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Managing the disturbance of visitors due to crowding is an important management task in protected areas with high use levels. To achieve this, managers need to know how the use level affects the perceived disturbance due to crowding. Here we present a method to predict the level of disturbance as a function of use level measured by number of visitors. In contrast to the visual approach where subjects are asked to evaluate acceptability of use levels from manipulated images of scenery, our approach uses data gathered from actual experiences: actual (measured) use levels and concurrent on-site data on levels of disturbance experienced by visitors. Using the example of Nature Park Telašćica, we show how these data can be acquired with limited resources (a smart-phone and short, time-stamped questionnaires), and demonstrate the subsequent analysis and model fitting. The resulting model estimates the probability that a visitor experiencing a given use level will report certain level of disturbance. We suggest a way of using the probability density functions to define an inherent limit of acceptable disturbance (LAD) due to crowding; the LAD can also be set to a desired value by management. Regardless of the definition, LAD can be used to determine the maximum acceptable use level as dictated by crowding considerations. The method gives predictions consistent with previous literature and can be used even when data are collected at low use levels.

The microalgae of the genus Pseudochloris/Picochlorum are characterized by fast growth, and wide nutrient (type and concentration) and salinity tolerance, all contributing towards exploration of their use in high-density biomass production and wastewater bioremediation. In this study, removal of nitrogen and phosphorus nutrients from oil refinery wastewater was monitored during growth of the marine eukaryotic microalgae Pseudochloris wilhelmii, with emphasis on biochemical analyses of its biomass quality to evaluate suitability for biodiesel production. A series of growth experiments under various nutrient and light regimes were performed in a temperature range of 20-30°C to evaluate nutrient removal and biomass growth dependence on temperature. The highest removal rate of dissolved inorganic nitrogen reached under the given experimental conditions was 0.823 mmol/(gday) accompanied by the corresponding biomass productivity of 115.2 mg/(Lday). Depending on light and temperature, the final lipid concentration ranged 181.5 – 319.8 mg/L. Furthermore, increase in nutrient load decreased the maximum specific growth rate by 25%, and the maximum specific removal rate of the dissolved inorganic nitrogen by 19%, whereas the duration of bioremediation process was nearly doubled. In contrast, constant light exposure expedited the nitrogen removal, i.e. bioremediation process, by almost 40%, while supporting over three times higher biomass productivity and the highest maximum specific growth rate of 0.528 g/(gday). The conditions favoring the highest nitrogen removal and highest toxicity reduction in oil refinery wastewater are met at 24°C and 130 µmol phot/(m2s). The highest proportion of carbon-binding to the P. wilhelmii biomass was noticed under the same conditions, thus indicating them as the most favorable conditions for hydrocarbon removal as well as for CO2 sequestration. Pseudochloris wilhelmii therefore represents a promising candidate for oil refinery wastewater remediation and valuable biomass cogeneration on a large-scale.