Reduction in long-term milk yields represents a notable share of the economic losses caused by bovine mastitis. Efficient, economic, and safe measures to prevent these losses require knowledge of the causal agent of the disease. The aim of this study was to investigate pathogen-specific impacts of mastitis on milk production of dairy cows. The materials consisted of milk and health recording data and microbiological diagnoses of mastitic quarter milk samples of 20,234 Finnish dairy cows during 2010, 2011, and 2012. The 6 most common udder pathogens were included in the study: Staphylococcus aureus, non-aureus staphylococci (NAS), Escherichia coli, Corynebacterium bovis, Streptococcus uberis, and Streptococcus dysgalactiae. We used a 2-level multilevel model to estimate curves for lactations with and without mastitis. The data on lactation periods to be compared were collected from the same cow. To enable comparison among lactations representing diverse parities, the estimated lactation curves were adjusted to describe the cow's third lactation. Mastitis caused by each pathogen resulted in milk production loss. The extent of the reduction depended on the pathogen, the timing of mastitis during lactation, and the type of mastitis (clinical vs. subclinical). The 2 most commonly detected pathogens were NAS and Staph. aureus. Escherichia coli clinical mastitis diagnosed before peak lactation caused the largest loss, 10.6% of the 305-d milk yield (3.5 kg/d). The corresponding loss for Staph. aureus mastitis was 7.1% (2.3 kg/d). In Staph. aureus mastitis diagnosed between 54 and 120 d in milk, the loss was 4.3% (1.4 kg/d). The loss was almost equal in both clinical and subclinical mastitis caused by Staph. aureus. Mastitis caused by Strep. uberis and Strep. dysgalactiae resulted in losses ranging from 3.7% (1.2 kg/d) to 6.6% (2.1 kg/d) depending on type and timing of mastitis. Clinical mastitis caused by the minor pathogens C. bovis and NAS also had a negative effect on milk production: 7.4% (2.4 kg/d) in C. bovis and 5.7% (1.8 kg/d) in NAS when both were diagnosed before peak lactation. In conclusion, minor pathogens should not be underestimated as a cause of milk yield reduction. On single dairy farms, control of E. coli mastitis would bring about a significant increase in milk production. Reducing Staph. aureus mastitis is the greatest challenge for the Finnish dairy sector.

The aim of this study was to determine risk factors for bovine intramammary infection (IMI) associated with the most common bacterial species in Finland. Large databases of the Finnish milk-recording system and results of microbiological analyses of mastitic milk samples from Valio Ltd. (Helsinki, Finland) were analyzed. The study group comprised 29,969 cows with IMI from 4,173 dairy herds. A cow with a quarter milk sample in which DNA of target species was detected in the PathoProof Mastitis PCR Assay (Thermo Fisher Scientific, Waltham, MA) was determined to have IMI. Only cows with IMI caused by the 6 most common pathogens or groups of pathogens, coagulase-negative staphylococci (CNS), Staphylococcus aureus, Streptococcus uberis, Streptococcus dysgalactiae, Corynebacterium bovis, and Escherichia coli, were included. The control group comprised 160,176 IMI-free cows from the same herds as the study group. A multilevel logistic regression model was used to study herd-and cow-specific risk factors for incidence of IMI. Pathogen-specific results confirmed those of earlier studies, specifically that increasing parity increases prevalence of IMI regardless of causative pathogen. Holsteins were more susceptible to IMI than Nordic Reds except when the causative pathogen was CNS. Occurrence of IMI caused by C. bovis was not related to milk yield, in contrast to IMI caused by all other pathogens investigated. Organic milk production was associated with IMI only when the causative pathogen of IMI was Staph. aureus; Staph. aureus IMI was more likely to occur in conventional than in organic production. Cows in older freestall barns with parlor milking had an increased probability of contracting an IMI compared with cows in tiestall barns or in new freestall barns with automatic milking. This was the case for all IMI, except those caused by CNS, the prevalence of which was not associated with the milking system, and IMI caused by Staph. aureus, which was most common in cows housed in tiestall barns. A better breeding index for milk somatic cell count was associated with decreased occurrence of IMI, indicating that breeding for improved udder health has been successful in reducing the incidence of IMI caused by the most common pathogens in Finland. In the Finnish dairy sector, the importance of other measures to control IMI will increase as the Holstein breed progressively takes the place of the Nordic Red breed. Attention should be paid to hygiene and cleanliness, especially in old freestall barns. Based on our results, the increasing prevalence of automatic milking is not a reason for special concern.

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The pipe model approach was compared with foliage biomass models by using the cross-sectional area at the tree crown base for predicting foliage biomass of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). We evaluated the impacts of site type, fertilization, and climate on the relationship between foliage biomass and cross-sectional area at the tree crown base, referred as to the pipe model ratio. Our hypotheses were that (i) the pipe model approach is a more precise and accurate method for foliage prediction than the traditional biomass models and (ii) the pipe model ratio for foliage does not explicitly depend on any single environmental driver. Data used here consisted of felled trees from Finnish and Swedish biomass studies. These data were analyzed by linear mixed models with different covariates, and the uncertainties of different modelling approaches were evaluated. The pipe model outperformed other models for Scots pine but not for Norway spruce. Results showed larger pipe model ratios for Scots pine in herb-rich forests compared with those of trees in subxeric heath forest. Results from fertilized trees indicated that the addition of nitrogen temporarily increased foliage biomass.

This paper applies the concept of cultural ecosystem services (CES) to reveal the diverse benefits the Baltic Sea provides to human well-being. The study identifies and defines relevant CES for marine and coastal environments and applies them in a survey with 4800 respondents from Germany, Finland and Latvia. The relative importance of various CES was determined by asking respondents to allocate 100 points between CES related to recreation, landscape, inspiration, learning and education, spiritual experiences and belonging, historically and culturally important places and the existence of habitats. The results reveal significant differences in the importance of various CES across countries, users and nonusers of the Baltic Sea, as well as respondents with different human–nature relationships. The results emphasize the importance of considering recreation, landscapes and habitats in conservation policies, while acknowledging that all CES are perceived as important by some population groups.Electronic supplementary materialThe online version of this article (10.1007/s13280-019-01239-1) contains supplementary material, which is available to authorized users.

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Ecosystem-based agricultural practices that utilize ecosystem processes aim to either reduce the negative externalities of agricultural production or increase the production of ecosystem services other than food provision. We examined consumer interest in buying and paying for food produced using ecosystem-based agricultural practices. According to the results, the most preferred practices were the more efficient use of livestock manure, the use of nitrogen-fixing crops, biological pest control, and the addition of soil carbon. Having these practices as an attribute of a food product increased the interest in buying the product for 43% of consumers. Their median willingness to pay (WTP) was 20% higher than for conventional products. Using socioeconomic and attitudinal variables, a hurdle model revealed the characteristics of a consumer segment interested in ecosystem-based agricultural practices.