Metrics for quantifying how much different threats contribute to red lists of species and ecosystems

Red lists are a crucial tool for the management of threatened species and ecosystems. Among the information red lists provide, the threats affecting the listed species or ecosystem, such as pollution or hunting, are of special relevance. This information can be used to quantify the relative contribution of different threat factors to biodiversity loss by disaggregating the cumulative extinction risk across species into components that can be attributed to certain threats. We devised and compared 3 metrics that accomplish this and may be used as indicators. The first metric calculates the portion of the temporal change in red list index (RLI) values that is caused by each threat. The second metric attributes the deviation of an RLI value from its reference value to different threats. The third metric uses extinction probabilities that are inferred from red list categories to estimate the contribution of a threat to the expected loss of species or ecosystems within 50 years. We used data from Norwegian Red Lists to test and evaluate these metrics. The first metric captured only a minor portion of the biodiversity loss caused by threats because it ignores species whose red list category does not change. Management authorities will often be interested in the contribution of a given threat to the total deviation from the optimal state. This was measured by the remaining metrics. The second metric was best suited for comparisons across countries or taxonomic groups. The third metric conveyed the same information but uses numbers of species or ecosystem as its unit, which is likely more intuitive to lay people and may be preferred when communicating with stakeholders or the general public.publishedVersio

Psykisk helse som tema i PPU-utdanningen

Nettside: https://psykisk-kommune.no/publishedVersio

Hunting for ecological indicators: are large herbivore skeleton measures from harvest data useful proxies for monitoring?

Hunter-collected data and samples are used as indices of population performance, and monitoring programs often take advantage of such data as ecological indicators. Here, we establish the relationships between measures of skeleton size (lower jawbone length and hind-leg length) and autumn carcass mass of slaughtered individuals of known age and sex of the high Arctic and endemic Svalbard reindeer (Rangifer tarandus platyrhynchus). We assess these relationships using a long-term monitoring dataset derived from hunted or culled reindeer. The two skeleton measures were generally strongly correlated within age class. Both jaw length (R2 = 0.78) and hind-leg length (R2 = 0.74) represented good proxies of carcass mass. These relationships were primarily due to an age effect (i.e. due to growth) as the skeleton measures reached an asymptotic size at 4–6 years of age. Accordingly, strong positive correlations between skeleton measures and carcass mass were mainly evident at the young age classes (range r [0.45–0.84] for calves and yearlings). For the adults, these relationships weakened due to skeletal growth ceasing in mature animals causing increased variance in mass with age—potentially due to the expected substantial impacts of annual environmental fluctuations. As proxies for carcass mass, skeleton measurements should therefore be limited to young individuals. Although body mass is the ‘gold standard’ in monitoring large herbivores, our results indicate that skeleton measures collected by hunters only provide similar valuable information for young age classes, particularly calves and yearlings. In sum, jaw length and hind-leg length function as proxies identical to body mass when documenting the impacts of changing environmental conditions on important state variables for reindeer and other herbivores inhabiting highly variable environments. Arctic · Citizen science · Hunter-collected data · Life history · Terrestrial large herbivoreHunting for ecological indicators: are large herbivore skeleton measures from harvest data useful proxies for monitoring?publishedVersio

Impacts of a warming climate on concentrations of organochlorines in a fasting high arctic marine bird: Direct vs. indirect effects?

The present study examined how climate changes may impact the concentrations of lipophilic organochlorines (OCs) in the blood of fasting High Arctic common eiders (Somateria mollissima) during incubation. Polychlorinated biphenyls (PCBs), 1-dichloro-2,2-bis (p-chlorophenyl) ethylene (p,p′-DDE), hexachlorobenzene (HCB) and four chlordane compounds (oxychlordane, trans-chlordane and trans- and cis-nonachlor) were measured in females at chick hatching (n = 223) over 11 years (2007–2017). Firstly, median HCB and p,p′-DDE concentrations increased ~75 % over the study period, whereas median chlordane concentrations doubled (except for oxychlordane). PCB concentrations, in contrast, remained stable over the study period. Secondly, both body mass and clutch size were negatively associated with OC levels, suggesting that females with high lipid metabolism redistributed more OCs from adipose tissue, and that egg production is an important elimination route for OCs. Thirdly, the direct climate effects were assessed using the mean effective temperature (ET: air temperature and wind speed) during incubation, and we hypothesized that a low ET would increase redistribution of OCs. Contrary to expectation, the ET was positively correlated to most OCs, suggesting that a warmer climate may lead to higher OCs levels, and that the impact of ET may not be direct. Finally, potential indirect impacts were examined using the Arctic Oscillation (AO) in the three preceding winters (AOwinter 1–3) as a proxy for potential long-range transport of OCs, and for local spring climate conditions. In addition, we used chlorophyll a (Chla) as a measure of spring primary production. There were negative associations between AOwinter 1 and HCB, trans-chlordane and trans-nonachlor, whereas oxychlordane and cis-chlordane were negatively associated with Chla. This suggests that potential indirect climate effects on eiders were manifested through the food chain and not through increased long-range transport, although these relationships were relatively weak.Impacts of a warming climate on concentrations of organochlorines in a fasting high arctic marine bird: Direct vs. indirect effects?publishedVersio

Alpha-tocopherol and MRI outcomes in multiple sclerosis - association and prediction

Objective: Alpha-tocopherol is the main vitamin E compound in humans, and has important antioxidative and immunomodulatory properties. The aim of this study was to study alpha-tocopherol concentrations and their relationship to disease activity in Norwegian multiple sclerosis (MS) patients. Methods: Prospective cohort study in 88 relapsing-remitting MS (RRMS) patients, originally included in a randomised placebo-controlled trial of omega-3 fatty acids (the OFAMS study), before and during treatment with interferon beta. The patients were followed for two years with repeated 12 magnetic resonance imaging (MRI) scans and nine serum measurements of alpha-tocopherol. Results: During interferon beta (IFNB) treatment, each 10 µmol/L increase in alpha-tocopherol reduced the odds (CI 95%) for simultaneous new T2 lesions by 36.8 (0.5–59.8) %, p = 0.048, and for combined unique activity by 35.4 (1.6–57.7) %, p = 0.042, in a hierarchical regression model. These associations were not significant prior to IFNB treatment, and were not noticeably changed by gender, age, body mass index, HLA-DRB1*15, treatment group, compliance, or the concentrations of 25-hydroxyvitamin D, retinol, neutralising antibodies against IFNB, or the omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid. The corresponding odds for having new T1 gadolinium enhancing lesions two months later was reduced by 65.4 (16.5–85.7) %, p = 0.019, and for new T2 lesions by 61.0 (12.4–82.6) %, p = 0.023. Conclusion: During treatment with IFNB, increasing serum concentrations of alpha-tocopherol were associated with reduced odds for simultaneous and subsequent MRI disease activity in RRMS patients.publishedVersio

Pastoral Herding Strategies and Governmental Management Objectives: Predation Compensation as a Risk Buffering Strategy in the Saami Reindeer Husbandry

Previously it has been found that an important risk buffering strategy in the Saami reindeer husbandry in Norway is the accumulation of large herds of reindeer as this increases long-term household viability. Nevertheless, few studies have investigated how official policies, such as economic compensation for livestock losses, can influence pastoral strategies. This study investigated the effect of received predation compensation on individual husbandry units’ future herd size. The main finding in this study is that predation compensation had a positive effect on husbandry units’ future herd size. The effect of predation compensation, however, was nonlinear in some years, indicating that predation compensation had a positive effect on future herd size only up to a certain threshold whereby adding additional predation compensation had little effect on future herd size. More importantly, the effect of predation compensation was positive after controlling for reindeer density, indicating that for a given reindeer density husbandry units receiving more predation compensation performed better (measured as the size of future herds) compared to husbandry units receiving less compensation

Forecasting the Nature Index. A comparison of methods

Skarpaas, O. & Pedersen, B. 2012. Forecasting the Nature Index: a comparison of methods - NINA Report 794. 28 pp. The Nature Index (NI) is an aggregate of many biodiversity indicators developed to give an overview of the state and trends of biodiversity. The NI is currently also being considered and implemented for other applications such as monitoring of national ecological sustainability and assessments of local management plans. For these and other applications of the NI, methods for forecasting future trends and responses to pressures and management actions are needed. In this report we discuss the opportunities for systematic forecasting of the NI. Our goal is twofold: First, to provide a basis for decisions regarding forecasting of the NI framework in general and, second, to provide specific advice for forecasting the current implementation of the Nature Index for Norway. The report briefly describes the current NI framework and its implementation in Norway and then discusses alternative forecasting methods in relation to the various purposes of forecasting and the properties of the NI with consequences for forecasting. Finally, a selection of methods is tested using simulated data and real data for forest in Norway. Ideally, we need a framework for forecasting that allows non-linear dynamics and covariates (mechanisms) and can handle missing values and short time series. Multivariate analysis may be necessary for certain applications. Automated forecasts may be necessary when there are many time series, and useful for on-the-fly updates and forecasts online. No forecasting method completely satisfies these requirements. For indicators that are known to follow standard population dynamics models, these models may be the best predictive tools. For certain parameter values the Ricker model may be a useful representation of the aggregated NI. The drawback is that these models must be specifically tailored to each case. Of the generic tools, ARIMA seems to be the most promising, as it includes common population dynamics models as special cases and a method to deal with non-stationarity (differencing), the incorporation of pressures is straightforward, modeling dependence among indicators is possible and procedures for automated model selection and forecasting exist. Our tests on simulated time series and data for forest suggest that ARIMA is the best alternative (considering bias and precision) among formal methods when the underlying dynamics are unknown and the time series are sufficiently long. When the underlying dynamics are known, specific dynamic models may perform better. However, for the current low number of data points in time in the NI (4-5), simple naive forecasts perform better than formal methods. When forecasts are made at the NI level, disregarding individual indicators, the best approach seems to be to extrapolate the current state; linear extrapolation of the trend between the two last observations is better when forecasts are made at the level of individual indicators and then aggregated. KEY WORDS Norway, Nature Index, biodiversity, forecasting, ARIMA, forest, Norge, Naturindeks, biologisk mangfold, framskriving, ARIMA, skogpublishedVersio