between the microclimate and the chrysomelid community with Seasonal and microclimatic effects on leaf beetles Chrysomelidae af respect to the rainy season. This can be attributed to more heterogeneous environment values during low precipitation months. For example, in tropical forests it has been observed that lower microclimatic variability occurs through the rainy season (Checa et al. 2014; Sanchez-Reyes et al. 2019), which could be due to a higher homogeneity in the vegetation structure. Therefore, chrysomelid populations are more variable in rela- tion to the seasonal microclimate prevailing during the dry season, so that the effects, particularly of precipitation, determine strong positive or negative responses in these insects (Pinheiro et al. 2002); this pattern also occurs in other phytophagous groups, such as Curculionidae or Cicadidae (Novotny et al. 1999; Silva et al. 2017). Significant microclimatic variables were very similar between seasons (environ- mental temperature, heat index, evapotranspiration and, to a lesser extent, wind speed), although there were differences in the order of importance and in their contribution to the variations in abundance of leaf beetles. In the rainy season, the most important variable to characterize the niche of the species was the heat index, which is considered to be a combination of humidity and temperature in the same value and represents the thermal sensation (Lee and Brenner 2015). In physiological terms, phytophagous insects must accumulate a certain amount of heat to be able to hatch and accelerate their development rate, thereby increasing the number of generations (Marco 2001; Mejia 2005). However, in the dry season, the variable of greatest importance was evap- otranspiration. Such variation can be attributed to the environmental humidity stress to which the host plants are exposed after rainfall, modifying the moisture content of leaves and stems and thereby affecting feeding patterns of chrysomelids. This sug- gests that direct effects on trophic networks may occur during drought periods, which influence the development of phytophagous insects, particularly due to desiccation (Martinez et al. 2010; Anderson et al. 2016). A similar set of microclimatic variables has been associated with Chrysomelidae in other works, specifically temperature, heat index, maximum wind speed and evapo- transpiration (Stewart et al. 1996; Flinte and Valverde de Macedo 2004; Isard et al. 2004; Baselga and Jiménez-Valverde 2007; Linzmeier and Ribeiro-Costa 2013; Aneni et al. 2014; Sanchez-Reyes et al. 2016b; Oliveira et al. 2017; Sandoval-Becerra et al. 2017). There are other studies where the most important abiotic variables were solar ra- diation, precipitation, relative humidity, photoperiod and condensation point (Flinte and Valverde de Macedo 2004; Isard et al. 2004; Linzmeier and Ribeiro-Costa 2013). It should be mentioned that differences compared to the present study arise due to various factors, including the type of study, geographic location, ecosystems evaluated and method for measuring microclimatic variables, as well as the specific response of taxa to the variables. Regarding the individual response of leaf beetles to the variables, it was observed that only 11 of the 71 species registered a significant variation between their niche and the average microclimatic conditions in the STE It has been observed that the number of chrysomelid species that present a significant relationship with abiotic pa- rameters is variable, although previous studies have focused on the effect of disturbance (Sandoval-Becerra et al. 2017) and elevation gradients (Sanchez-Reyes et al. 2016b). 38 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) The study of chrysomelid species associated with abiotic variables has been useful in recognizing part of their biology and ecology, specifically their reproductive cycle or their potential for biological control (Stewart et al. 1996; Flinte and Valverde de Mac- edo 2004; Isard et al. 2004; Oliveira et al. 2017). Also, such study has been applied to know their niches (Sanchez-Reyes et al. 2015a) and to identify indicator species of conservation status (Ohsawa and Nagaike 2006) or disturbance (Sandoval-Becerra et al. 2017). Other studies have focused on the influence of climate in the distribution of species (Sanchez-Reyes et al. 2016b; Wang et al. 2017). The present work, on the other hand, is one of the first to address the influence of microclimatic variation on Chrysomelidae from a seasonal perspective. Specifically, in the dry season, seven significant species were recorded, while in the rainy season there were only six. In both seasons, C. diversa was categorized as a generalist species, since it presented a low marginality and a high tolerance, which indicates a wide distribution in the study area associated with average microclimatic values. This response is similar to that observed in the same and other species within the genus, but in different areas (Sanchez-Reyes et al. 2016b; Sandoval-Becerra et al. 2017). The second common species in both seasons was A. trifasciata although it was categorized as a specialist due to high marginality and low tolerance values. A similar response pattern was previously recorded in the Sierra de San Carlos for this species (Sanchez-Reyes 2014). Association between variables and A. trifasciata was higher in the dry season, since the marginality parameters were higher, while the tolerance values were lower; that is, the distribution of A. trifasciata appears to be more restricted dur- ing the dry conditions. ‘The rest of the species demonstrated seasonal differences. For example, during the rainy season, L. suturella presented the highest marginality value and had a low tolerance to the microclimatic environment; similar responses were observed in Walterianella sp. 1 and Z. inconstans. In the dry season, Syphrea sp. 1 was the species with the lowest tolerance, followed by Chaetocnema sp. 1, Acallepitrix sp. 7, Epitrix sp. 1 (Galerucinae), and B. pumila (Cassidinae). However, some of these spe- cies also occurred throughout the year, despite being significantly associated with only one season. The above observations provide evidence that leaf beetles have seasonal modifications in their niche requirements. Influence of the microclimate may be more important in the rainy season, while in the dry season (or vice versa) the variables that determine niches are different, or they may have a non-significant contribution to the distribution of the species (Basset et al. 1992; Martinez et al. 2010; Garcia-Atencia et al. 2015). These seasonal changes may be associated with the synchronization of the reproductive cycles of the phytophagous insects, particularly depending on the precipitation and temperature provided by the forest structure, which is not constant throughout the year and tends to be increasingly variable (Basset et al. 1992; Soler et al. 2002; Garcia-Atencia et al. 2015). The broad microclimatic tolerance of C. diversa and the abiotic specialization of A, trifasciata represent a first approach to the analysis of the generalized environmental response of chrysomelids, even though both have been documented in other studies. In this way, it is probable that the behavior of the species is similar and constant in other Seasonal and microclimatic effects on leaf beetles Chrysomelidae 39 geographical areas, which would allow the use of such taxa in environmental monitor- ing. New studies on chrysomelid niches would allow us to elucidate these effects. It is also important to recognize that phytophagous insects and specialist taxa with a small niche breadth could be negatively influenced by the possible effects of climate change (Williams et al. 2007; Dormann et al. 2008; Hill et al. 2011), which will impact the structure and functioning of the communities (Hegland et al. 2009; Stuble et al. 2013; Luna-Castellanos et al. 2017). Effects extend to plant-insect interactions (mutualism, predation, competition, etc.), either due to phenological changes (synchronization in the interaction) or distribution of species (Hédar et al. 2004; Luna-Castellanos et al. 2017), with some species even being susceptible to local extinction (Tscharntke et al. 2002; Petermann et al. 2010). Furthermore, the present results and similar evidence suggest that climate variability can lead to significant biodiversity losses (Parmesan et al. 1999; Hill et al. 2002; Konvicka et al. 2003; Wilson et al. 2007). However, despite having knowledge about possible consequences, little information is available on the effects that the changing microclimate can have on biodiversity, its populations, bio- logical communities, and the ecosystems that harbor them. Conclusions The study of seasonal and microclimatic changes on species and communities is a topic of great importance in conservation ecology. Community attributes of the fam- ily Chrysomelidae and the beetles’ response to microclimatic variation were evaluated for the first time from a seasonal perspective, in a semideciduous tropical forest frag- ment of northeastern Mexico. Overall, the observed results were similar to those from other faunistic studies of leaf beetles, although the number of species ranked third within tropical forest areas of the state of Tamaulipas. Seasonality induced significant changes in the parameters of abundance, diversity and faunistic composition in the chrysomelid community. The highest number of specimens and species were recorded in the rainy season, while the lowest dominance and highest diversity occurred in the driest period. In this study, it was shown that Chrysomelidae were significantly associated with the microclimatic variation among seasons. However, the strength of this association and the number of significant species were different for each season. Changes in the abundance of the leaf beetles were influenced by the heat index, temperature, evapotranspiration, and average wind speed, reflected by specific conditions required for each species. Microclimatic and seasonal assessment could be useful for the evaluation of climate change, since niche analysis enables detection of specialized or vulnerable species, which are associated with a delimited set of environmental conditions. This characterization of the microclimate niche of Chrysomelidae from a seasonal perspective was conducted here for the first time in northeastern Mexico. However, additional studies are warranted to determine if the observed patterns are different when evaluating other abiotic factors or when evaluating other plant communities. 40 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Acknowledgements Financial support for this study was granted by the Consejo Nacional de Ciencia y Tecnologia (CONACYT-Mexico) (Doctoral scholarship No. 401277), as well as by the Programa del Mejoramiento del Profesorado (PROMEP) of the Universidad Au- tonoma de Tamaulipas. Sugeidi San Juanita Siaz Torres provided field support, meas- uring microclimatic variables during the sampling period. Sergio A. Teran Juarez col- laborated in the photography and editing of chrysomelid images. We acknowledge support provided by the authorities from Ejido Santa Ana, Victoria, Tamaulipas, who authorized the fieldwork during the sampling period. References Anderson MC, Zolin CA, Sentelhas PC, Hain CR, Semmens K, Yilmaz MT} Gao FE, Otkin JA, Tetra R (2016) The evaporative stress index as an indicador of agricultural drought in Brazil: An assessment based on crop yield impacts. Remote Sensing of Environment 174: 82-99. http://dx.doi.org/10.1016/j.rse.2015.11.034 Andrew NR, Hughes L (2005) Diversity and assemblage structure of phytophagous Hemiptera along a latitudinal gradient: predicting the potential impacts of climate change. Global Ecol- ogy and Biogeography 14: 249-262. https://doi.org/10.1111/j.1466-822x.2005.00149.x Aneni TI, Aisagbonhi CI, Iloba BN, Adaigben VC, Ogbebor CO (2014) Influence of weath- er factors on seasonal population dynamics of Coelaenomenodera elaeidis (Coleoptera: Chrysomelidae) and its natural enemies in NIFOR, Nigeria. American Journal of Plant Sciences 5: 42-47. https://doi.org/10.4236/ajps.2014.51007 Avila CJ, Postali-Parra JR (2003) Leaf consumption by Diabrotica speciosa (Coleoptera: Chrysomelidae) adults on different host plants. Scientia Agricola 60: 789-792. https://doi. org/10.1590/s0103-90162003000400028 Baselga A, Jiménez-Valverde A (2007) Environmental and geographical determinants of beta diversity of leaf beetles (Coleoptera: Chrysomelidae) in the Iberian Peninsula. Ecological Entomology 32: 312-318. https://doi.org/10.1111/j.1365-2311.2007.00880.x Basset Y, Samuelson GA (1996) Ecological characteristics of an arboreal community of Chrysomelidae in Papua New Guinea. In: Jolivet PHA, Cox ML (Eds) Chrysomelidae Biology. Volume 2: Ecological Studies. SPB Academic Publishing. Netherlands, 243-262. Basset Y, Aberlenc HP, Delvare G (1992) Abundance and stratification of foliage arthropods in a lowland rain forest of Cameroon. Ecological Entomology 17: 310-318. https://doi. org/10.1111/j.1365-2311.1992.tb01063.x Bouzan MA, Flinte M, Valverde-Macedo M, Ferreira-Monteiro R (2015) Elevation and tempo- ral distributions of Chrysomelidae in southeast Brazil with emphasis on the Galerucinae. ZooKeys 547: 103-117. https://doi.org/10.3897/zookeys.547.9723 Brook WB, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends in Ecology and Evolution 23: 453-460. https://doi.org/10.1016/j. tree.2008.03.011 Seasonal and microclimatic effects on leaf beetles Chrysomelidae 4] Burgos-Solorio A, Anaya-Rosales S (2004) Los crisomelinos (Coleoptera: Chrysomelidae: Chrysomelinae) del estado de Morelos. Acta Zoolégica Mexicana 20: 39-66. https://doi. org/10.21829/azm.2004.2031581 Challenger A, Dirzo R (2009) Factores de cambio y estado de la biodiversidad. In: CONABIO (Ed.) Capital natural de México, vol. 2: Estado de conservacién y tendencias de cambio. CONABIO, Mexico, 37-73. Checa MF, Rodriguez J, Willmott KR, Liger B (2014) Microclimate variability signifi- cantly affects the composition, abundance, and phenology of butterfly communities in a highly threatened Neotropical dry forest. Florida Entomologist 97: 1-13. https://doi. org/10.1653/024.097.0101 Chen J, Saunders SC, Crow TR, Naiman RJ, Brosofske KD, Mroz GD, Brookshire BL, Franklin JF (1999) Microclimate in forest ecosystem and landscape ecology. BioScience 49: 288-297. https://doi.org/10.2307/1313612 Cloudsley-Thompson JL (1962) Microclimates and the distribution of terrestrial arthro- pods. Annual Review of Entomology 7: 199-222. https://doi.org/10.1146/annureyv. en.07.010162.001215 Colwell RK (2013) EstimateS: Statistical estimation of species richness and shared species from samples. Version 9.1.0. http://purl.oclc.org/estimates Comisién Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Comisién Nacional de Areas Naturales Protegidas y The Nature Conservancy, Programa México, Pronatura (2007) Sitios prioritarios terrestres para la conservacién de la biodiversidad. Currano ED, Wilf PR, Wing SL, Labandeira CC, Lovelock EC, Royer DL (2008) Sharply in- creased insect herbivory during the Paleocene-Eocene Thermal Maximum. Proceeding of the National Academy of Sciences of the United States of America 105: 1960-1964. https://doi.org/10.1073/pnas.0708646105 De-Lucia EH, Casteel CL, Nabity PD, O’Neill BF (2008) Insects take a bigger bite out of plants in a warmer, higher carbon dioxide world. Proceeding of the National Academy of Sciences of the United States of America 105: 1781-1782. https://doi.org/10.1073/pnas.07 12056105 Dolédec S, Chessel D, Gimaret-Carpentier C (2000) Niche separation in community analysis: a new method. Ecology 81: 2914-2927. https://doi.org/10.2307/177351 Dormann CE, Schweiger O, Arens P, Augenstein I, Aviron ST, Bailey D (2008) Prediction uncertainty of environmental change effects on temperate European biodiversity. Ecology Letters 11: 235-244. https://doi-org/10.1111/j.1461-0248.2007.01142.x Esker PD, Obrycki J, Nutter FW (2002) Temporal distribution of Chaetocnema pulicaria (Coleop- tera: Chrysomelidae) populations in Iowa. Journal of Economic Entomology 95: 739-747. https://doi.org/10.1603/0022-0493-95.4.739 ESRI (2014) ArcGIS Desktop: versién 10.2.2. Redlands, California. Environmental Systems Research Institute. Flinte V, Valverde de Macedo M (2004) Biology and seasonality of Fulcidax monstrosa (FE) (Chrysomelidae: Chlamisinae). The Coleopterists Bulletin 58: 457-465. https://doi. org/10.1649/629 Flinte V, De Freitas S, Valverde de Macedo M, Ferreida-Monteiro R (2011) Altitudinal and temporal distribution of Plagiometriona Spaeth, 1899 (Coleoptera, Chrysomelidae, 42 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Cassidinae) in a tropical forest in southeast Brazil. ZooKeys 157: 15-31. https://doi. org/10.3897/zookeys.157.1179 Flinte V, Abejanella A, Daccordi M, Ferreida RM, Valverde-de Macedo M (2017) Chrysomeli- nae species (Coleoptera, Chrysomelidae) and new biological data from Rio de Janeiro, Brazil. ZooKeys 720: 5—22. https://doi.org/10.3897/zookeys.720.13963 Flowers RW (1996) La subfamilia Eumolpinae (Coleoptera: Chrysomelidae) en América Cen- tra. Revista de Biologia Tropical, Publicacién especial 2: 1-60. Furth DG (2009) Flea beetle diversity of the Sierra Tarahumara, Copper Canyon, Mexico (Chrysomelidae: Alticinae). In: Jolivet P, Schmitt M, Santiago-Blay J (Eds) Research on Chrysomelidae Volume 2. Koninklijke Brill. Leiden, The Netherlands, 131-151. https://doi.org/10.1163/ej.9789004152045.1-299.46 Furth DG (2013) Diversity of Alticinae in Oaxaca, Mexico: a preliminary study (Coleoptera, Chrysomelidae). In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomeli- dae 4. ZooKeys, 1-32. https://doi.org/10.3897/zookeys.332.4790 Furth DG, Longino JT, Paniagua M (2003) Survey and quantitative assessment of flea beetle diversity in a Costa Rican rainforest (Coleoptera: Chrysomelidae: Alticinae). In: Furth DG (Ed.) Special topics in leaf beetle biology. Proceedings of the 5" International Sym- posium on the Chrysomelidae. Pensoft Publishers. Bulgaria, 1-23. https://agris.fao.org/ agris-search/search.do?recordID=US20 1300259237 Garcia-Atencia S, Martinez-Hernandez N, Pardo-Locarno LC (2015) Escarabajos fitéfagos (Coleoptera: Scarabaeidae) en un fragmento de bosque seco tropical del departamento del Atlantico, Colombia. Revista Mexicana de Biodiversidad 86: 754-763. https://doi. org/10.1016/j.rmb.2015.07.009 Garcia-Morales LJ, Estrada-Castill6n AE, Garcia-Jiménez J, Villarreal-Quintanilla JA, Cantu- Ayala C, Jurado-Ybarra E, Vargas-Vazquez VA (2014) Floristica y vegetacién del Area Nat- ural Protegida Altas Cumbres, Tamaulipas, México. In: Correa SA, Horta JV, Garcia-Jimé- nez J, Barrientos-Lozano L (Eds) Biodiversidad tamaulipeca Vol. 2. Instituto Tecnoldgico de Ciudad Victoria. Tamaulipas, Mexico, 15-73. Gobierno del Estado (2015) Decreto Gubernamental mediante el cual se aprueba el programa de manejo del Area Natural Protegida “Altas Cumbres”, localizada en los municipios de Jaumave y Victoria, Tamaulipas. Organo del Gobierno Constitucional del Estado Libre y Soberano de Tamaulipas. Periddico Oficial del Estado de Tamaulipas. Tomo CXL. Secre- taria General de Gobierno. Cd Victoria, Mexico, 2—75. Gotelli NJ, Colwell RK (2011) Chapter 4. Estimating species richness. In: Magurran AE, McGill BJ (Eds) Biological diversity: frontiers in measurement and assessment. Oxford University Press. New York, USA, 39-54. Hammer O, Harper DAT, Ryan PD (2017) PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4: 1-9. http://palaeo-electron- ica.org/2001_1/past/issuel_01.htm Hautier Y, Tilman D, Isbell EK Seabloom EW, Borer ET, Reich PB (2015) Anthropogenic en- vironmental changes affect ecosystem stability via biodiversity. Science 348: 336-340. https://doi.org/10.1126/science.aaal788 Seasonal and microclimatic effects on leaf beetles Chrysomelidae 43 Hegland SJ, Nielsen A, Lazaro A, Bjerknes AL, Totland O (2009) How does climate warming affect plant-pollinator interactions? Ecology Letters 12: 184—95. https://doi.org/10.1111/ j.1461-0248.2008.01269.x Hill J, Griffiths H, Thomas C (2011) Climate change and evolutionary adaptations at spe- cies range margins. Annual Review of Entomology 56: 143-149. https://doi.org/10.1146/ annurey-ento-120709-144746 Hill JK, Thomas CD, Fox R, Telfer MG, Willis SG, Asher J, Huntley B (2002) Responses of but- terflies to twentieth century climate warming: implications for future ranges. Proceedings of the Royal Society B-Biological Sciences 269: 2163-2171. https://doi.org/10.1098/rspb.2002.2134 Hill JL, Hill RA (2001) Why are tropical rain forests so species rich? Classifying, review- ing, and evaluating theories. Progress in Physical Geography 25: 326-354. https://doi. org/10.1191/030913301680193805 Hodar JA, Zamora R, Pefuelas J (2004) El efecto del cambio global en las interacciones planta- animal. In: Valladares F (Ed.) Ecologia del bosque mediterraneo en un mundo cambiante. Ministerio de Medio Ambiente, EGRAF S. A., Madrid, 248 pp. Tannacone J, Alvarifio L (2006) Diversidad de la artropofauna terrestre en la Reserva Nacional de Junin, Per. Ecologia Aplicada 5: 171-174. https://doi.org/10.21704/rea.v5il-2.332 Isard SA, Spencer JL, Mabry TR, Levine E (2004) Influence of atmospheric conditions on high-elevation flight of western corn rootworm (Coleoptera: Chrysomelidae). Environ- mental Entomology 33: 650-656. https://doi.org/10.1603/0046-225x-33.3.650 Jiménez-Valverde A, Hortal J (2003) Las curvas de acumulacion de especies y la necesidad de evaluar la calidad de los inventarios bioldgicos. Revista Ibérica de Aracnologia 8: 151-161. Jost L (2006) Entropy and diversity. Oikos 113: 363-375. https://doi.org/10.1111/ j-2006.0030-1299.14714.x Koji S, Nakamura K (2006) Seasonal fluctuation, age structure, and annual changes in a pop- ulation of Cassida rubiginosa (Coleoptera: Chrysomelidae) in a natural habitat. Annals of the Entomological Society of America 99: 292-299. https://doi.org/10.1603/0013- 8746(2006)099[0292:sfasaa]2.0.co;2 Konvicka M, Maradova M, Benes J, Fric Z, Kepka P (2003) Uphill shifts in distribution of butterflies in the Czech Republic: effects of changing climate detected on a regional scale. Global Ecology and Biogeography 12: 403-410. https://doi.org/10.1046/j.1466- 822x.2003.00053.x Lassau SA, Hochuli DE Cassis G, Reid CAM (2005) Effects of habitat complexity on forest beetle diversity: do functional groups respond consistently? Diversity and Distribution 11: 73-82. https://doi.org/10.1111/j.1366-9516.2005.00124.x Lee D, Brenner T (2015) Perceived temperature in the course of climate change: an analysis of global heat index from 1979 to 2013. Earth System Science Data 7(2): 193-202. https://doi.org/10.5194/essd-7-193-2015 Linzmeier AM, Ribeiro-Costa CS (2008) Seasonality and temporal structuration of Alticini community (Coleoptera, Chrysomelidae, Galerucinae) in the Araucaria Forest of Parana, Brazil. Revista Brasileira de Entomologia 52: 289-295. https://doi.org/10.1590/s0085- 56262008000200009 44 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Linzmeier AM, Ribeiro-Costa CS (2013) Seasonal pattern of Chrysomelidae (Coleoptera) in the state of Parana, southern Brazil. Biota Neotropica 13: 154-162. https://doi.org/10.1590/ s1676-06032013000100018 Lucio-Garcia JN, Nifio-Maldonado S, Coronado-Blanco JM, Horta-Vega JV, Reyes-Mufoz JL, Sanchez-Reyes UJ (2019) Diversidad de Chrysomelidae (Coleoptera) en un fragmento de bosque tropical subcaducifolio del noreste de México. Entomologia mexicana 6: 348-355. Lucio-Garcia JN, Sanchez-Reyes UJ, Horta-Vega JV, Coronado-Blanco JM, Reyes-Mufoz JL, Nifio-Maldonado S (2020) Especies de Galerucinae (Coleoptera: Chrysomelidae) asociadas a fragmentos de bosque tropical del estado de Tamaulipas. Entomologia Mexicana 7: 286-293. Luna-Castellanos F, Cuautle M, Feria-Arroyo TP, Castillo-Guevara C (2017) Effects of climatic change in the interaction plant-ant: a mini review on thermal tolerance. Mexican Journal of Biotechnology 2: 81-88. https://doi.org/10.29267/mxjb.2017.2.1.81 Magurran AE (2004) Measuring biological diversity. Blackwell Science Ltd. United Kingdom, 256 pp. Marco V (2001) Modelacion de la tasa de desarrollo de insectos en funcién de la temperatura. Aplicacién al manejo integrado de plagas mediante el método de grados-dias. Aracnet (Bol. S.E.A.) 7: 147-150. http://sea-entomologia.org/PDF/BOLETIN_28/B28-038-147.pdf Martinez N, Garcia S, Sanjuan S, Gutiérrez MJ, Contreras C (2010) Composicién y estructura de la fauna de escarabajos (Insecta: Coleoptera) atraidos por trampas de luz en La Reserva Ecoldogica de Luriza, Atlantico, Colombia. Boletin de la Sociedad Entomolégica Aragonesa 47: 373-381. https://dialnet.unirioja.es/servlet/articulo?codigo=37 18541 Martinez-Sanchez I (2016) Bioecologia de Chrysomelidae (Coleoptera) en los Cafones de la Libertad y el Novillo, Victoria, Tamaulipas. Phd Thesis, Universidad Auténoma de Tamaulipas, Instituto de Ecologia Aplicada, Mexico. Martinez-Sanchez I, Nifio-Maldonado S, Barrientos-Lozano L, Horta-Vega JV (2009) Dinami- ca poblacional de Chrysomelidae (Coleoptera) en un gradiente altitudinal en tres muni- cipios del estado de Hidalgo, México. Tecno INTELECTO 6: 1-4. Mejia M (2005) Calentamiento global y la distribucién de plagas. Boletin de la NAPPO (On- tario, Canada), 2 pp. Miwa K, Meinke LJ (2017) Seasonality of Colaspis crinicornis (Coleoptera: Chrysomelidae) and its injury potential to corn in southeastern Nebraska. Journal of Economic Entomology 111: 209-217. https://doi.org/10.1093/jee/tox325 Morrone JJ, Marquez J (2008) Biodiversity of Mexican terrestrial arthropods (Arachnida and Hexapoda): a biogeographical puzzle. Acta Zoolégica Mexicana 24: 15—41. https://doi. org/10.21829/azm.2008.241613 Murillo D, Ortega I, Carrillo JD, Pardo A, Rendon J (2012) Comparacién de métodos de interpolacién para la generacién de mapas de ruido en entornos urbanos. Ingenierias US- BMed 3: 62-68. https://doi.org/10.21500/20275846.265 Nifio-Maldonado S, Sanchez-Reyes UJ (2017) Taxonomia de insectos. Orden Coleoptera. Fa- milia Chrysomelidae. In: Cibrian-Tovar D (Ed.) Fundamentos de entomologia forestal. Red de salud forestal — Redes tematicas de la Comisién Nacional de Ciencia y Tecnologia (CONACYT), Mexico, 304—310. Seasonal and microclimatic effects on leaf beetles Chrysomelidae 45 Nifio-Maldonado S, Riley EG, Furth DG, Jones RW (2005) Coleoptera: Chrysomelidae: In: Sanchez-Ramos G, Reyes-Castillo P, Dirzo R (Eds) Historia natural de la Reserva de la Biés- fera El Cielo, Tamaulipas, México. Universidad Auténoma de Tamaulipas, Mexico, 417-422. Nifio-Maldonado S, Romero-Napoles J, Sanchez-Reyes UJ, Jones RW, Gonzalez-De-Leén EI (2014) Inventario preliminar de Chrysomelidae (Coleoptera) de Tamaulipas, México. In: Correa-Sandoval J, Horta-Vega V, Garcia-Jiménez J, Barrientos-Lozano L (Eds) Biodiversi- dad Tamaulipeca Vol. 2, No. 2. Tecnolégico Nacional de México, Instituto Tecnolégico de Ciudad Victoria, Mexico, 121—132. Noguera FA (1988) Hispinae y Cassidinae (Coleoptera: Chrysomelidae) de Chamela, Jalisco, México. Entomologia Mexicana 77: 277-311. Novotny V, Basset Y, Auga J, Boen W, Dal C, Drozd P, Kasbal M, Isua B, Kutil R, Manumbor M, Molem K (1999) Predation risk for herbivorous insects on tropical vegetation: a search for enemy-free space and time. Austral Ecology 24: 477-483. https://doi.org/10.1046/ j.1440-169x.1999.00987.x Ohsawa M, Nagaike T (2006) Influence of forest types and effects of forestry activities on species richness and composition of Chrysomelidae in the central mountainous region of Japan. Biodiversity and Conservation 15: 1179-1191. https://doi.org/10.1007/978-1- 4020-5208-8_8 Oliveira D, Freire-Zilch KC, Hintz FC, Kohler A (2017) Populational fluctuation and distribu- tion of Epitrix sp. Foudras (Coleoptera: Chrysomelidae) in the organic tobacco manage- ment in Santa Cruz do Sul, RS, Brazil. American Journal of Plant Sciences 8: 3285-3294. https://doi.org/10.4236/ajps.2017.812221 Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421: 37—42. https://doi.org/10.1038/nature0 1286 Parmesan C, Ryrholm N, Stefanescu C, Hill JK, Thomas CD, Descimon H, Huntley B (1999) Poleward shifts in geographical ranges of butterfly species associated with regional warm- ing. Nature 399: 579-583. https://doi.org/10.1038/21181 Pedraza M, Marquez J, Gémez-Anaya JA (2010) Estructura y composicién de los ensambles es- tacionales de coledpteros (Insecta: Coleoptera) del bosque mesdfilo de montafa en Tlanchi- nol, Hidalgo, México, recolectados con trampas de intercepcién de vuelo. Revista Mexica- na de Biodiversidad 81: 437-456. https://doi.org/10.22201/ib.20078706e.2010.002.234 Petermann JS, Muller CB, Weigelt A, Weisser WW, Schmid B (2010) Effect of plant spe- cies loss on aphid parasitoid communities. Journal of Animal Ecology 79: 709-720. https://doi.org/10.1111/j.1365-2656.2010.01674.x Petitpierre E, Bastazo G, Blasco-Zumeta J (2000) Crisomélidos (Coleoptera: Chrysomelidae) de un sabinar de Juniperus thurifera L. en los Monegros (Zaragoza, NE, Espafia). Sociedad Entomoldgica Aragonesa 27: 53-61. Pimm SL (2007) Biodiversity: climate change or habitat loss — which will kill more species? Current Biology 18: 117-119. https://doi.org/10.1016/j.cub.2007.11.055 Pinheiro F, Diniz I, Coelho RD, Bandeira MPS (2002) Seasonal pattern of insect abundance in the Brazilian cerrado. Austral Ecology 27: 132-136. https://doi.org/10.1046/j.1442- 9993.2002.01165.x 46 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Régniére J (2009) Prediccién de la distribucién continental de insectos a partir de la fisiologia de las especies. Unasylva 60: 37-42. http://www.fao.org/3/i0670s/i0670s09. pdf Rehounek J (2002) Comparative study of the leaf beetles (Coleoptera: Chrysomelidae) in cho- sen localities in the district of Nymburk. Acta Universitatis. Palackianae Olomucensis Fac- ultas Rerum Natturalium Biologica 40: 123-130. Riley EG, Clark SM, Flowers RW, Gilbert AJ (2002) Chrysomelidae Latreille 1802. In: Arnett RH, Thomas MC, Skelley PE, Frank JH (Eds) American Beetles. Polyphaga: Scarabaeoidea through Curculionoidea. Vol 2. CRC Press LLC. Boca Raton, FL, 617-691. Root TL, Price JT, Hall KR, Schneider SH, Rosenzweing C, Pounds AJ (2003) Fingerprints of global warming on wild animals and plants. Nature 421: 57—60. https://doi.org/10.1038/ nature01333 Rzedowski J (2006) Vegetacién de México. 1 ra. Edicién digital. Comisién Nacional para el Con- ocimiento y Uso de la Biodiversidad, Mexico, 504 pp. https://doi.org/10.2307/1219727 Sanchez-Reyes UJ (2014) Analisis y distribucién de Chrysomelidae (Coleoptera) en la Sierra de San Carlos, Tamaulipas. MS ‘Thesis, Instituto Tecnolégico de Cd. Victoria. Tamaulipas, Mexico, 31(1): 10-22. https://doi.org/10.21829/azm.2015.311499 Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Banda-Hernandez JE, Medina- Puente A (2013) Galerucinae (Coleoptera: Chrysomelidae) del Cafon de la Peregrina, Victoria, Tamaulipas, México. Entomologia Mexicana 12: 1517-1522. Sanchez-Reyes UJ, Nifio-Maldonado S, Jones RW (2014) Diversity and altitudinal distribu- tion of Chrysomelidae (Coleoptera) in Peregrina Canyon, Tamaulipas, Mexico. ZooKeys 417: 103-132. https://doi.org/10.3897/zookeys.417.7551 Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Jones RW, Sandoval-Becerra FM (2015a) Analisis del nicho ecoldgico de Cryptocephalinae (Coleoptera: Chrysomelidae) en la Sierra de San Carlos, Tamaulipas, México. Entomologia Mexicana 2: 526-532. Sanchez-Reyes UJ, Nifto-Maldonado S, Meléndez-Jaramillo E, Gémez-Moreno VC, Banda- Hernandez JE (2015b) Riqueza de Chrysomelidae (Coleoptera) en el Cerro el Diente, San Carlos, Tamaulipas, México. Acta Zoolégica Mexicana 31: 10-22. https://doi. org/10.21829/azm.2015.311499 Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Clark SM, Jones RW (2016a) Faunistic patterns of leaf beetles (Coleoptera, Chrysomelidae) within elevational and temporal gradients in Sierra de San Carlos, Mexico. ZooKeys 611: 11-56. https://doi. org/10.3897/zookeys.611.9608 Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Sandoval-Becerra FM (2016b) Influencia del clima en la distribucién de Chrysomelidae (Coleoptera) en el Cafién de la Peregrina, Tamaulipas, México. Entomologia Mexicana 3: 467-473. Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Trevifio-Carreén J (2017) Assess- ment of land use-cover changes and successional stages of vegetation in the Natural Pro- tected Area Altas Cumbres, Northeastern Mexico, using Landsat satellite imagery. Remote Sensing 9: 1-33. https://doi.org/10.3390/rs90707 12 Sanchez-Reyes UJ, Nifio-Maldonado S, Barrientos-Lozano L, Clark SM, Trevifio-Carreén J, Almaguer-Sierra P (2019) Microclimate niche requirements ofleaf beetles (Chrysomelidae: Coleoptera) inasuccessional gradient oflow thorn forest innortheastern Mexico. Journal of Insect Conservation 23: 503-524. https://doi.org/10.1007/s10841-019-00140-2 Seasonal and microclimatic effects on leaf beetles Chrysomelidae 47 Sandoval-Becerra FM, Sanchez-Reyes UJ, Nifio-Maldonado S, Horta-Vega JV (2016) Patrones de actividad de Cassidinae Gyllenhal, 1813 (Coleoptera: Chrysomelidae) en el sendero interpretativo El Tepalo, Chapala, Jalisco. Entomologia mexicana 3: 488-494. Sandoval-Becerra FM, Nifio-Maldonado S, Sanchez-Reyes UJ, HortaVega JV, Venegas-Barrera CS, Martinez-Sanchez I (2017) Respuesta de la comunidad de Chrysomelidae (Coleop- tera) a la variacidn microclimatica en un fragmento de bosque de encino del noreste de México. Entomologia Mexicana 4: 421-427. Santiago-Blay JA (1994) Paleontology of leaf beetles: In: Jolivet PH, Cox ML, Petitpierre E (Eds) Novel aspects of the biology of Chrysomelidae. Kluwer Academic Publishers, Dordrecht, 1-68. https://doi.org/10.1007/978-94-011-1781-4_1 Schaefer HC, Jetz W, Bohning-Gaese K (2008) Impact of climate change on migratory birds: community reassembly versus adaptation. Global Ecology and Biogeography 17: 38-49. https://doi.org/10.1111/j.1466-8238.2007.00341.x Scherer G (1983) Diagnostic key for the Neotropical Alticinae genera. Entomologische Arbe- iten aus dem Museum G. Frey 31/32: 2-89. Sen I, Gék A (2016) Seasonal activity of adult leaf beetles (Coleoptera: Chrysomelidae, Or- sodacnidae) occurring in Kovada Lake and Kizilda’g National Parks in Isparta Province (Turkey). Biologia 71: 593-603. https://doi.org/10.1515/biolog-2016-0062 Silva JO, Leal CRO, Espirito-Santo MM, Morais HC (2017) Seasonal anddiel variations inthe- activity ofcanopy insect herbivores differ betweendeciduous andevergreen plant species in- atropical dry forest. Journal of Insect Conservation 21: 667—676. https://doi.org/10.1007/ s10841-017-0009-9 Soler JM, Garcia-Mari F, Alonso D (2002) Evolucién estacional de la entomofauna auxiliar en citricos. Boletin Sanidad Vegetal Plagas 28: 133-149. https://doi.org/10.4995/the- sis/10251/5952 Staines C (2002) The New World tribes and genera of hispines (Coleoptera: Chrysomelidae: Cassidinae). Proceedings of the Entomological Society of Washington 104: 721-784. StatSoft Inc (2007) STATISTICA: data analysis software system, version 8.0. www.statsoft.com Stewart CA, Emberson RM, Syrett P (1996) Temperature effects on the alligator weed flea-bee- tle Agasicles hygrophila (Coleoptera: Chrysomelidae): implications for biological control in New Zealand. In: Moran VC, Hoffman JH (Eds) Proceedings of the IX International Sym- posium on Biological Control of Weeds. University of Cape Town. South Africa, 393-398. Stuble KL, Pelini SL, Diamond SE, Fowler DA, Dunn RR, Sanders NJ (2013) Foraging by forest ants under experimental climatic warming: a test at two sites. Ecology and Evolution 3: 482-491. https://doi.org/10.1002/ece3.473 Thioulouse J, Chessel D, Dolédec S, Olivier JM (1997) ADE-4: a multivariate analysis and graph- ical display software. Stat Comput 7: 75-83. https://doi.org/10.1023/A:1018513530268 Triplehorn CA, Johnson NF (2005) Borror and DeLong’s Introduction to the Study of Insects. Seventh Edition. Thomson Brooks/Cole, Learning Inc. United States of America, 864 pp. Tscharntke T, Steffan-Dewenter I, Kruess A, Thies TC (2002) Characteristics of insect popula- tions on habitat fragments: a mini review. Ecological Research 17: 229-239. https://doi. org/10.1046/j.1440-1703.2002.00482.x Uribe-Botero E (2015) El cambio climatico y sus efectos en la biodiversidad en América Latina. Comisién Economica para América Latina y el Caribe, Naciones Unidas. Santiago, 84 pp. 48 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Vié JC, Hilton-Taylor C, Stuart SN (2009) Wildlife in a changing world — an analysis of the 2008 IUCN Red List of threatened species. Ingoprint. Barcelona, Espafa, 180 pp. https://doi.org/10.2305/IUCN.CH.2009.17.en Wang C, Hawthorne D, Qin Y, Pan X, Li Z, Zhu S (2017) Impact of climate and host availability on future distribution of Colorado potato beetle. Scientific Reports 7: 1-9. https://doi.org/10.1038/s41598-017-04607-7 Wasowska M (2004) Impact of humidity and mowing on chrysomelid communities (Coleop- tera, Chrysomelidae) in meadows of the Wierzbanéwka valley Pogdérze Wielickie hills, Southern Poland. Biologia Bratislava 59: 601-611. White RE (1993) A revision of the subfamily Criocerinae (Chrysomelidae) of North America north of Mexico. United States Department of Agriculture, Agricultural Research Service. Technical Bulletin 1805, 158 pp. Wilcox JA (1972) A review of the North American Chrysomelinae leaf beetles (Coleoptera: Chrysomelidae). University of the State of New York. State Education Department. State Museum and Science Service. Bulletin 421, 37 pp. Williams PH, Araujo MB, Rasmont P (2007) Can vulnerability among British bumblebee (Bombus) species be explained by niche position and breadth? Biological Conservation 138: 493-505. https://doi.org/10.1016/j.biocon.2007.06.001 Wilson RJ, Gutiérrez D, Gutiérrez J, Monserrat VJ (2007) An elevational shift in butterfly species richness and composition accompanying recent climate change. Global Change Biology 13: 1873-1887. https://doi.org/10.1111/j.1365-2486.2007.01418.x Wolda H (1988) Insect seasonality: Why? Annual Review of Ecology and Systematics 19: 1-18. https://doi.org/10.1146/annurev.es.19.110188.000245 Yanes-Gomez G, Morén MA (2010) Fauna de coledpteros Scarabaeoidea de Santo Domingo Huehuetlan, Puebla, México. Su potencial como indicadores ecolégicos. Acta Zoolégica Mexicana 26: 123-145. https://doi.org/10.21829/azm.2010.261683 Appendix | Table Al. Taxonomic checklist of Chrysomelidae by season in a fragment of semideciduous tropical for- est from northeastern Mexico (March 2016 to February 2017). Taxon Rainy season Dry season N N N CRIOCERINAE Latreille, 1807 14 Tribe Lemini Heinze, 1962 Lema sp. 1 5 = D Lema sp. 2 2 2 - Lema sp. 3 2 - 2 Neolema sp. 1 2 2 = Oulema sp. 1 3 3 = CASSIDINAE Gyllenhal, 1813 410 Tribe Chalepini Weise, 1910 Baliosus sp. 1 1 1 = Brachycoryna pumila Guérin-Meéneville, 1844 34 17 17 Seasonal and microclimatic effects on leaf beetles Chrysomelidae 49 Taxon Rainy season Dry season N N N Chalepus digressus Baly, 1885 1 _ 1 Heterispa vinula (Erichson, 1847) 311 209 102 Octotoma intermedia Staines, 1989 3 3 - Sumitrosis inaequalis (Weber, 1801) 2 2 — Tribe Cassidini Gyllenhal, 1813 Agroiconota vilis (Boheman, 1855) 1 1 = Charidotella sexpunctata (Fabricius, 1781) 3 2 1 Helocassis clavata (Fabricius, 1798) 12 7 Helocassis crucipennis (Boheman, 1855) 37 16 21 Microctenochira punicea (Boheman, 1855) 4 3 1 Microctenochira varicornis (Spaeth, 1926) 1 1 = CHRYSOMELINAE Latreille, 1802 9 Tribe Chrysomelini Latreille, 1802 Calligrapha ancoralis Stal, 1860 1 1 - Calligrapha fulvipes Stal, 1859 1 ~ i Deuterocampta atromaculata Stal, 1859 1 1 Labidomera suturella Chevrolat, 1844 3 1 2 Plagiodera semivittata Stal, 1860 2 1 1 Plagiodera thymaloides Stal, 1860 1 1 - GALERUCINAE Latreille, 1802 1628 Tribe Galerucini Latreille, 1802 Coraia subcyanescens (Schaeffer, 1906) 8 8 _ Tribe Luperini Chapuis, 1875 Acalymma sp. 1 1 1 - Cyclotrypema furcata (Olivier, 1808) 23 23 = Diabrotica biannularis Harold, 1875 1 1 = Gynandrobrotica lepida (Say, 1835) 8 1 WA Paratriarius curtisii (Baly, 1886) 1 1 s Tribe Alticini Newman, 1835 Acallepitrix sp. 1 1 - 1 Acallepitrix sp. 2 1 1 Acallepitrix sp. 3 2 2 - Acallepitrix sp. 4 i) - 3 Acallepitrix sp. 5 11 5 6 Acallepitrix sp. 6 9 2 7 Acallepitrix sp. 7 8 4 4 Acallepitrix sp. 8 2 2 - Acrocyum dorsale Jacoby, 1885 30 17 13 Acrocyum sp. 1 2 - 2 Alagoasa bipunctata (Chevrolat, 1834) 8 5 3 Alagoasa trifasciata (Fabricius, 1801) 19 15 4 Alagoasa sp. 1 1 1 - Asphaera abdominalis (Chevrolat, 1835) 1 1 = Asphaera nigrofasciata Jacoby, 1885 1 1 ~ Centralaphthona diversa (Baly, 1877) 692 440 252 Centralaphthona sp. 1 1 1 - Chaetocnema sp. 1 19 6 13 Disonycha stenosticha Schaefer, 1931 1 - 1 Epitrix sp. 1 28 10 18 Heikertingerella sp. 1 24 21 3 Longitarsus sp. 1 7 4 3 Longitarsus sp. 2 16 1 15 Margaridisa sp. 1 147 16 131 Monomacra bumeliae (Schaeffer, 1905) 528 336 192 Phyllotreta aeneicollis (Crotch, 1873) 1 1 ps Syphrea sp. 1 8 2 6 50 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) Taxon Rainy season Dry season N N N Syphrea sp. 2 2 5 - Walterianella sp. 1 9 8 1 Walterianella sp. 2 1 1 - CRYPTOCEPHALINAE Gyllenhal, 1813 6 Tribe Cryptocephalini Gyllenhal, 1813 Cryptocephalus umbonatus Schaeffer, 1906 1 - 1 Diachus chlorizans (Suffrian, 1852) 1 1 = Tribe Clytrini Lacordaire, 1848 Babia distinguenda Jacoby, 1889 1 1 = Smaragdina agilis (Lacordaire, 1848) 3 - 3 EUMOLPINAE Hope, 1840 36 Tribe Eumolpini Hope, 1840 Brachypnoea sp. 1 3 1 2 Brachypnoea sp. 2 5 1 4 Colaspis freyi (Bechyné, 1950) 1 1 = Colaspis melancholica Jacoby, 1881 13 12 1 Colaspis townsendi Bowditch, 1921 1 1 - Xanthonia sp. 1 3 = 3 Zenocolaspis inconstans (Lefevre, 1878) 8 7 1 Tribe Typophorini Chapuis, 1874 Paria sp. 1 2 2 - 71 species Totals 2103 1242 861 Table A2. Outlying Mean Index parameters for chrysomelid species in the rainy season. Key: InerO = Total inertia, OMI = Marginality index, T1 = Tolerance, T2 = Residual tolerance, p = probability; signifi- cant values in bold. Species InerO OMI Tl T2 P Acallepitrix sp. 2 3.76 3.76 0.00 0.00 0.55 Acallepitrix sp. 3 11.91 5.64 3.86 2.42 0.16 Acallepitrix sp. 5 5.74 2.92 0.82 2.00 0.09 Acallepitrix sp. 6 11.66 7.62 2.35 1.69 0.08 Acallepitrix sp. 7 3.88 0.23 0.99 2.67 0.96 Acallepitrix sp. 8 3.72 3.03 0.10 0.59 0.42 Acalymma sp. 1 4.56 4.56 0.00 0.00 0.47 Acrocyum dorsale 6.33 0.54 2.01 3.78 0.24 Agroiconota vilis 1.51 1.51 0.00 0.00 0.91 Alagoasa bipunctata 3.45 0.85 0.97 1.63 0.70 Alagoasa trifasciata 5.20 252 0.90 1.78 0.00 Alagoasa sp. 1 2.29 2.29 0.00 0.00 0.78 Asphaera abdominalis 2.29 2.29 0.00 0.00 0.78 Asphaera nigrofasciata 5.57 Spey 0.00 0.00 0.40 Babia distinguenda 9.82 9.82 0.00 0.00 0.23 Brachycoryna pumila 5.14 0.95 2.58 1.62 0.25 Brachypnoea sp. 1 5.83 5.83 0.00 0.00 0.37 Brachypnoea sp. 2 0.75 0.75 0.00 0.00 0.97 Calligrapha fulvipes 3.05 3.05 0.00 0.00 0.65 Centralaphthona diversa 6.01 0.20 2.14 3.67 0.02 Centralaphthona sp. 1 0.94 0.94 0.00 0.00 0.96 Chaetocnema sp. 1 5.46 1.58 0.81 3.08 0.43 Charidotella sexpunctata 2.52 LaF 0.62 0.63 0.79 Colaspis freyi 4.30 4.30 0.00 0.00 0.49 Colaspis melancholica 7.96 7.96 0.00 0.00 0.31 Colaspis townsendi 3.33 1.00 0.24 2.08 0.40 Seasonal and microclimatic effects on leaf beetles Chrysomelidae 51 Species InerO OMI Tl T2 P Coraia subcyanescens 4.61 0.57 0.42 3.62 0.78 Cyclotrypema furcata 3.25 0.37 0.70 2.18 0.58 Diabrotica biannularis 222 222 0.00 0.00 0.81 Diachus chlorizans 0.59 0.59 0.00 0.00 0.98 Deuterocampta atromaculata 3.05 3.05 0.00 0.00 0.65 Epitrix sp. 1 4.62 3.55 0.37 0.70 0.07 Gynandrobrotica lepida 20.23 20.23 0.00 0.00 0.06 Heikertingerella sp. 1 6.29 0.11 1.29 4.89 0.96 Helocassis clavata 9.99 1.93 6.06 2.00 0.22 Helocassis crucipennis 5.12 1.61 0.46 3.05 0.09 Heterispa vinula 6.06 0.09 1.30 4.68 0.21 Labidomera suturella 23.86 23.86 1.83 0.00 0.04 Lema sp. 2 6.01 4.36 0.80 0.85 0.26 Longitarsus sp. 1 17.20 5.69 10.66 0.85 0.07 Longitarsus sp. 2 2.53 2.53 0.00 0.00 0.75 Margaridisa sp. 1 5.40 0.16 2.07 3.17 0.86 Microctenochira punicea 2.59 1.41 0.38 0.80 0.59 Microctenochira varicornis 9.80 9.80 0.00 0.00 0.23 Monomacra bumeliae 6.99 0.44 1.70 4.85 0.00 Neolema sp. 1 5.55 5.45 0.00 0.10 0.18 Octotoma sp. 1 4.60 1.23 1.88 1.50 0.66 Oulema sp. 1 3.75 2.72 0.08 0.94 0.49 Paratriarius curtisii 2.62 2.62 0.00 0.00 0.71 Paria sp. 1 8.16 2532 3.98 1.86 0.56 Phyllotreta aeneicollis 6.34 6.34 0.00 0.00 0.35 Plagiodera semivittata 4.00 4.00 0.00 0.00 0.53 Plagiodera thymaloides 3.15 3.15 0.00 0.00 0.65 Sumitrosis inaequalis 3.17 0.35 0.64 2.18 0.97 Sumitrosis sp. 1 1.24 1.24 0.00 0.00 0.94 Syphrea sp. 1 1.70 0.60 0.01 1.08 0.92 Syphrea sp. 2 3.41 3.20 0.04 0.16 0.44 Walterianella sp. 1 7.26 5.25 1.49 0.51 0.02 Walterianella sp. 2 2.62 2.62 0.00 0.00 0.71 Zenocolaspis inconstans 6.56 4.15 0.23 2.18 0.02 Table A3. Outlying Mean Index parameters for chrysomelid species in the dry season. Key: InerO = To- tal inertia, OMI = Marginality index, T1 = Tolerance, T2 = Residual tolerance, p = probability; significant values in bold. Species InerO OMI Tl T2 P Acallepitrix sp. 1 7.86 7.86 0.00 0.00 0.41 Acallepitrix sp. 4 5.76 2.15 0.23 3.38 0.41 Acallepitrix sp. 5 5.63 0.90 3.16 1.58 0.45 Acallepitrix sp. 6 6.31 0.46 2.41 3.43 0.80 Acallepitrix sp. 7 8.30 6.09 0.42 1.79 0.02 Acrocyum dorsale 8.21 0.25 3.58 4.38 0.72 Acrocyum sp. 1 14.37 7.55 4,42 2.40 0.10 Alagoasa trifasciata 7.09 6.52 0.04 0.53 0.05 Alagoasa sp. 1 4.47 1.72 0.68 2.07 0.52 Brachycoryna pumila 9.76 2.11 5.09 2.56 0.03 Brachypnoea sp. 1 9.51 0.65 4.61 4.25 0.95 Brachypnoea sp. 2 12.33 12.33 0.00 0.00 0.10 Calligrapha fulvipes 5.45 5.45 0.00 0.00 0.56 Centralaphthona diversa 8.06 0.30 2.79 4.97 0.04 Chaetocnema sp. 1 10.03 6.78 1.71 1.54 0.01 52 Species Chalepus digressus Charidotella sexpunctata Colaspis townsendi Cryptocephalus umbonatus Disonycha stenosticha Epitrix sp. 1 Gynandrobrotica lepida Heikertingerella sp. 1 Helocassis clavata Helocassis crucipennis Heterispa vinula Labidomera suturella Lema sp. 1 Lema sp. 3 Longitarsus sp. 1 Longitarsus sp. 2 Margaridisa sp. 1 Microctenochira punicea Monomacra bumeliae Plagiodera thymaloides Smaragdina agilis Syphrea sp. 1 Walterianella sp. 1 Xanthonia sp. 1 Zenocolaspis inconstans InerO 12.80 9.42 5.85 0.83 8.31 7.50 4.94 5.75 6.28 8.65 7.04 3.43 8.29 2.29 5.51 5.79 7.69 2.93 6.20 5.72 5.31 11.29 5.72 4.60 4,25, OMI 12.80 9.42 5.85 0.83 8.31 3.02 1.29 0.88 0.57 1.95 0.23 1.30 1.54 2.29 2.46 0.13 0.13 2.93 0.16 5.72 0.53 9.97 5.72 2.42 4.25 Tl 0.00 0.00 0.00 0.00 0.00 1.43 0.25 2.31 4.26 5.37 1.79 0.78 4.25 0.00 0.09 0.20 3.27 0.00 2.86 0.00 1.71 0.20 0.00 0.23 0.00 José Norberto Lucio-Garcia et al. / ZooKeys 1080: 21-52 (2022) T2 0.00 0.00 0.00 0.00 0.00 3.05 3.41 2.57 1.45 1.33 5.02 1.34 2.50 0.00 2.96 5.47 4,29 0.00 3.18 0.00 3.07 1.12 0.00 1.95 0.00