Quantifying resilience of humans and other animals.

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.

Flickering gives early warning signals of a critical transition to a eutrophic lake state.

There is a recognized need to anticipate tipping points, or critical transitions, in social-ecological systems. Studies of mathematical and experimental systems have shown that systems may 'wobble' before a critical transition. Such early warning signals may be due to the phenomenon of critical slowing down, which causes a system to recover slowly from small impacts, or to a flickering phenomenon, which causes a system to switch back and forth between alternative states in response to relatively large impacts. Such signals for transitions in social-ecological systems have rarely been observed, not the least because high-resolution time series are normally required. Here we combine empirical data from a lake-catchment system with a mathematical model and show that flickering can be detected from sparse data. We show how rising variance coupled to decreasing autocorrelation and skewness started 10-30 years before the transition to eutrophic lake conditions in both the empirical records and the model output, a finding that is consistent with flickering rather than critical slowing down. Our results suggest that if environmental regimes are sufficiently affected by large external impacts that flickering is induced, then early warning signals of transitions in modern social-ecological systems may be stronger, and hence easier to identify, than previously thought.

Lake and watershed characteristics rather than climate influence nutrient limitation in shallow lakes.

Both nitrogen (N) and phosphorus (P) can limit primary production in shallow lakes, but it is still debated how the importance of N and P varies in time and space. We sampled 83 shallow lakes along a latitudinal gradient (5 degrees 55 degrees S) in South America and assessed the potential nutrient limitation using different methods including nutrient ratios in sediment, water, and seston, dissolved nutrient concentrations, and occurrence of N-fixing cyanobacteria. We found that local characteristics such as soil type and associated land use in the catchment, hydrology, and also the presence of abundant submerged macrophyte growth influenced N and P limitation. We found neither a consistent variation in nutrient limitation nor indications for a steady change in denitrification along the latitudinal gradient. Contrary to findings in other regions, we did not find a relationship between the occurrence of (N-fixing and non-N-fixing) cyanobacteria and the TN:TP ratio. We found N-fixing cyanobacteria (those with heterocysts) exclusively in lakes with dissolved inorganic nitrogen (DIN) concentrations of < 100 microg/L, but notably they were also often absent in lakes with low DIN concentrations. We argue that local factors such as land use and hydrology have a stronger influence on which nutrient is limiting than climate. Furthermore, our data show that in a wide range of climates N limitation does not necessarily lead to cyanobacterial dominance.

Impacts of agricultural phosphorus use in catchments on shallow lake water quality: About buffers, time delays and equilibria.

Phosphorus (P) losses caused by intensive agriculture are known to have potentially large negative effects on the water quality of lakes. However, due to the buffering capacity of soils and lake ecosystems, such effects may appear long after intensive agriculture started. Here we present the study of a coupled shallow lake catchment model, which allows a glimpse of the magnitude of these buffer-related time delays. Results show that the buffering capacity of the lake water was negligible whereas buffering in the lake sediment postponed the final lake equilibrium for several decades. The surface soil layer in contact with runoff water was accountable for a delay of 5-50 years. The most important buffer, however, was the percolation soil layer that may cause a delay of 150-1700 years depending on agricultural P surplus levels. Although the buffers could postpone final lake equilibria for a considerable time, current and target agricultural surplus levels eventually led to very turbid conditions with total P concentrations of 2.0 and 0.6 mg L(-1) respectively. To secure permanent clear water states the current agricultural P surplus of 15 kg P ha(-1) yr(-1) should drop to 0.7 kg P ha(-1) yr(-1). We present several simple equations that can be used to estimate the sustainable P surplus levels, buffer related time delays and equilibrium P concentrations in other catchment-lake systems.