Multi-year Data Research Articles

Erratum: “Open-source quality control routine and multi-year power generation data of 175 PV systems” [J. Renewable Sustainable Energy 14, 043501 (2022)

Erratum: “Open-source quality control routine and multi-year power generation data of 175 PV systems” [J. Renewable Sustainable Energy <b>14</b>, 043501 (2022)

Assessing the Accuracy and Consistency of Cropland Products in the Middle Yangtze Plain

With the evolution of remote sensing, more data products concerning cropland distribution are becoming available. However, the accuracy and consistency across all datasets in crucial regions are inherently uncertain. We delved into the Middle Yangtze Plain, a complex and vital agricultural area with relatively high cultivation intensities in China. We used confusion matrices and consistency analysis to compare the accuracy and consistency of four multi-year cropland distribution data products. These include Global Land Analysis &amp; Discovery Cropland Data (GLAD), Annual Global Land Cover (AGLC), the China Land Cover Dataset (CLCD), and China’s Annual Cropland Dataset (CACD). Key findings include the following: GLAD has the highest precision at 96.09%, the CLCD has the highest recall at 98.41%, and AGLC and CACD perform well in achieving a balance between precision and recall, with F1 scores of 90.30% and 90.74%, respectively. In terms of consistency, GLAD and the CLCD show inconsistency at 69.58%. When all four products unanimously classify a pixel as cropland, the identified cropland area closely corresponds to the statistical data reported in the yearbook. The Jianghan Plain holds the majority of cropland in the Middle Yangtze Plain, constituting 50.88%. From 2003 to 2019, the cropland area experienced fluctuating and ascending trends. Shangrao City witnessed the most notable rise in cropland area, with an increase of 323.0 km2, whereas Wuhan City underwent the most substantial decline, amounting to 185.8 km². These findings contribute valuable insights into the precision and consistency of existing cropland distribution products, offering a foundation for further research.

High accuracy prediction of the post-combustion carbon capture process parameters using the Decision Forest approach

This paper investigates the relationships among the important process parameters that impact Post-combustion Carbon Capture (PCC) carbon dioxide (CO2) separation. A better understanding of the complex relationships among those parameters can support optimization and performance enhancement of the separation process. Being able to precisely predict the process parameters will enable the operator to determine the current state of the process, forecast any potential changes or events, and adjust process parameters to enhance the plant's performance. With the objective of studying the process parameters' correlations in the amine-based PCC process, we modeled the multi-year historical production data of the Clean Energy Technologies Research Institute (CETRi) (formerly known as the International Test Center for PCC or ITC) in Regina, Saskatchewan, Canada, using a Decision Forest approach. The model validation process revealed that the Decision Forest model produced higher predictive accuracy than previous efforts. The Decision Forest models we developed also represent knowledge about the importance of parameters involved in the capture process, and such knowledge is useful for further optimization of the capture process in the future.

The Variation in the Water Level of Lake Baikal and Its Relationship with the Inflow and Outflow

Lake Baikal is the largest freshwater lake in the world, accounting for about 20% of the world’s fresh surface water. The lake’s outflow to the ocean occurs only via the Angara River, which has several hydroelectric power plants (HPPs) along its watercourse. The first such HPP, Irkutsk HPP, was built in 1956 and is located 60 km from the Angara River’s source. After two years, the backwater from this HPP expanded to the lake shores and began raising the Baikal Lake level. Currently, there is a dynamic balance between the new lake level, the lake inflow from its tributaries, and the Angara River discharge through the Irkutsk HPP. However, both the Angara River discharge and the Baikal Lake level were distorted by the HPP construction. Thus, to understand the changes to the lake basin over the past century, we first needed to estimate naturalized lake levels that would be if no HPP was ever built. This was an important task that allowed (a) the actual impact of global changes on the regional hydrological processes to be estimated and (b) better management of the HPP itself to be provided through future changes. With these objectives in mind, we accumulated multi-year data on the observed levels of Lake Baikal, and components of its water budget (discharge of main tributaries and the Angara River, precipitation, and evaporation). Thereafter, we assessed the temporal patterns and degree of coupling of multi-year and intra-annual changes in the lake’s monthly, seasonal, and annual characteristics. The reconstruction of the average monthly levels of Lake Baikal and the Angara River water discharge after the construction of the Irkutsk HPP was based on the relationship of the fluctuations with the components of the Lake water budget before regulation. As a result, 123-year time series of “conditionally natural” levels of Lake Baikal and the Angara River discharge were reconstructed and statistically analyzed. Our results indicated high inertia in the fluctuations in the lake level. Additionally, we found a century-long tendency of increases in the lake level of about 15 cm per 100 years, and we quantified the low-frequency changes in Lake Baikal’s water levels, the discharge of the Angara River, and the main lake tributaries. An assessment of the impact of the Irkutsk HPP on the multi-year and intra-annual changes in the Lake Baikal water level and the Angara River discharge showed that the restrictions on the discharge through the HPP and the legislative limitations of the Lake Baikal level regime have considerably limited the fluctuations in the lake level. These fluctuations can lead to regulation violations and adverse regimes during low-water or high-water periods.

Demography and threats to population growth of Cirsium pitcheri, a threatened dune plant, in Wisconsin.

Multi-year and multi-site demographic data for rare plants allow researchers to observe threats and project population growth rates and thus long-term persistence of the species, generating knowledge, which allows for effective conservation planning. Demographic studies across more than a decade are extremely rare but allow for the effects of threats to be observed and assessed within the context of interannual environmental variation. We collected demographic data on the Threatened plant Cirsium pitcheri in two sites from 2011-2022. These sites were chosen because one exhibited the presence of non-native seed predators while the other did not, and we hypothesized that we would see declines and potentially extinction of the population threatened by predation. Over the course of our study, we observed additional threats, such as human trampling and high lake levels, which led to significant erosion, sand burial, and storm damage to plants. We find high interannual variation in vital rates and population growth rates for both populations, which mask the overall effects of predation. We observed dramatic declines in plant survivorship and population growth rates in both sites in the years with high lake levels. We conclude that high lake levels, which are expected to become more frequent with climate change, pose a significant threat to all near-shore populations of C. pitcheri.

Mangrove tree height growth monitoring from multi-temporal UAV-LiDAR

Quantifying the mangrove height growth rate is important for understanding mangrove growth as well as its coupling with the other ecosystems and the climate. However, research on this topic has been limited due to the lack of multi-temporal data on mangrove tree height (TH) and methods for tree-level analysis. This study investigates the use of multi-year UAV-LiDAR data for mangrove TH growth characterization. We evaluated the UAV-LiDAR data by comparing it with field measured THs, observing a deviation ranging between −9 and +11 cm. Notably, the deviation was minimal at only 1 cm when comparing datasets collected using the same LiDAR sensor, indicating the validity of adopting multi-year UAV-LiDAR data for mangrove TH growth analysis. Methodologically, we assessed a tree-based approach and a grid-based approach. The tree-based approach is considered more feasible as it mirrors field measurements, allowing for direct comparisons with field surveys. In addition, statistically significant differences were revealed in TH growth rates among mangrove species and clumpiness groups (p < 0.001), while the invasion of Spartina alterniflora did not significantly affect the growth rates. This paper presents the inaugural effort in mangrove TH growth quantification using multi-temporal UAV-LiDAR data, showcasing the potential of this quickly emerging remote sensing technique in individual mangrove change analysis. We proposed a recommended framework for UAV-LiDAR-based TH growth rate measurement. The limitations and uncertainties embedded in the data sources, methodology, and results interpretation were also discussed.

Characterization of the natural resource potential of the agricultural zone of the Krasnoyarsk territory

The aim of the study was to determine the natural resource potential of the agricultural territories in the agricultural regions of the Krasnoyarsk Territory and to investigate the fundamental characteristics of climatic conditions. Location and time of the study. The study utilized multi-year data (from 1978 to 2020) from 22 meteorological stations located in the natural districts of the Krasnoyarsk Territory to analyze climatic conditions. Methods. A georesource database was used to assess the natural resource potential (NRP), including information about soils, agroclimatic parameters, and their impact on agricultural crops. Soils and climatic parameters were ranked on a scale of 5 to 100. The NRP assessment was categorized as follows (points): 1–20 – low; 21–40 – below average; 41–60 – average; 61–80 – above average; 81–100 – high. Climatic conditions were analyzed based on multi-year data from meteorological stations in different natural regions of the Krasnoyarsk Territory, using trend analysis and data smoothing methods to identify dynamics. Results. The natural resource potential values vary from 32.5 points for the northern forest-steppe podzolic soils in the Kansk Natural District to 62.5 points for chernozems (black soils) in the northern forest-steppe of the South Minusinsk Natural District. Weighted average NRP values for the agricultural territories of the Krasnoyarsk Krai increase in the following sequence (points): subtaiga (38.0) – Kansk Natural District (45.4) –Krasnoyarsk Natural District (46.3) – Achinsk-Bogotol Natural District (47.4) – Chulymo-Yenisei Natural District (47.8) – Nazarovo Natural District (49.4) – South Minusinsk Natural District (54.3). Conclusions. Climate warming, accompanied by significant increases in summer and winter precipitation, milder winters, and prolonged growing seasons favorable for agricultural crops and varieties, will have a positive impact on the NRP of the region's agrolandscapes, promoting the development of commercial agriculture, especially in the forest-steppe zone. The range of agricultural crops and varieties may expand. Cultivating winter and hard wheat varieties is expected to become more effective. Improved natural conditions will contribute to bringing long abandoned lands into agricultural production. Changes in soil regimes and properties will lead to the transformation of agricultural crop cultivation technologies.

Which EU Country Contributes Most to GHG Emissions in the LULUCF Sector Relative to Population and GDP?

Abstract In pursuit of climate neutrality, EU nations must collectively address the problem of greenhouse gas (GHG) emissions and air pollutants, which necessitates equitable economic strategies. However, the heterogeneous economic, social, and geographical profiles present hurdles in enacting a cohesive policy framework and realizing shared goals. Land use, land use change and forestry (LULUCF) sector play a crucial role in achieving the EU 2050 climate neutrality goal, as LULUCF is both a source and a sink for GHG emissions, it provides products like wood and biomass that help to reduce emissions in other sectors. This paper aims to compare GHG emissions of different EU countries by using targeted indicators related to per capita and to GDP per capita to enhance the analysis. The results reveal substantial differences in emissions in relation to population and GDP per capita between selected EU countries, even among countries with similar profiles, such as Estonia, Latvia, Lithuania. Notably, countries with lower GDP per capita and smaller population tend to have higher emission values, suggesting less efficiency in managing land use and forestry. The study highlights the need for multi-year data analysis to identify trends in emissions and removals within the LULUCF sector, considering the impacts of natural disasters and economic activities such as bark beetle outbreak or wood harvesting.

Where, when, how and what seagrass to transplant for long lasting results in transitional water systems: the cases of Cymodocea nodosa, Zostera marina, Zostera noltei and Ruppia cirrhosa

Seagrasses play a vital role in marine ecosystems worldwide. However, until recently these ecosystems were experiencing declines due to various global and local threats. In response to this issue, initiatives have been launched to combat seagrass loss by addressing local and regional major stressors and actively engaging in restoration efforts by transplantation. Although seagrass restoration has progressed significantly with the development of numerous transplant techniques, these are not always crowned with success. This is often due to the fact that the environmental parameters of water, sediment and biota of the recipient sites are not carefully considered in their suitability for transplantation. In this study, the multi-year experiences and data from numerous environmental surveys in transitional water systems have been condensed to define limit values for the ideal growth conditions and the extreme values in which the survival of four aquatic angiosperm species is possible: Cymodocea nodosa, Zostera marina, Zostera noltei and Ruppia cirrhosa. Approaches to transplants, seasonality and critical issues have been explored. The identified limits and parameters of water, sediment and biota will help to define the suitability of a recipient site for the rooting of seagrasses, increasing the chances of success for transplant operations.

HOW SPOUSAL BEREAVEMENT SHAPES LIFE SATISFACTION: STABILITY AND CHANGE ACROSS HISTORICAL TIME

Abstract Lifespan psychological and life course sociological research have long shown that spousal bereavement constitutes one of the most stressful life events in older adulthood that is often associated with marked declines in well-being. It is an open question though whether and how the well-being implications of spousal loss have changed over the past decades. To do so, we used multi-year within-person longitudinal change data from 2,042 participants (Mage at event =65.73 years, 71% women) of the German Socio-Economic Panel obtained annually since 1984. We combine latent basis growth models with methods that analyze the Area under the Curve so as to consider the time window from five years prior to five years after spousal loss. Results revealed that having lost one’s spouse in the 2000s and 2010s is associated with overall less well-being declines than having lost one’s spouse in the 1980s and 1990s. Building on earlier approaches that have distinguished anticipation, reaction, and adaptation phases of bereavement revealed that such improvements are primarily driven by fewer declines in the anticipation phase and faster recovery in the adaptation phases (both by about 0.1 SD per 10 years of historical time), whereas we found partial evidence for steeper declines in the immediate reaction phase. We discuss and in part examine possible explanatory factors at the individual, spousal, social, and societal level for the observed historical improvements in life satisfaction trajectories surrounding spousal loss in Germany over the last three decades.

Open‐source photovoltaic model pipeline validation against well‐characterized system data

AbstractAll freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.

“Firefly” of the Submarine Mountains: New Data on Physiculus cynodon (Moridae, Teleostei) from Emperor Seamounts and Northwestern Hawaiian Ridge

Physiculus cynodon is a member of the Moridae family and possesses a ventral bioluminescent organ. Although it has been captured by commercial vessels for decades, our understanding of its biology and ecology remains fragmented. This paper provides data on the species’ spatial and vertical distributions; age and growth; size, age, sex compositions; and sex ratio in the waters around the Emperor Seamounts and the northwestern Hawaiian Ridge. This information is based on the analysis of multi-year Russian data obtained from scientific surveys and observations on commercial fishing vessels. The northernmost capture of this species has been recorded at Nintoku Seamount. Additionally, this species was regularly encountered at depths ranging from 53 to 900 m on seamounts such as Lira (Annei), Koko, Milwaukee (Yuryaku and Kammu), Colahan, and C-H of the Emperor Seamounts and Hancock, Zapadnaya, and Academician Berg of the northwestern Hawaiian Ridge. Catch rates of P. cynodon gradually decreased in a southeastern direction. Notably, the relative abundance of this species in bottom trawl catches significantly surpasses that in pelagic catches. The age of the fish in the catch varied from 9 to 37 years, and its growth is described by the VBGF equation with the following coefficients: L∞ = 858.6, k = 0.030, t0 = 3.5. While the growth patterns for males and females were similar, it is worth mentioning that males rarely survive beyond the age of 25 years.

The importance of capturing power system operational details in resource adequacy assessments

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. In this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system’s RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

Benzo(a)Pyrene in PM10 - Air Monitoring Results in Poland

Abstract Benzo(a)pyrene (B(a)P) is an extremely toxic substance from the group of PAHs (polycyclic aromatic hydrocarbons). These compounds are formed mainly during combustion processes, and they are transported on the surfaces of suspended aerosol in the air. In Poland, both the concentration of suspended dusts and the amount of B(a)P are among the highest in Europe. The aim of the research was to compare levels of B(a)P concentrations in various locations in Poland. Based on multi-year data, coming from the period 2009-2019, linear trends in changes of these levels were determined with the least squares method. The annual courses of B(a)P concentrations in the air show clear seasonal variations. The highest concentrations are observed in the autumn-winter months, the lowest in the spring-summer months. The annual courses of B(a)P/PM10 ratio show clear seasonal variations. This ratio allows to evaluate the content of B(a)P in PM10 particles, expressed in ngB(a)P/μgPM10. The highest ratio values are observed in the autumn-winter months, the lowest ones in the spring-summer months. At most air monitoring stations, the assigned B(a)P concentration trend lines show a weak decline.

Spatiotemporal Variability of Urban Air Pollution in Bucharest City

Urban air pollution is one of the major challenges that cities around the world face. Particulate matter (PM), nitrogen dioxide (NO2), volatile organic compounds (VOCs), and other pollutants are many times over the recommended airborne exposure, generating a strong impact on human health and city well-being. Considering Bucharest as a case study, this study aimed to investigate the patterns of particulate matter and nitrogen dioxide concentrations. Multiyear data from the Romanian National Air Quality Monitoring Network were used to investigate spatial and temporal variability. All air pollutants presented a typical bimodal trend during the day, with specific double peaks corresponding to the morning rush hours and nighttime. Spatial variability in NO2 concentrations was observed, with almost double the concentration values in the city center during midday compared with those for the background and industrial areas. A weekly pattern of PM was noticed, with lower concentrations during the weekends in comparison with those during weekdays, more pronounced in the case of PM10 compared with the case of PM2.5. The fine particle fraction presented monthly and seasonal variability, with higher levels during the cold months compared with the warm months, mainly corresponding to the increased household heating. The estimated proportion of mortality attributable to annual exposure to an air PM2.5 above 5 μg/m3 in Bucharest ranged between 7.55% and 8.26%, with the maximum from 2021. By contrast, the estimated proportion of mortality attributable to PM10 and NO2 above 10 μg/m3 was significantly lower, with values around 4%. The results are useful in supporting environmental planning measures to decrease urban air pollution.

Abandoned cropland compensates the decrease in net ecosystem productivity of impervious surface expansion in China

Abandoned cropland and impervious surface expansion are generally considered to have positive and negative impacts on net ecosystem productivity (NEP), respectively. However, the comprehensive comparison of the impacts of these two land use changes on NEP remains lacking. We use multi-year land cover data, NEP data, and statistical data to track the interannual variability of abandoned cropland and impervious surface expansion in China, and subsequently estimate their impacts on NEP. From 2000 to 2019, 30.8 × 106 ha of cropland in China was abandoned, while the impervious surface area expanded by 8.97 × 106 ha over the period. The average annual abandonment rate and impervious surface expansion rate were 0.83% and 2.96%, respectively. The average annual NEP of abandoned cropland and impervious surface expansion were 39.9 g C/m2 and 16.2 g C/m2, respectively. Using the space-for-time method to estimate NEP changes, results showed that the carbon sink of 0.013 Tg C accumulated by abandoned cropland not only offset the carbon source of 0.01 Tg C from impervious surface expansion but sequestered additional 0.003 Tg C during the study period. Further analysis of the relationships between NEP and natural and anthropogenic factors revealed that temperature had the most significant positive impact on NEP (0.35, p < 0.01), while the urbanization rate had the most significant negative impact on NEP (−0.33, p < 0.01). This study provides a new insight for regulating the effects of land use changes on natural carbon sink/source, and highlights the importance of abandoned cropland to enhancing natural carbon sink.

Contemporary community composition, spatial distribution patterns, and biodiversity characteristics of zooplankton in large alpine Lake Sevan, Armenia

We studied the quantitative composition, spatial distribution, and temporal dynamics of the zooplankton community of the alpine Lake Sevan, Armenia, the largest surface water in the Caucasus region. This article is providing a long-term information and fills the research gap of multiyear data on zooplankton, as the previous research on zooplankton provided only snapshots of the community, and a consistent assessment over multiple years was missing. However, an initial mini-review of historical studies indicated that zooplankton biomass and fish abundance were undergoing large fluctuations, indicating the importance of top-down control. We analysed 239 samples from the period 2016-2019 from 32 sampling sites in Lake Sevan and recorded 37 species of meso- and macrozooplankton (Rotifers, Copepods, Cladocera). Biomass fluctuations were high with peaking biomasses in 2016 and lowest biomasses in 2018, yearly averaged biomass varied about one order of magnitude. Variability over time was hence much higher than spatial variability. The pelagic habitat at the deepest part of the lake showed the highest diversity and biomasses but contrasts between sampling sites remained smaller than changes from year to year or seasonally. Many samples were dominated by a single species, and these key species explain observed biomass dynamics to a wide extent. We applied hierarchical clustering in order to identify phenological groups that appear to show similar patterns of occurrence. This clustering resulted in 6 groups where of 5 groups just consisting of one single species and these 5 key species were the Cladocerans Daphnia magna, Daphnia hyalina, Diaphanosoma sp. as well as the calanoids Arctodiaptomus bacillifer and Acanthodiaptomus denticornis. The most important species in Lake Sevan’s zooplankton during the observation period was D. magna, which reached high biomasses in 2016 and 2017 but then suddenly almost disappeared in 2018 and 2019. When there were more D. magna present, the water became clearer, which was measured using Secchi depth. This shows that these large water fleas effectively controlled the amount of phytoplankton in the water. Daphnia magna, in turn, managed to dominate zooplankton community only during times of extremely low fish biomass indicating strong top-down control of this large Cladoceran by fish. Both observations together imply a strong trophic linkage between fish, zooplankton, and phytoplankton and provide evidence for trophic cascades in Lake Sevan. Besides the novel insights into zooplankton community dynamics of this unique lake of high socio-economical, cultural, and ecological importance, our study also points to potential management opportunities for eutrophication control by biomanipulation, as well as our investigation allows us to conclude that probably biotic factors were more important than abiotic factors in explaining the observed changes and dynamics within the plankton community.

Sources and long-term variability of carbon monoxide at Mount Kenya and in Nairobi

Abstract. Carbon monoxide (CO) concentrations in the troposphere are decreasing globally, with Africa as an exception. Yet, the region is understudied, with a deficit of ground-based observations and highly uncertain CO emission inventories. This paper reports multiyear observational CO data from the Mt. Kenya Global Atmosphere Watch (GAW) station, as well as summertime CO isotope observations from both Mt. Kenya and Nairobi, Kenya. The CO variability at Mt. Kenya is characterized by slightly increased concentrations during dry periods and a strong influence of short-term pollution events. While some data gaps and differences in instrumentation complicate decadal-scale trend analysis, a small long-term increase is resolved. High-pollution events are consistent with isotopic signal from downwind savanna fires. The isotope fingerprint of CO in Nairobi indicates an overwhelming dominance (near 100 %) of primary emissions from fossil fuel combustion with implications for air pollution policy. In contrast, the isotope signature of CO intercepted at the large-footprint Mt. Kenya region suggests that at least 70 % is primary sourced, with a predominance likely from savanna fires in Africa. Taken together, this study provides quantitative constraints of primary vs. secondary CO in the eastern Africa region and in urban Nairobi, with implications for satellite-based emission inventories as well as for chemical transport and climate modeling.

Model-based prediction of a vacant summer niche in a subarctic urbanscape: A multi-year open access data analysis of a ‘niche swap’ by short-billed Gulls

Gulls belong to the seabird group, and are widely considered to be useful ecological indicators. Increasing urbanization throughout the Anthropocene has led to the rise of the urban landscape (‘urbanscape’) as a globally dominant habitat. Though historically less developed, similar urbanization patterns are emerging in the boreal forest, the world's largest forest ecoregion. Here we evaluate the ecological position of migratory Short-billed Gulls (Larus canus) in a subarctic urbanscape. We attempt to investigate a summer niche swap theory, in which gulls annually fill a vacant niche otherwise occupied by common ravens in winter. For that investigation we conducted seasonal plot surveys for Short-billed Gull presence from 2013 to 2016 in the Fairbanks, AK municipality. All data were made publicly available. We compiled them in a open source and ESRI geographic information system (GIS) platform and then added 68 open-access predictor layers, including socio-economic U.S. Census data. We trained, tested, and evaluated the performance of an ensemble of machine learning models, resulting in predictions of gull-abundance hotspots and coldspots, at 100-m resolution for inference. We find that Short-billed Gulls prefer the synergy of industrial areas near man-made water bodies, impervious surfaces, gravel pits, strip malls, transfer sites (garbage dumps) and some young forest vegetation. This study is a first-known attempt to utilize a blended ‘Big Data’ approach, in combination with traditional multi-year field-based data collection and alternative model assessments, in order to characterize an urban seabird niche. Our findings, and the digital infrastructure herein, provide an interdisciplinary baseline for potential applications in urban planning and monitoring the spread of disease reservoirs.

Bathymetric segregation among demersal benthos and its contributions to the differences in the bycatches on bottom fisheries in the Emperor Seamounts area, Northwestern Pacific Ocean

The need for the management of commercially targeted species and surrounding ecosystems has become more apparent in conjunction with the thriving commercial exploration of open seas. Despite the growing global interest in how fishing activity impacts seamount ecosystems, data regarding to the fishing impacts of gillnets on seamount ecosystems are scarce, and quantitative comparisons between trawls and gillnets are surprisingly limited. Our quantitative comparative studies using observer data collected at the southern Emperor Seamounts area revealed that the quantity and quality of bycatches of four key demersal benthos, denoted as Vulnerable marine ecosystem (VME) indicator taxa designated in the convention text of The North Pacific Fisheries Commission (three orders of dominant corals, Antipatharia, Scleractinia, and “Gorgonian” (Alcyonacea with solid axis), and Porifera), were not inherently different between the gear types, and operational tactics, such as depth or positions, might be prior factors largely affecting bycatches of benthic assemblages in the fishing activities carried out at Emperor Seamounts. Additionally, assessments of multiyear operational data revealed temporal shifts in the species composition of cold-water coral bycatches. Overall, the synthesis of bycatch occasions provided by scientific observers enabled us to reveal (1) the variations in bathymetric distributions and the contribution of local topographies toward demersal benthic organisms and (2) fishing operational features, such as operation positions and depth, which may strongly affect bycatches.