The Dynamic Shift Detector: An algorithm to identify changes in parameter values governing populations

Forecasting insect dynamics in a changing world

Predicting how insects will respond to stressors through time is difficult because of the diversity of insects, environments, and approaches used to monitor and model. Forecasting models take correlative/statistical, mechanistic models, and integrated forms; in some cases, temporal processes can be inferred from spatial models. Because of heterogeneity associated with broad community measurements, models are often unable to identify mechanistic explanations. Many present efforts to forecast insect dynamics are restricted to single-species models, which can offer precise predictions but limited generalizability. Trait-based approaches may offer a good compromise that limits the masking of the ranges of responses while still offering insight. Regardless of the modeling approach, the data used to parameterize a forecasting model should be carefully evaluated for temporal autocorrelation, minimum data needs, and sampling biases in the data. Forecasting models can be tested using near-term predictions and revised to improve future forecasts.

Multi-season climate projections forecast declines in migratory monarch butterflies

Climate change poses a unique threat to migratory species as it has the potential to alter environmental conditions at multiple points along a species' migratory route. The eastern migratory population of monarch butterflies (Danaus plexippus) has declined markedly over the last few decades, in part due to variation in breeding-season climate. Here, we combined a retrospective, annual-cycle model for the eastern monarch population with climate projections within the spring breeding grounds in eastern Texas and across the summer breeding grounds in the midwestern U.S. and southern Ontario, Canada to evaluate how monarchs are likely to respond to climate change over the next century. Our results reveal that projected changes in breeding-season climate are likely to lead to decreases in monarch abundance, with high potential for overwintering population size to fall below the historical minimum three or more times in the next two decades. Climatic changes across the expansive summer breeding grounds will also cause shifts in the distribution of monarchs, with higher projected abundances in areas that become wetter but not appreciably hotter (e.g., northern Ohio) and declines in abundance where summer temperatures are projected to increase well above those observed in the recent past (e.g., northern Minnesota). Although climate uncertainties dominate long-term population forecasts, our analyses suggest that we can improve precision of near-term forecasts by collecting targeted data to better understand relationships between breeding-season climate variables and local monarch abundance. Overall, our results highlight the importance of accounting for the impacts of climate changes throughout the full-annual cycle of migratory species.

Long transient response of vegetation dynamics after four millennia of anthropogenic impacts in an island ecosystem

Agents of global change commonly have a higher impact on island ecosystem dynamics. In the Mediterranean region, those dynamics have historically been influenced by anthropogenic impacts, for example, the introduction of invasive species and overharvesting of resources. Here, we analysed the spatio-temporal dynamics of vegetation in sa Dragonera island, which experienced a large environmental change ca. 4000 years ago by the arrival of humans. Anthropogenic impacts, such as herbivory by goats and over-logging, ended in the 1970s, while in 2011 the site became the largest Mediterranean island where rats were eradicated. Invasive rats and goats played the ecological role of two endemic species, the cave goat and the giant dormouse, which inhabited the island for more than 5 million years and were rapidly extinct by humans. We used Landsat imagery to explore NDVI as a proxy of vegetation productivity over the years 1984-2021, orthophotos to assess changes in land and vegetation covers and historical plant inventories to study the dynamics in plant diversity. Results showed that those indicators steadily increased both in spring and in summer, while the noise around the trends was partially explained by climate variability. The regime shifts in the temporal dynamics of vegetation productivity suggested a transient from a perturbed to a non-perturbed stable state. Trends in successional dynamics, spatial self-organization and plant diversity also showed the same type of transient dynamics. Historical perturbations related to harvesting (mainly the synergies between goat browsing, burning and forest over-logging) were more important than rat eradication or the influence of climate to explain the vegetation dynamics. Our study shows the transient nature of this small island ecosystem after 4000 years of perturbations and its current path towards vegetation dynamics more controlled by ecological interactions lacking large herbivores and omnivores, drought dynamics and the carrying capacity of the island.

Long-term ecological research and the COVID-19 anthropause: A window to understanding social-ecological disturbance

The period of disrupted human activity caused by the COVID-19 pandemic, coined the "anthropause," altered the nature of interactions between humans and ecosystems. It is uncertain how the anthropause has changed ecosystem states, functions, and feedback to human systems through shifts in ecosystem services. Here, we used an existing disturbance framework to propose new investigation pathways for coordinated studies of distributed, long-term social-ecological research to capture effects of the anthropause. Although it is still too early to comprehensively evaluate effects due to pandemic-related delays in data availability and ecological response lags, we detail three case studies that show how long-term data can be used to document and interpret changes in air and water quality and wildlife populations and behavior coinciding with the anthropause. These early findings may guide interpretations of effects of the anthropause as it interacts with other ongoing environmental changes in the future, particularly highlighting the importance of long-term data in separating disturbance impacts from natural variation and long-term trends. Effects of this global disturbance have local to global effects on ecosystems with feedback to social systems that may be detectable at spatial scales captured by nationally to globally distributed research networks.