Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Iterative Near-Term Ecological Forecasting: Needs, Opportunities, And Challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward

Scale-invariant structure of size fluctuations in plants

A wide range of physical and biological systems exhibit complex behaviours characterised by a scale-invariant structure of the fluctuations in their output signals. In the context of plant populations, scaling relationships are typically allometric. In this study, we analysed spatial variation in the size of maize plants (Zea Mays L.) grown in agricultural plots at constant densities and found evidence of scaling in the size fluctuations of plants. The findings indicate that the scaling of the probability distribution of spatial size fluctuation exhibits non-Gaussian behaviour compatible with a Lévy stable process. The scaling relationships were observed for spatial scales spanning three orders of magnitude. These findings should provide additional information for the selection and development of empirically accurate models of pattern formation in plant populations

Approaches to advance scientific understanding of macrosystems ecology

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological pat- terns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require valida- tion, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Functionally reversible impacts of disturbances on lake food webs linked to spatial and seasonal dependencies

Increasing human impact on the environment is causing drastic changes in disturbance regimes and how they prevail over time. Of increasing relevance is to further our understanding on biological responses to pulse disturbances (short duration) and how they interact with other ongoing press disturbances (constantly present). Because the temporal and spatial contexts of single experiments often limit our ability to generalize results across space and time, we conducted a modularized mesocosm experiment replicated in space (five lakes along a latitudinal gradient in Scandinavia) and time (two seasons, spring and summer) to generate general predictions on how the functioning and composition of multitrophic plankton communities (zoo-, phyto- and bacterioplankton) respond to pulse disturbances acting either in isolation or combined with press disturbances. As pulse disturbance, we used short-term changes in fish presence, and as press disturbance, we addressed the ongoing reduction in light availability caused by increased cloudiness and lake browning in many boreal and subarctic lakes. First, our results show that the top-down pulse disturbance had the strongest effects on both functioning and composition of the three trophic levels across sites and seasons, with signs for interactive impacts with the bottom-up press disturbance on phytoplankton communities. Second, community composition responses to disturbances were highly divergent between lakes and seasons: temporal accumulated community turnover of the same trophic level either increased (destabilization) or decreased (stabilization) in response to the disturbances compared to control conditions. Third, we found functional recovery from the pulse disturbances to be frequent at the end of most experiments. In a broader context, these results demonstrate that top-down, pulse disturbances, either alone or with additional constant stress upon primary producers caused by bottom-up disturbances, can induce profound but often functionally reversible changes across multiple trophic levels, which are strongly linked to spatial and temporal context dependencies. Furthermore, the identified dichotomy of disturbance effects on the turnover in community composition demonstrates the potential of disturbances to either stabilize or destabilize biodiversity patterns over time across a wide range of environmental conditions