Estimation of the maximum utilization area including home range and peripheral sites.

There is increasing evidence that occasional utilization area (peripheral sites), in addition to typical utilization area (home range), is important for wildlife conservation and management. Here we estimated the maximum utilization area (MUA), including both typical and occasional utilization areas, based on asymptotic curves of utilization area plotted against sample size. In previous studies, these curves have conventionally been plots of cumulative utilization area versus sample size, but this cumulative method is sensitive to stochastic effects. We propose a new method based on simulation studies where outcomes of replicated simulations are averaged to reduce stochastic effects. In this averaged method, possible combinations of sample size with the same number of location data replicated from a dataset were averaged and applied to the curves of utilization area. The cumulative method resulted in a large variation of MUA estimates, depending on the start date as well as total sample size of the dataset. In the averaged method, MUA estimates were robust against changes in the start date and total sample size. The large variation of MUA estimates arose because location data on any day including the start date are affected by unpredictable effects associated with animal activity and environmental conditions. In the averaged method, replicates of sample size resulted in a reduction of temporal stochasticity, suggesting that the method stably provides reliable estimates for MUA.

Linking population dynamics models with empirically derived models through phytoplankton primary production.

There are alternative methods for estimation of phytoplankton primary production (PP) that are fundamentally different in the calculation approach. The process-oriented PP model is a mechanistic, empirically derived method based on the photosynthesis-light relationships. The population dynamics-based PP calculation, which is a synthetic method, provides a production estimate based on population dynamics of phytoplankton. These alternative methods were here compared with regard to production estimates and linked to enhance the performance of the existing models of population dynamics applied to a wide variety of lakes worldwide in terms of morphometry, nutrient status, and light environments. Estimates of PP were shown to be sensitive to changes in phytoplankton sinking and zooplankton grazing rates in both methods. Production estimates in the process-oriented PP model were also sensitive to light-associated parameters such as day length. Although the production estimated from the population dynamics-based PP calculation tended to be lower than that from the process-oriented PP model irrespective of lake morphometry, production estimates calculated from both methods with standard parameterization were comparable when production was estimated on an annual timescale. However, it was also shown that the alternative methods could produce different production estimates when estimated on shorter timescales such as cyanobacterial blooms in summer. Cyanobacteria with low mortality due to grazing and sinking losses have been considered as trophic bottlenecks, but there is increasing evidence that their mortality is, to a considerable extent, due to parasitic pathogens. In the case of cyanobacterial blooms, an addition of parasite-related loss term (19%-33% of standing stock) resulted in a resolution of the difference in production estimates between the methods. These analyses theoretically support the critical role of parasitism and resolve the bottleneck problem in aquatic ecosystem metabolism.

Benthic-planktonic coupling, regime shifts, and whole-lake primary production in shallow lakes.

Alternative stable states in shallow lakes are typically characterized by submerged macrophyte (clear-water state) or phytoplankton (turbid state) dominance. However, a clear-water state may occur in eutrophic lakes even when macrophytes are absent. To test whether sediment algae could cause a regime shift in the absence of macrophytes, we developed a model of benthic (periphyton) and planktonic (phytoplankton) primary production using parameters derived from a shallow macrophyte-free lake that shifted from a turbid to a clear-water state following fish removal (biomanipulation). The model includes a negative feedback effect of periphyton on phosphorus (P) release from sediments. This in turn induces a positive feedback between phytoplankton production and P release. Scenarios incorporating a gradient of external P loading rates revealed that (1) periphyton and phytoplankton both contributed substantially to whole-lake production over a broad range of external P loading in a clear-water state; (2) during the clear-water state, the loss of benthic production was gradually replaced by phytoplankton production, leaving whole-lake production largely unchanged; (3) the responses of lakes to biomanipulation and increased external P loading were both dependent on lake morphometry; and (4) the capacity of periphyton to buffer the effects of increased external P loading and maintain a clear-water state was highly sensitive to relationships between light availability at the sediment surface and the of P release. Our model suggests a mechanism for the persistence of alternative states in shallow macrophyte-free lakes and demonstrates that regime shifts may trigger profound changes in ecosystem structure and function.

Macrophyte refuges, prey behaviour and trophic interactions: consequences for lake water clarity.

Macrophytes may enhance grazing on phytoplankton by providing a refuge for zooplankton against fish predation. Loss of macrophytes can trigger sudden degradation of water clarity (regime shift) in lakes. However, the presence of piscivores may drive planktivorous fish to take refuge amongst littoral macrophytes. To address the possibility of regime shifts, I here constructed an empirically based model that combined population dynamics of organisms with game theory for optimal habitat selection, taking into consideration the trophic structure, lake size and eutrophication. The model showed that macrophytes generally acted as a refuge for zooplankton, rather than for fish. The model predicted that regime shifts were more likely in small, shallow lakes and that the presence of macrophytes raised the possibility of regime shifts. The present study demonstrated that the fast dynamics of animal behaviour could lead to regime shifts, in connection with slower variables such as nutrient loading.