Anssi Lensu

The collection of citizen data is often employed to generate insights regarding species distribution, population sizes, and population structure; however, biases inherent in citizen science are seldom addressed. In this study, we examined the factors influencing hunters' observations of moose, Alces alces , during the moose hunting season in Finland. By analyzing approximately 0.5 million moose observations collected between 2017 and 2021, we discovered that, in addition to the population size in the previous year, the progression of the hunting season due to culling had a significant impact on the observations. The effects of hunting effort, including the time spent hunting and the number of hunters, were notably influenced by the use of dogs in hunting. However, different classes of moose exhibited varied responses to the presence of dogs, suggesting a potential for biases in sex ratio and population size estimation. Additionally, landscape characteristics also affected observations, which may suggest variations in the potential for visual observation or differences in moose behavior. We discuss the implications of our findings for biases in population parameter estimation and outline several areas for future research.

Knowledge of species' habitat requirements, and the environmental conditions and resources needed for survival and reproduction are key factors in effective conservation management. We used species distribution modeling to study golden eagle ( Aquila chrysaetos ) habitat requirements. Additionally, we developed two different models to determine suitability at the nest‐site and territory levels. We estimated the maximum number of predicted territories to infer the potential carrying capacity by developing a simulation based on our nest and territory models. As the species is known to avoid human disturbance, we also evaluated the potential risk of wind farms to predicted golden eagle territory areas. Our results show that slope preference (>10°) and avoidance of human settlements are key factors at nest sites, explaining 50% and 21% of the variance in the nest model, respectively. At the territory level, avoidance of human habitation is the most important factor (51%). As expected, areas predicted to have high occupancy probability are most abundant in northern Finland, where most of the current population breeds. Based on our simulation results, the species has an estimated 170,000 km ² of modeled habitat available that could carry 492–554 territories in Finland depending on the population size and habitat quantity, which dictate territory size. When examining wind farms at different stages of planning, we found that 18.9% of them were close to core areas in known nesting territories, and 1.4%–6.7% were close to core areas in simulated potential territories. Our results demonstrate how wind farms impact golden eagle population in Finland and must be considered in current and future planning.

There is a global call for more efficient voluntary conservation practices. Voluntary conservation requires landowner participation, which may limit conservation efficiency. Here, we evaluated the ecological costs and benefits of a voluntary conservation policy relative to obligatory conservation, two hypothetical scenarios of randomly distributed conservation area networks, and two hypothetical ecologically optimized conservation area networks. The study was based on spatial conservation prioritization maps reflecting the conservation priority of forest in Central Finland. Our results suggest that voluntary conservation area networks can be relatively cost‐efficient with higher nature values and better connectivity compared to a randomly selected conservation area network. Voluntary conservation area networks scored slightly higher nature values than the obligatory conservation area network but suffered from lower connectivity and smaller area size. Quality differences between the voluntary conservation area networks were minor. Our analysis showed that neither of the voluntary conservation area networks achieved its full conservation potential when compared to an ecologically optimized conservation area network. Thus, our results indicate that the societal pursuit of landowner's conservation acceptance, and hence rejection of the systematic conservation planning, has come with a cost of reduced nature values and connectivity in the current conservation area network.

The representativeness of aquatic ecosystem monitoring and the precision of the assessment results are of high importance when implementing the EU’s Water Framework Directive that aims to secure a good status of waterbodies in Europe. However, adapting monitoring designs to answer the objectives and allocating the sampling resources effectively are seldom practiced. Here, we present a practical solution how the sampling effort could be re-allocated without decreasing the precision and confidence of status class assignment. For demonstrating this, we used a large data set of 272 intensively monitored Finnish lake, coastal, and river waterbodies utilizing an existing framework for quantifying the uncertainties in the status class estimation. We estimated the temporal and spatial variance components, as well as the effect of sampling allocation to the precision and confidence of chlorophyll-a and total phosphorus. Our results suggest that almost 70% of the lake and coastal waterbodies, and 27% of the river waterbodies, were classified without sufficient confidence in these variables. On the other hand, many of the waterbodies produced unnecessary precise metric means. Thus, reallocation of sampling effort is needed. Our results show that, even though the studied variables are among the most monitored status metrics, the unexplained variation is still high. Combining multiple data sets and using fixed covariates would improve the modeling performance. Our study highlights that ongoing monitoring programs should be evaluated more systematically, and the information from the statistical uncertainty analysis should be brought concretely to the decision-making process.

Clastic-biogenic varves are widely used for reconstructing past climate: in boreal environments, the accumulation of minerogenic clasts on the lake floor is generally considered a proxy for past variations in spring floods reflecting previous winter conditions. However, the physical mechanisms behind this winter climate sensitivity and the influence of catchment type on the varve formation are not fully investigated. Here, we present a winter climate record inferred from the clastic laminae of three lakes located on the region of fine-grained tills in Eastern Finland spanning from AD 1890 to 1990. The minerogenic varve data are compared with instrumental meteorological and hydrological time series in order to investigate the physical link between winter and spring climate and minerogenic matter accumulation. Our analyses reveal that the climate-catchment mechanisms operating in the region of fine-grained tills differ crucially from previously described climate catchment interactions on sand moraine-dominated catchments in Finland, where the maximum river discharge in spring controls the clastic lamina formation. However, in contrast to earlier boreal varve records from Central Finland, the clastic lamina formation in the studied region correlates negatively with spring temperatures and winter precipitation. This could be an artefact of varying catchment dynamics but also related to the regional climate. The lakes surrounded by catchments characterized by fine-grained tills are more sensitive to cold and dry winters. The differences in the sensitivity of varve characteristics to climate, highlights the importance of understanding the catchment dynamics in detail in order to better understand climatic forcing.

The renewable energy sector is growing at a rapid pace in northern Chile and the solar energy potential is one of the best worldwide. Therefore, many types of solar power plant facilities are being built to take advantage of this renewable energy resource. Solar energy is considered a clean source of energy, but there are potential environmental effects of solar technology, such as landscape fragmentation, extinction of local biota, microclimate changes, among others. To be able to minimize environmental impacts of solar power plants, it is important to know what kind of environmental conditions solar power plants create. This study provides information about abiotic and biotic conditions in the vicinity of photovoltaic solar power plants. Herein, the influence of these power plants as drivers of new microclimate conditions and arthropods diversity composition in the Atacama Desert was evaluated. Microclimatic conditions between panel mounts was found to be more extreme than in the surrounding desert yet beneath the panels temperature is lower and relative humidity higher than outside the panel area. Arthropod species composition was altered in fixed-mount panel installations. In contrast, solar tracking technology showed less influence on microclimate and species composition between Sun and Shade in the power plant. Shady conditions provided a refuge for arthropod species in both installation types. For example, Dipterans were more abundant in the shade whereas Solifugaes were seldom present in the shade. The presented findings have relevance for the sustainable planning and construction of solar power plants.

Solar radiation mineralizes dissolved organic matter (DOM) to dissolved inorganic carbon through photochemical reactions (DIC photoproduction) that are influenced by iron (Fe) and pH. This study addressed as to what extent Fe contributes to the optical properties of the chromophoric DOM (CDOM) and DIC photoproduction at different pH values. We created the associations of Fe and DOM (Fe-DOM) that cover the range of loadings of Fe on DOM and pH values found in freshwaters. The introduced Fe enhanced the light absorption by CDOM independent of pH. Simulated solar irradiation decreased the light absorption by CDOM (i.e., caused photobleaching). Fe raised the rate of photobleaching and steepened the spectral slopes of CDOM in low pH but resisted the slope steepening in neutral to alkaline pH. The combination of a low pH (down to pH 4) and high Fe loading on DOM (up to 3.5 μmol mg DOM^–1) increased the DIC photoproduction rate and the apparent quantum yields for DIC photoproduction up to 7-fold compared to the corresponding experiments at pH >6 or without Fe. The action spectrum for DIC photoproduction shifted toward the visible spectrum range at low pH in the presence of Fe. Our results demonstrated that Fe can contribute to DIC photoproduction by up to 86% and produce DIC even at the visible spectrum range in acidic waters. However, the stimulatory effect of Fe is negligible at pH >7.