Optimizing Models of the North Atlantic Spring Bloom Using Physical, Chemical and Bio-Optical Observations from a Lagrangian Float

The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO(2) from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15 %. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is larger by a factor of 2.5 to 4.5 for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has a statistically significant better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

A 170 year spring phenology index of plants in eastern China

Extending phenological records into the past is essential for the understanding of past ecological change and evaluating the effects of climate change on ecosystems. A growing body of historical phenological information is now available for Europe, North America, and Asia. In East Asia, long-term phenological series are still relatively scarce. This study extracted plant phenological observations from old diaries in the period 1834–1962. A spring phenology index (SPI) for the modern period (1963–2009) was defined as the mean flowering time of three shrubs (first flowering of Amygdalus davidiana and Cercis chinensis, 50% of full flowering of Paeonia suffruticosa) according to the data availability. Applying calibrated transfer functions from the modern period to the historical data, we reconstructed a continuous SPI time series across eastern China from 1834 to 2009. In the recent 30 years, the SPI is 2.1–6.3 days earlier than during any other consecutive 30 year period before 1970. A moving linear trend analysis shows that the advancing trend of SPI over the past three decades reaches upward of 4.1 d/decade, which exceeds all previously observed trends in the past 30 year period. In addition, the SPI series correlates significantly with spring (February to April) temperatures in the study area, with an increase in spring temperature of 1°C inducing an earlier SPI by 3.1 days. These shifts of SPI provide important information regarding regional vegetation-climate relationships, and they are helpful to assess long term of climate change impacts on biophysical systems and biodiversity.

Quantitative morphometric analysis of lakes using GIS: rectangularity R , ellipticity E , orientation O , and the rectangularity vs. ellipticity index, REi

Quantitative measures of polygon shapes and orientation are important elements of geospatial analysis. These kinds of measures are particularly valuable in the case of lakes, where shape and orientation patterns can help identifying the geomorphological agents behind lake formation and evolution. However, the lack of built-in tools in commercial geographic information system (GIS) software packages designed for this kind of analysis has meant that many researchers often must rely on tools and workarounds that are not always accurate. Here, an easy-to-use method to measure rectangularity R, ellipticity E, and orientation O is developed. In addition, a new rectangularity vs. ellipticity index, REi, is defined. Following a step-by-step process, it is shown how these measures and index can be easily calculated using a combination of GIS built-in functions. The identification of shapes and estimation of orientations performed by this method is applied to the case study of the geometric and oriented lakes of the Llanos de Moxos, in the Bolivian Amazon, where shape and orientation have been the two most important elements studied to infer possible formation mechanisms. It is shown that, thanks to these new indexes, shape and orientation patterns are unveiled, which would have been hard to identify otherwise.

Spring temperature variability and eutrophication history inferred from sedimentary pigments in the varved sediments of Lake Żabińskie, north-eastern Poland, AD 1907–2008

Varved lake sediments are excellent natural archives providing quantitative insights into climatic and environmental changes at very high resolution and chronological accuracy. However, due to the multitude of responses within lake ecosystems it is often difficult to understand how climate variability interacts with other environmental pressures such as eutrophication, and to attribute observed changes to specific causes. This is particularly challenging during the past 100 years when multiple strong trends are superposed. Here we present a high-resolution multi-proxy record of sedimentary pigments and other biogeochemical data from the varved sediments of Lake Żabińskie (Masurian Lake District, north-eastern Poland, 54°N–22°E, 120 m a.s.l.) spanning AD 1907 to 2008. Lake Żabińskie exhibits biogeochemical varves with highly organic late summer and winter layers separated by white layers of endogenous calcite precipitated in early summer. The aim of our study is to investigate whether climate-driven changes and anthropogenic changes can be separated in a multi-proxy sediment data set, and to explore which sediment proxies are potentially suitable for long quantitative climate reconstructions. We also test if convoluted analytical techniques (e.g. HPLC) can be substituted by rapid scanning techniques (visible reflectance spectroscopy VIS-RS; 380–730 nm). We used principal component analysis and cluster analysis to show that the recent eutrophication of Lake Żabińskie can be discriminated from climate-driven changes for the period AD 1907–2008. The eutrophication signal (PC1 = 46.4%; TOC, TN, TS, Phe-b, high TC/CD ratios total carotenoids/chlorophyll-a derivatives) is mainly expressed as increasing aquatic primary production, increasing hypolimnetic anoxia and a change in the algal community from green algae to blue-green algae. The proxies diagnostic for eutrophication show a smooth positive trend between 1907 and ca 1980 followed by a very rapid increase from ca. 1980 ± 2 onwards. We demonstrate that PC2 (24.4%, Chl-a-related pigments) is not affected by the eutrophication signal, but instead is sensitive to spring (MAM) temperature (r = 0.63, pcorr < 0.05, RMSEP = 0.56 °C; 5-yr filtered). Limnological monitoring data (2011–2013) support this finding. We also demonstrate that scanning visible reflectance spectroscopy (VIS-RS) data can be calibrated to HPLC-measured chloropigment data and be used to infer concentrations of sedimentary Chl-a derivatives {pheophytin a + pyropheophytin a}. This offers the possibility for very high-resolution (multi)millennial-long paleoenvironmental reconstructions.

Spring-summer temperatures reconstructed for northern Switzerland and southwestern Germany from winter rye harvest dates, 1454–1970

This paper presents a unique 517-yr long documentary data-based reconstruction of spring-summer (MAMJJ) temperatures for northern Switzerland and southwestern Germany from 1454 to 1970. It is composed of 25 partial series of winter grain (secale cereale) harvest starting dates (WGHD) that are partly based on harvest related bookkeeping of institutions (hospitals, municipalities), partly on (early) phenological observations. The resulting main Basel WGHD series was homogenised with regard to dating style, data type and altitude. The calibration and verification approach was applied using the homogenous HISTALP temperature series from 1774–1824 for calibration (r = 0.78) and from 1920–1970 for verification (r = 0.75). The latter result even suffers from the weak data base available for 1870– 1950. Temperature reconstructions based on WGHD are more influenced by spring temperatures than those based on grape harvest dates (GHD), because rye in contrast to vines already begins to grow as soon as sunlight brings the plant to above freezing. The earliest and latest harvest dates were checked for consistency with narrative documentary weather reports. Comparisons with other European documentarybased GHD and WGHD temperature reconstructions generally reveal significant correlations decreasing with the distance from Switzerland. The new Basel WGHD series shows better skills in representing highly climate change sensitive variations of Swiss Alpine glaciers than available GHD series.

Parameterization of temperature sensitivity of spring phenology and its application in explaining diverse phenological responses to temperature change

Existing evidence of plant phenological change to temperature increase demonstrates that the phenological responsiveness is greater at warmer locations and in early-season plant species. Explanations of these findings are scarce and not settled. Some studies suggest considering phenology as one functional trait within a plant's life history strategy. In this study, we adapt an existing phenological model to derive a generalized sensitivity in space (SpaceSens) model for calculating temperature sensitivity of spring plant phenophases across species and locations. The SpaceSens model have three parameters, including the temperature at the onset date of phenophases (Tp), base temperature threshold (Tb) and the length of period (L) used to calculate the mean temperature when performing regression analysis between phenology and temperature. A case study on first leaf date of 20 plant species from eastern China shows that the change of Tp and Tb among different species accounts for interspecific difference in temperature sensitivity. Moreover, lower Tp at lower latitude is the main reason why spring phenological responsiveness is greater there. These results suggest that spring phenophases of more responsive, early-season plants (especially in low latitude) will probably continue to diverge from the other late-season plants with temperatures warming in the future.

GIS-Karte des Südsudans gewinnt Kartografie-Preis

Eine vom Centre for Develpment and Environment (CDE) der Universität Bern gestaltete Karte der südsudanesischen Region East Equatoria hat den „New Mapmaker Award 2009“ gewonnen. Der Preis wird gemeinsam von der britischen Kartografiegesellschaft und der amerikanischen National Geographic Society vergeben. Die im Rahmen eines Capacity-Development- Programms für Geoinformationsmanagement entworfene Karte wurde vollumfänglich in ArcMap aufgebaut, ohne Einsatz von Graphiksoftware.

GIS layers on Human-Elephant conflicts in Laikipia District

GIS layers on Human-Elephant conflicts in Laikipia District: aerial counts, wildlife distribution, land-use, Human-Elephant conflicts hotspots and temporal patterns, and conflict deterrence activities

An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

Influence of Surface Oceanographic Variability on Abundance of the Western Winter-Spring Cohort of Neon Flying Squid Ommastrephes Bartramii in the Nw Pacific Ocean

Abundance of the Ommastrephes bartramii winter-spring cohort fluctuated greatly from 1995 to 2004. To understand how abundance was influenced by sea surface conditions, we examined the variations in the proportion of thermal habitats with favourable sea surface temperature (SST). The SST data of both the spawning and feeding grounds were used to calculate the monthly proportion of favourable-SST areas (PFSSTA). Catch per fishing day per fishing boat (catch per unit effort, CPUE) of the Chinese mainland squid-jigging fleet was used as squid abundance index. The relationships between CPUE and monthly PFSSTA at spawning and feeding grounds were analyzed, and the relationship between CPUE and selected PFSSTA was quantified with a multiple linear regression model. Results showed that February PFSSTA at the spawning ground and August to November PFSSTA at the feeding ground could account for about 60% of the variability in O. bartramii abundance between 1995 and 2004, that February was the most important period influencing squid recruitment during the spawning season, and that feeding ground PFSSTA during the fishing season would influence CPUE by causing squid to aggregate. Our forecast model was found to perform well when we compared the model-predicted CPUEs and the average CPUEs observed during August to November in 2005 and 2006 from the Chinese squid-jigging fishery.