Can Dung Beetles (Scarabaeinae) Indicate the Status of Amazonia’S Ecosystems? Insights Integrating Anthropogenic Disturbance with Seasonal Patterns
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Animal Biology 67 (2017) 301–318 brill.com/ab Can dung beetles (Scarabaeinae) indicate the status of Amazonia’s ecosystems? Insights integrating anthropogenic disturbance with seasonal patterns Reinaldo L. Cajaiba1,3,4,∗, Eduardo Périco1, Wully B. da Silva2 and Mário Santos3 1 Laboratory of Ecology and Evolution, University of Taquari Valley, R. AvelinoTallini, 95900-000 Lajeado, RS, Brazil 2 Federal University of Pará, R. Cel. José Porfírio 2515, 68371-040 Altamira, PA, Brazil 3 Laboratory of Applied Ecology, CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, 5000-911 Vila Real, Portugal 4 Federal Institute of Education, Science and Technology of Maranhão, R. Dep. Gastão Vieira 1000, 65393-000, Buriticupu, MA, Brazil Submitted: May 28, 2017. Final revision received: October 12, 2017. Accepted: November 3, 2017 Abstract Temporal and spatial variation in dung beetles abundances is a pattern observed in many tropical forests. The present study evaluated the seasonal patterns of dung beetles in a range of increasingly disturbed ecosystems of the state of Pará, northern Brazil, to identify valuable disturbance indicators. The areas included native forest, agriculture, pasture for extensive livestock grazing and secondary forests. Fieldwork was carried out encompassing the complete range of environmental conditions en- countered during the year. In total, 13,649 individuals were captured within 23 genera and 99 species but with pronounced differences among ecosystems and seasons. The obtained results seem to demon- strate that dung beetles can be used to help identify ecosystems under very complex and variable environmental conditions. The ecological drift observed also demonstrates the possibility of using dung beetles as ecological indicators of disturbance in Amazonia. Keywords Amazon rainforest; beetles; biodiversity; scarab; seasonality; tropical forest ∗ ) Corresponding author; e-mail: [email protected] © Koninklijke Brill NV, Leiden, 2017 DOI 10.1163/15707563-00002538 Downloaded from Brill.com09/27/2021 05:23:13PM via free access 302 R.L. Cajaiba et al. / Animal Biology 67 (2017) 301–318 Introduction The landscape of the Brazilian Amazon (Amazonia) is being transformed by vast in- vestments in roads, leading to the growth of urban areas, extensive livestock rearing and intensive farming (Mertens et al., 2002; Tabarelli et al., 2004). These activities are closely associated with forest logging but also with hydroelectric power and mining (Soares-Filho et al., 2005). The new land uses might generate strong eco- logical impacts that were not fully anticipated (Cajaiba & Silva, 2017), resulting in isolation of animal populations and local extinctions (Aizen et al., 2012; Valiente- Banuet et al., 2015). From a conservation perspective, the condition of an ecosystem, the status or difference from reference conditions, might be assessed using informative surro- gates named ecological indicators (Heink & Kowarik, 2010; Costanza, 2012; Heath, 2013). Indicator species should be highly sensitive to changes in the structure and functioning of an ecosystem and easily monitored, providing valuable information on the system’s qualitative status (Rapport & Hildén, 2013). Dung beetles (DB; Coleoptera: Scarabaeinae) are considered particularly informative (Gardner et al., 2008; Da Silva et al., 2013), because of their sensitivity to abiotic and biotic factors. In fact, soil depth, soil structure and porosity, humidity, temperature, soil pH, and pollution (Nichols et al., 2008; Viegas et al., 2014; Campos & Hernández, 2015; Cajaiba et al., 2017) and the composition of the vertebrate community are strongly correlated with DB communities (Spector, 2006). Their roles as herbivores, carni- vores, omnivores, scavengers (Vandewalle et al., 2010) as well as pollinators, seed dispersers, and decomposers highlight their importance in the ecosystems (Nichols et al., 2008; Vandewalle et al., 2010; Bicknell et al., 2014). The suitability of DB for monitoring the effects of subtle changes in the ecosystems was demonstrated by Scheffler (2005) and Nichols & Gardner (2011). Diverse methods developed for Amazonia predict huge landscape changes in the future, with warmer and dryer climates, while the status of ecosystems remains without realistic projections (Marengo, 2015; Marengo et al., 2016). This prelimi- nary work examines differences in DB neotropical communities in different seasons and/or associated with ecosystems with increasing anthropogenic disturbances to determine their usefulness as ecological indicators. This information might guide the construction of more robust ecological assess- ments aimed at envisaging possible changes in the status of Amazonia’s pristine ecosystems, integrating the multiple factors associated with DB dynamics and highlighting the most effective management practices through quantitative metrics (Santos et al., 2016a, b). Material and methods Study sites The study was performed in the municipality of Uruará, state of Pará, Northern Brazil (−03°4327S, −53°448W). The dominant land use/land cover of the Downloaded from Brill.com09/27/2021 05:23:13PM via free access R.L. Cajaiba et al. / Animal Biology 67 (2017) 301–318 303 study area was natural forests (69% of the area). Extensive livestock production and the exploitation of timber at a large scale (mostly illegal) are currently consid- ered the most serious environmental threats (Cajaiba et al., 2016). The climate of the study area is classified as Aw (Köppen), i.e. hot and humid; the average annual rain- fall is 2000 mm (Peel et al., 2007). The studied areas encompass ecosystems that, in terms of physical characteristics and anthropogenic disturbances, are representative of the region: Native Vegetation (NV), Mature Secondary succession (MS: vege- tation with 15 years of regeneration), Early Secondary succession (ES: vegetation with five years of regeneration), Agriculture (Ag: cocoa plantations, Theobroma cacao L.) and Pasture for extensive livestock (Pa) (fig. 1). This gradient in distur- bance was considered fundamental to analyse the response of the DB communities (Cajaiba et al., 2017). Sampling method Sampling was carried out in February/March (rainy season), June (intermediary season), and September/October (dry season) of the year 2015. This allowed check- ing for seasonal differences in the activity and structure of DB communities. The Figure 1. Location of the study sites in the municipality of Uruará, state of Pará, northern Brazil. Abbreviations: Ag, agriculture; ES, early secondary succession; MS, mature secondary succession; NV, native vegetation; Pa, pasture. Downloaded from Brill.com09/27/2021 05:23:13PM via free access 304 R.L. Cajaiba et al. / Animal Biology 67 (2017) 301–318 sampling points were placed at a minimum distance of 100 m from ecotones to guarantee that most DB captured in the pitfalls were associated with the monitored ecosystem. Pitfall traps (75 mm diameter and 110 mm deep) were filled with forma- lin, alcohol, water, and a few drops of detergent. Each pitfall was covered by a roof to prevent rainwater from entering, and each trap remained installed for 48 h prior to collection. Each pitfall contained different types of bait: HF, human feces; RM, rotten meat; and RB, rotten banana, in order to attract different species according to their feeding habits. Non-baited pitfalls were used as control (Co). Seven sampling points were placed at each study site at distances of 100 m from each other. Each sample point contained four pitfall traps separated by a distance of 5 m and including the different baits (HF, RM, RB, Co). This protocol was applied to all ecosystems and monitoring periods, creating a total sampling effort of 840 traps. The DB collected were conserved in 70% ethanol, taken to the laboratory and identified to the species level when possible or assigned to morphospecies. The identification was based on the keys proposed by Vaz-de-Mello et al. (2011) and Pacheco & Vaz-de-Mello (2015). Data analysis One-way analysis of variance (ANOVA) was used followed by the Tukey test to test for: a) possible differences in the abundance and richness of dung beetles among ecosystems; b) possible differences in abundance and richness in different sampling periods (seasonal variation) and within each ecosystem (Zar, 1984). Bray-Curtis cluster analysis was applied to verify the similarity between different ecosystems and seasons, and the UPGMA algorithm was used to depict the distance based on the Bray-Curtis index. This index ranges between 0 (indicating no similarity in community composition between sites) and 1 (indicating complete overlap), and it is considered one of the most robust measures of community similarity (Magurran, 2004). The cophenetic correlation coefficient was used to verify that the result of the cluster analysis was significant. In order to check for environmental variables that influence the DB communities at particular periods of the year, a correlation analysis (Pearson correlation) was applied between DB abundance and richness and meteorological data – temperature, humidity and precipitation. The normality of the data was verified by the Shapiro-Wilk test. In order to homogenize the variances and normalize the residues the abundance was transformed by log(x + 1). All analyses were performed using PAST software version 3.14 (Hammer et al., 2001). Results A total of 13 649 dung beetles were captured within 23 genera and 99 species. The