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Questions: Field-based ecosystem mapping is prone to observer bias, typically resulting in a mismatch between maps made by different mappers, that is, inconsistency. Experimental studies testing the influence of site, mapping scale, and differences in experience level on inconsistency in field-based ecosystem mapping are lacking. Here, we study how inconsistencies in field-based ecosystem maps depend on these factors. Location: Iškoras and Guollemuorsuolu, northeastern Norway, and Landsvik and Lygra, western Norway. Methods: In a balanced experiment, four sites were field-mapped wall-to- wall to scales 1:5000 and 1:20,000 by 12 mappers, representing three experience levels. Thematic inconsistency was calculated by overlay analysis of map pairs from the same site, mapped to the same scale. We tested for significant differences between sites, scales, and experience-level groups. Principal components analysis was used in an analysis of additional map inconsistencies and their relationships with site, scale and differences in experience level and time consumption were analysed with redundancy analysis. Results: On average, thematic inconsistency was 51%. The most important predictor for thematic inconsistency, and for all map inconsistencies, was site. Scale and its interaction with site predicted map inconsistencies, but only the latter were important for thematic inconsistency. The only experience-level group that differed significantly from the mean thematic inconsistency was that of the most experienced mappers, with nine percentage points. Experience had no significant effect on map inconsistency as a whole. Conclusion: Thematic inconsistency was high for all but the dominant thematic units, with potentially adverse consequences for mapping ecosystems that are fragmented or have low coverage. Interactions between site and mapping system properties are considered the main reasons why no relationships between scale and thematic inconsistency were observed. More controlled experiments are needed to quantify the effect of other factors on inconsistency in field-based mapping. classification, experience, field-based mapping, GIS, inter-observer variation, land-cover mapping, landscape metrics, ordination, scale, vegetation mapping

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using “convection-permitting” models to produce reliable climate change information over the Fenno-Scandinavian region.

The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modeling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behavior of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (October–March), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensembles exhibited improved performance compared to their forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher-resolution regional climate simulations. The CMIP6 ensemble displayed a similar behavior to CMIP5, but reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angola Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic processes that take place. Improvements in observational networks (both in situ and satellite) as well as continued advancements in high-resolution modeling will be critical, in order to develop a robust assessment of climate change for southern Africa.

The continuous change in observed key indicators such as increasing nitrogen deposition, temperatures and precipitation will have marked but uncertain consequences for the ecosystem carbon (C) sink-source functioning of the Arctic. Here, we use multiple in-situ data streams measured by the Greenland Ecosystem Monitoring programme in tight connection with the Soil-Plant-Atmosphere model and climate projections from the high-resolution HIRHAM5 regional model. We apply this modelling framework with focus on two climatically different tundra sites in Greenland (Zackenberg and Kobbefjord) to assess how sensitive the net C uptake will expectedly be under warmer and wetter conditions across the 21st century and pin down the relative contribution to the overall C sink strength from climate versus plant trait variability. Our results suggest that temperatures (5–7.7 °C), total precipitation (19–110 %) and vapour pressure deficit will increase (32–36 %), while shortwave radiation will decline (6–9 %) at both sites by 2100 under the RCP8.5 scenario. Such a combined effect will, on average, intensify the net C uptake by 9–10 g C m−2 year−1 at both sites towards the end of 2100, but Zackenberg is expected to have more than twice the C sink strength capacity of Kobbefjord. Our sensitivity analysis not only reveals that plant traits are the most sensitive parameters controlling the net C exchange in both sites at the beginning and end of the century, but also that the projected increase in the net C uptake will likely be similarly influenced by future changes in climate and existing local nutrient conditions. A series of experiments forcing realistic changes in plant nitrogen status at both sites corroborates this hypothesis. This work proves the unique synergy between monitoring data and numerical models to assist robust model calibration/validation and narrow uncertainty ranges and ultimately produce more reliable C cycle projections in understudied regions such as Greenland.

Ensemble methods are remarkably powerful for quantifying geological uncertainty. However, the use of the ensemble of reservoir models for robust optimization (RO) can be computationally demanding. The straightforward computation of the expected net present value (NPV) requires many expensive simulations. To reduce the computational burden without sacrificing accuracy, we present a fast and effective approach that requires only simulation of the mean reservoir model with a bias correction factor. Information from distinct controls and model realizations can be used to estimate bias for different controls. The effectiveness of various bias-correction methods and a linear or quadratic approximation is illustrated by two applications: flow optimization in a one-dimensional model and the drilling-order problem in a synthetic field model. The results show that the approximation of the expected NPV from the mean model is significantly improved by estimating the bias correction factor, and that RO with mean model bias correction is superior to both RO performed using a Taylor series representation of uncertainty and deterministic optimization from a single realization. Use of the bias-corrected mean model to account for model uncertainty allows the application of fairly general optimization methods. In this paper, we apply a nonparametric online learning methodology (learned heuristic search) for efficiently computing an optimal or near-optimal robust drilling sequence on the REEK Field example. This methodology can be used either to optimize a complete drilling sequence or to optimize only the first few wells at a reduced cost by limiting the search depths.

The study describes the depositional development and sediment partitioning in a prograding paralic Triassic succession. The deposits are associated with the advance of large prism‐scale clinoforms across a shallower platform area. Approaching the platform, the limited accommodation and associated relative higher rates of deposition generated straighter clinoforms with lower foreset angles. The vertical restriction across the platform is interpreted to have amplified the tidal signature. Sediment was redistributed from the coast into increasingly sandy delta‐front deposits, compared to offshore equivalents. The deposits comprise extensive compound dune fields of amalgamated and increasingly clean sandbodies up‐section. Rapid deposition of significant amounts of sand led to differential subsidence and growth‐faulting in the delta front, with downthrown fault blocks further amplifying the tidal energy through funnelling. A mixed‐energy environment created along‐strike variability along the delta front with sedimentation governing process‐regime. Areas of lower sedimentation were reworked by wave and storm‐action, whereas high sedimentation rates preserved fluvially dominated mouth bars. A major transgression, however, favoured tidally dominated deposits also in these areas, attributed to increasing rugosity of the coastline. Formation of an extensive subaqueous platform between the coast and delta front dampened incoming wave energy, and tidally dominated deposits dominate the near‐shore successions. Meanwhile formation of wave‐built sand‐bars atop the platform attest to continued wave influence. The strong tidal regime led to the development of a heterolithic near‐shore tidally dominated channel system, and sandier fluvial channels up‐river. The highly meandering tidal channels incising the subaqueous platform form kilometre wide successions of inclined heterolithic stratification. The fluvially dominated channels which govern deposition on the delta plain are narrower and slightly less deep, straighter, generally symmetric and filled with cleaner sands. This study provides important insight into tidal amplification and sand redistribution during shallowing on a wide shelf, along with along‐strike process‐regime variability resulting from variations in sediment influx. © 2020 The Authors. Basin Research published by International Association of Sedimentologists and European Association of Geoscientists and Engineers and John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Large population increases of Arctic-breeding waterfowls over recent decades have intensified the conflict with agricultural interests in both Eurasia and North America. In the spring-staging region Vesterålen in sub-Arctic Norway, sheep, dairy and meat farmers have reported reduced agricultural grassland yields due to pink-footed geese Anser brachyrhynchus and barnacle geese Branta leucopsis that rest and forage in the region for 3-4 weeks in spring on their way to their breeding grounds on Svalbard. Here, we report from an experimental exclosure design where goose access to plots at three grassland fields in Vesterålen was prevented. The experiment was conducted over 3 years between 2012 and 2014. Goose abundance varied greatly between fields and years as a function of variable spring weather and forage quantity, facilitating evaluation of longer-term impacts under contrasting grazing intensities. First and second harvest yields across fields and years were 20% and 19% higher in exclosures than in plots open for grazing, while total yields (sum of first and second harvests) were on average 27% higher. Within-year effects on harvest yields varied substantially, primarily due to highly contrasting sward development during the spring-staging periods. Cool weather (2012) led to slow sward development and little or no effects on harvest yields, warmer weather (2013) resulted in generally large effects, while variable weather (2014) led to treatment effects varying across fields, with one field experiencing 61% higher yields in exclosures while there were no significant impacts on first-harvest yields at the two other fields. Goose grazing did not increase dry weight-based proportions of weeds. Overall, the farmers' reports on yield-loss due to goose grazing were confirmed, although impacts varied substantially between years. A novel finding is that second-harvest yields were also reduced. For the most affected farmers, it is unlikely that the current subsidy scheme is sufficient to cover all the their losses.