Temporal changes in community composition are a facet of biodiversity change and are referred to as temporal beta diversity. Macroecological patterns of temporal beta diversity have gained attention because of the recent biodiversity crisis. However, no one has seriously studied how temporal beta diversity differs from spatial beta diversity, and the most basic neutral dynamics and temporal beta-diversity patterns remain unknown. Therefore, the present study aimed to reveal the basic properties of temporal beta-diversity patterns under neutral dynamics and identify their differences from those of spatial beta-diversity patterns. A simulation of neutral dynamics was conducted to test the parameter dependency of temporal beta-diversity patterns. Specifically, four fundamental parameters of the neutral model—the fundamental biodiversity number, local community size, mortality rate, and immigration rate—were studied. To describe the form of the simulated temporal distance-decay patterns based on both the Bray–Curtis and Sørensen dissimilarity indices, a three-parameter negative exponential function was fitted for each simulated dissimilarity matrix. The negative exponential function was successfully fitted to all the simulated results and three estimated parameters and the intercepts of the function were plotted along the change in the four parameters of the neutral model. The simulated results demonstrated that upper limits exist in the temporal distance-decay patterns; thus, the temporal distance-decay curves saturate before reaching a completely dissimilar state. Additionally, the form of the curve strongly depends on the four parameters of the neutral model. These results suggest that the relationship between local communities and virtual species pools differs in temporal and spatial beta diversity. Specifically, they suggest that the species pool is spatially variable but temporally constant.

Large areas of forests are annually damaged or destroyed by outbreaking insect pests. Understanding the factors that trigger and terminate such population eruptions has become crucially important, as plants, plant-feeding insects, and their natural enemies may respond differentially to the ongoing changes in the global climate. In northernmost Europe, climate-driven range expansions of the geometrid moths Epirrita autumnata and Operophtera brumata have resulted in overlapping and increasingly severe outbreaks. Delayed density-dependent responses of parasitoids are a plausible explanation for the ten-year population cycles of these moth species, but the impact of parasitoids on geometrid outbreak dynamics is unclear due to a lack of knowledge on the host ranges and prevalences of parasitoids attacking the moths in nature. To overcome these problems, we reviewed the literature on parasitism in the focal geometrid species in their outbreak range, and then constructed a DNA barcode reference library for all relevant parasitoid species based on reared specimens and sequences obtained from public databases. The combined parasitoid community of E. autumnata and O. brumata consists of 32 hymenopteran species, all of which can be reliably identified based on their barcode sequences. The curated barcode library presented here opens up new opportunities for estimating the abundance and community composition of parasitoids across populations and ecosystems based on mass barcoding and metabarcoding approaches. Such information can be used for elucidating the role of parasitoids in moth population control, possibly also for devising methods for reducing the extent, intensity, and duration of outbreaks.

Restoration has now emerged as a global priority, with international initiatives such as the “UN Decade on Ecosystem Restoration (2021-2030)”. To fulfil the large-scale global restoration ambitions, an essential step is the monitoring of vegetation recovery after restoration interventions. The aim of this study was to evaluate the utility of remotely-sensed vegetation indices, Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), to monitor the rate of forest regeneration across a tropical forest restoration project area in Kibale National Park, Uganda. As a result, we observed non-linear patterns in NDVI and EVI across the first 25 years of recovery. Both NDVI and EVI increase for the first 10 years of forest regeneration. This “greening” phase could be used as the indicator of successful onset of forest recovery. In particular, the decline of elephant grass, which suppresses the natural regeneration of trees in our area, can be detected as an increase in NDVI. Primary forests differed from the 25-year-old regenerating forests based on the unique combination of low mean and low seasonal variation in EVI. Our results, therefore, suggest that the long-term success of forest restoration could be monitored by evaluating how closely the combination of mean, and degree of seasonal variation in EVI, resembles that observed in the primary forest.