Swedish University of Agricultural Sciences

About: Swedish University of Agricultural Sciences is a education organization based out in Uppsala, Sweden. It is known for research contribution in the topics: Population & Soil water. The organization has 13510 authors who have published 35241 publications receiving 1414458 citations. The organization is also known as: Sveriges Lantbruksuniversitet & SLU.

A model-driven approach to quantify migration patterns: individual, regional and yearly differences.

Abstract: Summary 1. Animal migration has long intrigued scientists and wildlife managers alike, yet migratory species face increasing challenges because of habitat fragmentation, climate change and over-exploitation. Central to the understanding migratory species is the objective discrimination between migratory and nonmigratory individuals in a given population, quantifying the timing, duration and distance of migration and the ability to predict migratory movements. 2. Here, we propose a uniform statistical framework to (i) separate migration from other movement behaviours, (ii) quantify migration parameters without the need for arbitrary cut-off criteria and (iii) test predictability across individuals, time and space. 3. We first validated our novel approach by simulating data based on established theoretical movement patterns. We then formulated the expected shapes of squared displacement patterns as nonlinear models for a suite of movement behaviours to test the ability of our method to distinguish between migratory movement and other movement types. 4. We then tested our approached empirically using 108 wild Global Positioning System (GPS)collared moose Alces alces in Scandinavia as a study system because they exhibit a wide range of movement behaviours, including resident, migrating and dispersing individuals, within the same population. Applying our approach showed that 87% and 67% of our Swedish and Norwegian subpopulations, respectively, can be classified as migratory. 5. Using nonlinear mixed effects models for all migratory individuals we showed that the distance, timing and duration of migration differed between the sexes and between years, with additional individual differences accounting for a large part of the variation in the distance of migration but not in the timing or duration. Overall, the model explained most of the variation (92%) and also had high predictive power for the same individuals over time (69%) as well as between study populations (74%). 6. The high predictive ability of the approach suggests that it can help increase our understanding of the drivers of migration and could provide key quantitative information for understanding and managing a broad range of migratory species.

Laboratory semen assessment and prediction of fertility: still utopia?

Abstract: Finding a laboratory test reliable enough to predict the potential fertility of a given semen sample or a given sire for artificial insemination (AI) is still considered utopian, as indicated by the modest correlations seen between results obtained in vitro and field fertility. Male fertility is complex, and depends upon a heterogeneous population of spermatozoa interacting at various levels of the female genital tract, the vestments of the oocyte, and the oocyte itself. For this reason, laboratory assessment of semen must include the testing of most sperm attributes relevant for fertilization and embryo development, not only in individual spermatozoa but within a large sperm population as well. Strategies for the discovery of in vitro predictors of semen fertility require evaluations of low sperm doses for AI, so that differences in innate in vivo fertility can be accurately detected.

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe

Abstract: Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non-crop habitats, and species’ dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7- and 1.4-fold respectively. Arable-dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield-enhancing ecosystem services.

Air temperature triggers the recovery of evergreen boreal forest photosynthesis in spring

Abstract: The timing of the commencement of photosynthesis (P-*) in spring is an important determinant of growing-season length and thus of the productivity of boreal forests. Although controlled experiments have shed light on environmental mechanisms triggering release from photoinhibition after winter, quantitative research for trees growing naturally in the field is scarce. In this study, we investigated the environmental cues initiating the spring recovery of boreal coniferous forest ecosystems under field conditions. We used meteorological data and above-canopy eddy covariance measurements of the net ecosystem CO2 exchange (NEE) from five field stations located in northern and southern Finland, northern and southern Sweden, and central Siberia. The within- and intersite variability for P-* was large, 30-60 days. Of the different climate variables examined, air temperature emerged as the best predictor for P-* in spring. We also found that 'soil thaw', defined as the time when near-surface soil temperature rapidly increases above 0degreesC, is not a useful criterion for P-*. In one case, photosynthesis commenced 1.5 months before soil temperatures increased significantly above 0degreesC. At most sites, we were able to determine a threshold for air-temperature-related variables, the exceeding of which was required for P-*. A 5-day running-average temperature (T-5) produced the best predictions, but a developmental-stage model (S) utilizing a modified temperature sum concept also worked well. But for both T-5 and S, the threshold values varied from site to site, perhaps reflecting genetic differences among the stands or climate-induced differences in the physiological state of trees in late winter/early spring. Only at the warmest site, in southern Sweden, could we obtain no threshold values for T-5 or S that could predict P-* reliably. This suggests that although air temperature appears to be a good predictor for P-* at high latitudes, there may be no unifying ecophysiological relationship applicable across the entire boreal zone.