Bee Assemblage in the Southern Chihuahuan Desert: The Role of Season, Year, and Trap Color in Abundance

Recognizing how populations fluctuate over time is a crucial factor in determining the environmental elements affecting population persistence. However, the limited information on wild bee populations complicates the estimation of the impact of anthropogenic threats leading to changes in population size. To address this, we conducted a study capturing and monitoring nine species of wild bees through monthly samplings over four years. Tray traps were placed in permanent plots, and capture records were used to determine population size (N) and density (D). A generalized linear model (GLM) was employed to determine how the use of traps affected bee species captures. The families Apidae and Halictidae represented the most captures. Apis mellifera, the Lasioglossum (Dialictus spp.) complex, and Macrotera sinaloana exhibited the largest number of captures and highest population density. Most species (77.7%) showed a tendency to remain constant over the years and to have a higher number of captures in the spring months. Moreover, yellow traps were the most effective in capturing bee individuals. We suggest that the availability of essential resources and the reduction in environmental stressors positively affected the capture of wild bee populations.

Rare and declining bee species are key to consistent pollination of wildflowers and crops across large spatial scales

Biodiversity promotes ecosystem function (EF) in experiments, but it remains uncertain how biodiversity loss affects function in larger-scale natural ecosystems. In these natural ecosystems, rare and declining species are more likely to be lost, and function needs to be maintained across space and time. Here, we explore the importance of rare and declining bee species to the pollination of three wildflowers and three crops using large-scale (72 sites across 5000 km² ), multi-year datasets. Half of the sampled bee species (82/164) were rare or declining, but these species provided only ~15% of overall pollination. To determine the number of species important to EF, we used two methods of "scaling up," both of which have previously been used for biodiversity-function analysis. First, we summed bee species' contributions to pollination across space and time and then found the minimum set of species needed to provide a threshold level of function across all sites; according to this method, effectively no rare and declining bee species were important to pollination. Second, we account for the "insurance value" of biodiversity by finding the minimum set of bee species needed to simultaneously provide a threshold level of function at each site in each year. The second method leads to the conclusion that 25 rare and eight declining bee species (36% and 53% of all rare and declining bee species, respectively) are included in the minimum set. Our findings provide some of the strongest evidence yet that rare and declining species are key to meeting threshold levels of EF, thereby providing a more direct link between real-world biodiversity loss and EF.

Declining age at menarche in Indonesia: a systematic review and meta-analysis

BACKGROUND

There has been much research on the average age at menarche onset. In higher income countries the lowering in average age at menarche is earlier than in middle-income countries and lower income countries. Indonesia as a middle-income country also has some research experience related to the average age at menarche for girls.

OBJECTIVES

This study aimed to review the lowering of the average age at menarche in Indonesia and to predict changes in average age at menarche.

METHODS

This study provides a systematic review and meta-analysis using references from Google Scholar, PubMed and Popline databases on the trend of age at menarche in Indonesia and other data sources from local and national survey reports. Metaprop command in STATA was used to do the meta-analysis of proportion of early age at menarche and time series with auto-regressive integrated moving average (ARIMA) models were used in analyzing the trend and predicting the age at menarche.

RESULTS

The results show that in Indonesia the timing of age at menarche onset has significantly lowered during the 40 years before 2010. There was meaningful decrease of age at menarche, which changed from 14.43 years [confident interval (CI) 95%: 14.42, 14.44] to 13.63 years (CI95%: 13.63, 13.64). Using the ARIMA model, mean age at menarche onset for the next year predicted that the coefficient regression would be -0.0245 (CI95%: -0.0275, -0.0215). The predicted average age at menarche shows a decrease of 0.0245 years (8-9 days) each year.

CONCLUSION

The findings indicate a significant lowering of age at menarche in Indonesian girls that has continued as a predictable trend through time until the present, paralleling recent socioeconomic changes. These predictions provide key indicators of a girl's future healthy transition from childhood into young adulthood.