Abstract. Koneri R, Nangoy MJ, Siahaan P. 2019. The abundance and diversity of butterflies (Lepidoptera: Rhopalocera) in Talaud Islands, North Sulawesi, Indonesia. Biodiversitas 20: 3275-3283. Butterflies play a number of roles in the ecosystem. They help pollination and natural propagation and also are an important element of the food chain as prey for bats, birds, and other insectivorous animals. This study aimed to analyze the abundance and diversity of butterflies (Lepidoptera: Rhopalocera) in the Talaud Islands of North Sulawesi, Indonesia. The sampling method used was scan sampling along the transect line in three habitat types, namely, forest edge, farmland, and shrubland. The species diversity was determined by using the diversity index (Shanon-Wiener), the species richness index was calculated using the Margalef species richness index (R1), while species evenness was counted by using the Shannon evenness index (E). One-way ANOVA and Duncan test at the 95% significance level were used to determine differences in species richness, species abundance, species diversity values, and species evenness among habitat. In this study, we identified 1008 individuals of butterfly consisted of 32 species and five families. Nymphalidae was the dominant family with 15 species, while the highest abundance species was Eurema tominia. The highest species abundance, species richness index, species diversity index, and species evenness index were found in forest edge habitat. The largest similarity index of the composition of the butterfly communities was found in forest edge and farmland habitats. The abundance and diversity of butterfly species in a habitat are strongly influenced by the diversity of vegetation as shelter and source of nectar for butterflies, and the existence of a river as a source of water and minerals from wet rocks, mud, and sand along the riverside.

Defining appropriate null expectations for species distribution hypotheses is important because sampling bias and spatial autocorrelation can produce realistic, but ecologically meaningless, geographic patterns. Generating null species occurrences with similar spatial structure to observed data can help overcome these problems, but existing methods focus on single or pairs of species and do not incorporate between-species spatial structure that may occlude comparative biogeographic analyses. Here, we describe an algorithm for generating randomised species occurrence points that mimic the within-and between-species spatial structure of real datasets and implement it in a new R package -fauxcurrence. The algorithm can be implemented on any geographic domain for any number of species, limited only by computing power. To demonstrate its utility, we apply the algorithm to two common analysis-types: testing the fit of species distribution models (SDMs) and evaluating niche-overlap. The method works well on all tested datasets within reasonable timescales. We found that many SDMs, despite a good fit to the data, were not significantly better than null expectations and identified only two cases (out of a possible 32) of significantly higher niche divergence than expected by chance. The package is user-friendly, flexible and has many potential applications beyond those tested here, such as joint SDM evaluation and species co-occurrence analysis, spanning the areas of ecology, evolutionary biology and biogeography.

Defining appropriate null expectations for species distribution hypotheses is important because sampling bias and spatial autocorrelation can produce realistic, but ecologically meaningless, geographic patterns. Generating null species occurrences with similar spatial structure to observed data can help overcome these problems, but existing methods focus on single or pairs of species and do not incorporate between-species spatial structure that may occlude comparative biogeographic analyses. Here, we describe an algorithm for generating randomised species occurrence points that mimic the within- and between-species spatial structure of real datasets and implement it in a new R package - fauxcurrence. The algorithm can be implemented on any geographic domain for any number of species, limited only by computing power. To demonstrate its utility, we apply the algorithm to two common analysis-types: testing the fit of species distribution models (SDMs) and evaluating niche-overlap. The method works well on all tested datasets within reasonable timescales. We found that many SDMs, despite a good fit to the data, were not significantly better than null expectations and identified only two cases (out of a possible 32) of significantly higher niche divergence than expected by chance. The package is user-friendly, flexible and has many potential applications beyond those tested here, such as joint SDM evaluation and species co-occurrence analysis, spanning the areas of ecology, evolutionary biology and biogeography.

Abstract. Koneri R, Nangoy MJ, Wakhid. 2021. Richness and diversity of insect pollinators in various habitats around Bogani Nani Wartabone National Park, North Sulawesi, Indonesia. Biodiversitas 22: 288-297.  The pollination of plants by insects is one of the most important and essential ecosystem services in natural and agricultural landscapes and Insect pollinators play an important role in this process. This is because they help to transfer pollen from the anther to the stigma, which leads to fertilization. This study aims to analyze the richness and diversity of insect pollinators in various habitats around the Bogani Nani Wartabone National Park, Toraut, North Sulawesi. It was carried out from June to August 2020 on three types of habitats around the National Park, namely forest edges, shrubs and agricultural land. For each habitat, four plots with a size of 50 m x 25 m were made with a distance of 100 m between them. The insect pollinator observation technique used was the scan sampling method. Furthermore, data analysis was carried out on abundance, richness index, diversity index, species evenness index, dominance index and the relationship between sampling locations and environmental factors. The results showed that there were 979 insect pollinators caught at the observation point, which consisted of 60 species from 16 families and 4 orders and the most common order was Hymenoptera with 31 species. The species which were found based on their relative abundance indicated that Nomia strigata was the most abundant followed by Nomia melanderi, Apis dorsata, Ropalidia fasciata and Amegilla zonata. Furthermore, the highest abundance of insect pollinators was found in shrub habitats, while the highest species richness and diversity were found at the forest edge. Therefore, it was concluded that different types of habitat affect the richness and diversity of insect pollinator species around the Bogani Nani Wartabone National Park. In addition, this proves that the forest area of Bogani Nani Wartabone National Park generally supports the abundance, richness, and diversity of insect pollinators, which were discovered in the surrounding habitats, namely shrubs and agricultural land.

Abstract. Ransaleleh TA, Wahyuni I, Kawatu M, Nangoy MJ, Wiantoro S. 2021. Behavior of the black flying fox, Pteropus alecto (Chiroptera: Pteropodidae) in cages. Biodiversitas 22: 5657-5665. Hunting and illegal trading have become a common thread for the black flying fox in Sulawesi, Indonesia. However, information on its biology and behavior as a baseline for conservation and management program is still lacking. Therefore, this study aims to examine the behavioral activities of black flying fox, Pteropus alecto (Temminck, 1837) kept in cages through direct observation. The results showed that feeding was carried out by descending to the bottom of the cage before picking up fruits with the mouth and wings. Furthermore, the time associated with this process ranged from 06.01 to 10.00, while agonistic behavior performed using claws and wings took place from 10.01 to 14.00 in the daytime and 22.01 to 02.00 at night. Grooming was carried out using the tongue and wings, from 14.01 to 18.00 during the day and 22.01 to 02.00 during the night. Subsequently, the bats slept by perching with the eyes closed and the whole body wrapped with the wings from 02.01 to 10.00, while locomotion and stationary behaviors were performed by perching with eyes open and flying around the cage with the wings spread apart from 10.01 to 14.00 during the day and 22.01 to 02.00 at night. The percentage of day and night behavior activities consist of agonistic 0.12%, grooming 6.14%, eating 19.36%, sleeping 56.33%, and stationary and locomotive 17.76%. The results improve the understanding of P. alecto's daily activities in the cage which are difficult to observe in the wild and provide insight for conservation and wildlife management. Furthermore, information from this study is useful for future bat captivity programs.