Spatio-temporal Mismatches Research Articles

Mapping Spatiotemporal Disparities in Residential Electricity Inequality Using Machine Learning.

The move toward electrification is critical for decarbonizing the energy sector but may exacerbate energy unaffordability without proper safeguards. Addressing this challenge requires capturing neighborhood-scale dynamics to uncover the blind spots in residential electricity inequality. Based on publicly available, multisourced remote sensing and census data, we develop a high-resolution, spatiotemporally explicit machine learning (ML) framework to predict tract-level monthly electricity consumption across the conterminous U.S. from 2013-2020. We then construct the electricity affordability gap (EAG) metric, defined as the gap between electricity bills and 3% of household income, to better identify energy-vulnerable communities over space and time. The results show that our framework largely improves the resolution of electricity consumption data while achieving an R2 of 0.82 compared to the Low-Income Energy Affordability Data (LEAD). We estimate an annual $16.18 billion economic burden on the ability to afford electricity bills, exceeding current federal appropriations in alleviating energy difficulties. We also observe pronounced seasonal and urban-rural disparities, with monthly EAG in summer and winter being 2-3 times greater than other seasons and rural residents facing burdens up to 1.7 times higher than their urban counterparts. These insights inform equitable electrification by addressing spatiotemporal mismatches and multiple jurisdictional challenges in energy justice efforts.

Climate change drives spatiotemporal mismatches between bivalves and mangrove in the Colombian Pacific coast

The Piangua Anadara tuberculosa and Anadara similis are bivalve species thrive among mangrove roots and are crucial for vulnerable human communities, providing both economic and nutritional support. In the Colombian Pacific coast, significant efforts have been directed towards understanding the abundance and population structure of these mangrove bivalves. However, the impact of climate change on the spatiotemporal relationship between the potential distribution of these bivalves and their potential habitat, Rhizophora mangle, remains underexplored. We developed distinct Ecological Niche Models (ENMs) for both bivalve species and their potential habitat based on species presence-pseudo-absence data, soil physicochemical attributes, and bioclimatic variables projected for the present and future in the Colombian Pacific coast. The projections for 2030 and 2050 were formulated using the optimistic (Shared Socioeconomic Pathways –SSP1), intermediate (SSP2), and pessimistic (SSP5) climate change scenarios as proposed by the Intergovernmental Panel on Climate Change (IPCC) in its sixth report. Currently, there is a significant correlation between the potential distribution of the Piangua species and the mangroves on the Colombian Pacific coast. However, this relationship is expected to undergo spatiotemporal changes due to future climate shifts, especially by 2050 under the most pessimistic climate scenario (SSP5). Our findings offer valuable insights for the management and conservation of both the Piangua and the mangroves in the Colombian Pacific coast. Conservation efforts for the Piangua species should prioritize areas that are likely to remain suitable for both the species and its associated habitat, the mangroves.

Long-term planning and coupling optimization of multi-regional natural gas and hydrogen supply systems: A case study of China

Low-carbon transition of energy systems features more natural gas and hydrogen consumption to replace coal and oil. Planning of natural gas and hydrogen supply systems with multiple supply sources, end-consumers, large infrastructures and spatio-temporal mismatches are challenging tasks. In this study, two long-term, multi-regional and monthly time-scale optimization models for natural gas and hydrogen supply systems are developed respectively. China is taken as a case. The natural gas demand will initially increase and then decrease, leading to a premature decommissioning of infrastructure. A coupling model is established to explore the retrofitting of decommissioned natural gas infrastructure for hydrogen supply. Results show that 44.14 % decommissioned pipelines and 34.17 % decommissioned storage facilities of natural gas supply system can be retrofitted, with an annual increase of 63.98 % and 62.80 % in hydrogen pipelines and storage facilities, and a 9.15 % reduction in transition costs.

Changes in the supply and demand potentials of China's glacier water resources in the 21st century: Spatiotemporal mismatches and combined effects

China's glacier water resources (GWRs) are not only indispensable suppliers of fresh water for humans living in large domestic areas but also affect the water supply to downstream neighbouring countries. Therefore, it is crucial to systematically evaluate the spatiotemporal (mis-) matches between the supply and demand potentials of China's GWRs and the combined supply and demand effects in the 21st century to enable regional sustainable development. To facilitate such research, in this study, we first regionalized the importance of China's GWRs in terms of the supply potential and downstream human dependence to reveal the spatial (mis-) matches between supply and demand potentials. Then, changes in the service potential of glacier meltwater and in population dynamics, as well as their temporal (mis-) matches and associated opportunities and risks, were further assessed at the river basin scale. The results showed that GWR plays an important role in 4 of 16 macroscale glacier-fed basins (i.e., Tarim, Junggar, Ili, and Zangxi) and 11 of 37 subbasins within the China region due to higher supply potential and demand potential in those basins. The importance of China's GWRs increases dramatically when taking the demand potential of downstream countries into account, especially in the Ganges and Indus river basins. The peaks in meltwater runoff from the most glacierized basins of the eastern Tianshan Mountains, eastern Qilian Mountains, and southeastern Tibetan Plateau of China occur slightly earlier than the projected peak population (around 2030) under the mid-range Shared Socioeconomic Pathway (SSP245), leading to a compound risk in terms of decreasing meltwater supply and increasing human dependence at the end of the 2020s. However, the peak meltwater is expected to occur later than the peak population in the Tarim, Qiangtang Plateau, and Qaidam basins. The opportunities offered by the increase in meltwater can relieve the water resource pressure for those populations under water-stressed conditions. Greater attention should also be paid to water shortage risks in the transboundary river basins, especially in the Indus and Ganges basins, because the peak meltwater within China is generally expected to occur sooner than the projected peak population of downstream countries. This study provides an effective planning and decision-making basis for the full utilization of China's GWRs and adaptation when glacier runoff declines.

Full Temporal Characterization of Ultrabroadband Few-Cycle Laser Pulses Using Atomically Thin WS2

Nowadays, the accurate and full temporal characterization of ultrabroadband few-cycle laser pulses with pulse durations below 7 fs is of great importance in fields of science that investigate ultrafast dynamic processes. There are several indirect methods that use nonlinear optical signals to retrieve the complex electric field of femtosecond lasers. However, the precise characterization of few-cycle femtosecond laser sources with an ultrabroadband spectrum presents additional difficulties, such as reabsorption of nonlinear signals, partial phase matching, and spatiotemporal mismatches. In this work, we combine the dispersion scan (d-scan) method with atomically thin WS2 flakes to overcome these difficulties and fully characterize ultrabroadband laser pulses with a pulse duration of 6.9 fs and a spectrum that ranges from 650 to 1050 nm. Two-dimensional WS2 acts as a remarkably efficient nonlinear medium that offers a broad transparency range and allows for achieving relaxed phase-matching conditions due to its atomic thickness. Using mono- and trilayers of WS2, we acquire d-scan traces by measuring the second-harmonic generation (SHG) signal, originated via laser–WS2 interaction, as a function of optical dispersion (i.e., glass thickness) and wavelength. Our retrieval algorithm extracts a pulse duration at full-width half-maximum of 6.9 fs and the same spectral phase function irrespective of the number of layers. We benchmark and validate our results obtained using WS2 by comparing them with those obtained using a 10-μm-thick BBO crystal. Our findings show that atomically thin media can be an interesting alternative to micrometer-thick bulk crystals to characterize ultrabroadband femtosecond laser pulses using SHG-d-scan with an error below 100 as (attoseconds).

Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data – instead of models – to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment – where BMPs have been more widely reported – the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Nest orientation and proximity to snow patches are important for nest site selection of a cavity breeder at high elevation

Timing and location of reproduction are central to reproductive success across taxa. Among birds, many species have evolved specific strategies to cope with environmental variability including shifts in timing of reproduction to track resource availability or selecting suitable nest location. In mountain ecosystems, complex topography and pronounced seasonality result in particularly high spatiotemporal variability of environmental conditions. Moreover, the risk of climate‐induced resource mismatches is particularly acute in mountain regions given that temperature is increasing more rapidly than in the lowlands. We investigated how a high‐elevation passerine, the white‐winged snowfinch Montifringilla nivalis, selects its nest site in relation to nest cavity characteristics, habitat composition and snow condition. We used a combination of field habitat mapping and satellite remote sensing to compare occupied nest sites with randomly selected pseudo‐absence sites. In the first half of the breeding season, snowfinches preferred nest cavities oriented towards the morning sun while they used cavities proportional to their availability later on. This preference might relate to the nest microclimate offering eco‐physiological advantages, namely thermoregulatory benefits for incubating adults and nestlings under the harsh conditions typically encountered in the alpine environment. Nest sites were consistently located in areas with greater‐than‐average snow cover at hatching date, likely mirroring the foraging preferences for tipulid larvae developing in meltwater along snowfields. Due to the particularly rapid climate shifts typical of mountain ecosystems, spatiotemporal mismatches between foraging grounds and nest sites are expected in the future. This may negatively influence demographic trajectories of the white‐winged snowfinch. The installation of well‐designed nest boxes in optimal habitat configurations could to some extent help mitigate this risk.

Foraging behavior of a mesopelagic predator, the northern elephant seal, in northeastern Pacific eddies

The role of mesoscale features in structuring trophic transfer in the mesopelagic zone is poorly understood. Deploying sensors on marine animals, or “biologging,” is a powerful tool to infer the organism's behavior and simultaneously collect high-resolution oceanographic data to describe physical-biological interactions. We investigated whether mesoscale eddies are used by a mesopelagic predator, the northern elephant seal (Mirounga angustirostris), and if so, what mechanisms might create beneficial foraging conditions in association with eddies. We hypothesized seals would increase their foraging behavior in both cyclonic and anticyclonic eddies due to nutrient enhancement and physical aggregation of prey and that seals would dive deeper in anticyclonic eddies in response to a deeper prey field. We used tracking data and continuous in situ temperature measurements from 221 adult female northern elephant seals collected between 2004 and 2019. These predators primarily targeted myctophid fishes and squid throughout the northeast Pacific mesopelagic zone, foraging between approximately 400–800 m. Eddy encounters were identified using remotely sensed sea level anomaly data and confirmed visually with collocated sea level anomaly, in situ temperature, and in situ temperature anomaly. Over more than 30,000 days of data and >3 million temperature casts collected by seals, we found 129 high confidence encounters with anticyclonic eddies and 83 with cyclonic eddies. Overall, seals traveled more slowly and in a less directed manner while associated with eddies, particularly anticyclonic eddies, suggesting increased foraging behavior, especially in the California Current. Elephant seals spent more time at the edges of cyclonic eddies than their center. In contrast, they utilized both the interior and edge of anticyclonic eddies. This suggests that the aggregation of prey at the frontal region of an eddy is an important mechanism, whereas nutrient upwelling associated with an eddy play a more minor role in enhancing the seals' prey field. Seal foraging behavior was not influenced by eddy age, size, amplitude, or rotational speed. The large sample size in this study showed considerable variation between individual behavioral responses, suggesting caution when extrapolating individual behavior to a population level. Our data show that both cyclonic and anticyclonic eddies can affect the seals' prey field as demonstrated by enhanced foraging behavior. Still, the variation in behavioral responses resulting from individual foraging strategies, eddy histories, and possible spatiotemporal mismatches between eddy physics and biological responses relevant to mesopelagic predators merit further investigation.

Decarbonising the residential heating sector: A techno-economic assessment of selected technologies

Decarbonising the residential heating sector through electrification can add to the existing flexibility demands in the electricity sector arising from spatio-temporal mismatches in supply in demand. Heat demand peaks during winter require seasonal flexibility, since solar availability is at its minimum, while uncontrolled scheduling of heating appliances requires short term flexibility. However, scheduling appliances optimally and seasonal energy storages can deliver short and long term flexibility by temporarily increasing indoor room temperatures in the short term, and hydrogen generation through electrolysis in the long term. Furthermore, waste heat of fuel cells for power supply coincides with heat demand during winter. Therefore, a techno-economic assessment of different heat provision technologies and refurbishments is performed with a building model implementing flexible heat demand. The model can invest in and schedule different appliances and thereby control the indoor temperature within given boundaries. Emission reductions are then applied and sensitivity analyses for indoor temperatures and H2 prices are performed. The results show that using a combination of solar PV, heat pumps, electrolysers and fuel cells is more cost-efficient than refurbishments. Hydrogen combustion is only used when hydrogen prices fall below gas prices, or when the lower indoor boundary temperature is above 23 °C.

Identification of land use conflicts in China's coastal zones: From the perspective of ecological security

Identification of land use conflicts (LUCs) from the perspective of ecological security is essential for ensuring regional ecological security. Coastal zones in China experience complex management challenges related to increasing demands of ecological protection and economic development, similar to other coastal countries throughout the world. In this study, we established an index system for evaluating the ecological security importance from two perspectives: ecological sensitivity and importance of ecosystem service function. We then used this index system to delimit ecological security space and identify actual LUCs in China's coastal zones in 2018. In addition, we discussed the situation of LUCs in transitional zones of the coastal zones from a horizontal perspective. Results indicated prominent spatio–temporal mismatches among cultivated land, construction land, and the ecological spatial layout in coastal zones. In the ecological space, the area of cultivated land conflict zone was 12.60%, whereas that of the construction land conflict zone was 10.26%. LUCs existed in all coastal provinces. Overall, significant regional differences were observed in the distribution of LUCs, with near-land side and southern region showing higher distributions than the near-sea side and northern region, respectively. Meanwhile, the cultivated land conflict zone generally radiated outward with the construction land conflict zone as the ‘source’. The findings of this study can provide insights for decision-makers into the location of cultivated land and construction land, which are most likely to occupy ecologically important spaces.

Understory vegetation contributes to microclimatic buffering of near-surface temperatures in temperate deciduous forests

Accurately predicting microclimate is considered a high priority for understanding organismal responses to climate change at biologically relevant scales. However, approaches to developing robust microclimate datasets and understanding of the biophysical processes altering microclimatic regimes are limited. We developed and evaluated an approach for predicting microclimatic temperatures in montane forests that incorporates the influence of complex vegetation structure and landscape physiography. Additionally, we determined spatiotemporal mismatches between free-air and microclimatic temperatures to highlight the location, phenology, and magnitude of differences in predicted temperature. We combined temperature datalogger measurements with LiDAR-derived vegetation and GIS-derived landscape physiographic characteristics to downscale free-air temperatures to microclimatic (3 m2 spatial resolution) temperatures in the Great Smoky Mountains. We assessed the contribution of forest vegetation layers in altering microclimatic temperatures and model accuracy, and compared coarse-grain temperature maps with microclimatic temperature maps. Understory vegetation structure contributes to microclimatic buffering of near-surface, forest temperatures and enhances the accuracy of maximum temperature predictions during the growing season by altering the effects of solar insolation and topographic convergence index on microclimatic temperatures. Elevation and solar insolation covaried with spatiotemporal mismatches between free-air and microclimatic temperatures, suggesting that these landscape physiographic characteristics may contribute to deviations between macro- and micro-scale temperature. Our findings demonstrate the importance of including complex vegetation characteristics and biophysical interactions as climate forcing factors in microclimate modeling. We also demonstrate the plausibility of accurately predicting microclimatic temperatures over broad extents, an important step in predicting potential organismal responses to climate change.

Assessment of the TROPOMI tropospheric NO<sub>2</sub> product based on airborne APEX observations

Abstract. Sentinel-5 Precursor (S-5P), launched in October 2017, carrying the TROPOspheric Monitoring Instrument (TROPOMI) nadir-viewing spectrometer, is the first mission of the Copernicus Programme dedicated to the monitoring of air quality, climate, and ozone. In the presented study, the TROPOMI tropospheric nitrogen dioxide (NO2) level-2 (L2) product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) has been validated over strongly polluted urban regions by comparison with coincident high-resolution Airborne Prism EXperiment (APEX) remote sensing observations (∼ 75 m × 120 m). Satellite products can be optimally assessed based on (APEX) airborne remote sensing observations, as a large amount of satellite pixels can be fully mapped at high accuracy and in a relatively short time interval, reducing the impact of spatiotemporal mismatches. In the framework of the S-5P validation campaign over Belgium (S5PVAL-BE), the APEX imaging spectrometer has been deployed during four mapping flights (26–29 June 2019) over the two largest urban regions in Belgium, i.e. Brussels and Antwerp, in order to map the horizontal distribution of tropospheric NO2. For each flight, 10 to 20 TROPOMI pixels were fully covered by approximately 2700 to 4000 APEX measurements within each TROPOMI pixel. The TROPOMI and APEX NO2 vertical column density (VCD) retrieval schemes are similar in concept. Overall, for the ensemble of the four flights, the standard TROPOMI NO2 VCD product is well correlated (R = 0.92) but biased negatively by −1.2 ± 1.2 × 1015 molec cm−2 or −14 ± 12 %, on average, with respect to coincident APEX NO2 retrievals. When replacing the coarse 1∘ × 1∘ the massively parallel (MP) version of the Tracer Model version 5 (TM5) a priori NO2 profiles by NO2 profile shapes from the Copernicus Atmospheric Monitoring Service (CAMS) regional chemistry transport model (CTM) ensemble at 0.1∘ × 0.1∘, R is 0.94 and the slope increases from 0.82 to 0.93. The bias is reduced to −0.1 ± 1.0 × 1015 molec cm−2 or −1.0 ± 12 %. The absolute difference is on average 1.3 × 1015 molec cm−2 (16 %) and 0.7 × 1015 molec cm−2 (9 %), when comparing APEX NO2 VCDs with TM5-MP-based and CAMS-based NO2 VCDs, respectively. Both sets of retrievals are well within the mission accuracy requirement of a maximum bias of 25 %–50 % for the TROPOMI tropospheric NO2 product for all individual compared pixels. Additionally, the APEX data set allows the study of TROPOMI subpixel variability and impact of signal smoothing due to its finite satellite pixel size, typically coarser than fine-scale gradients in the urban NO2 field. For a case study in the Antwerp region, the current TROPOMI data underestimate localized enhancements and overestimate background values by approximately 1–2 × 1015 molec cm−2 (10 %–20 %).

Integrating Ecosystem Resilience and Resistance Into Decision Support Tools for Multi-Scale Population Management of a Sagebrush Indicator Species

Imperiled sagebrush (Artemisia spp.) ecosystems of western North America are experiencing unprecedented conservation planning efforts. Advances in decision-support tools operationalize concepts of ecosystem resilience by quantitatively linking spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances. However, failure to consider higher trophic-level fauna of conservation concern in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. Here, we provide multi-scale examples of decision-support tools for management and restoration actions that evaluate general resilience mapped to variation in soil moisture and temperature regimes through new lenses of habitat selection and population performance responses for an at-risk obligate species to sagebrush ecosystems, the greater sage-grouse (Centrocercus urophasianus). We then briefly describe general pathways going forward for more explicit integration of sage-grouse fitness with factors influencing variation in sagebrush resilience to disturbance and resistance to invasive species (e.g., annual grasses). The intended product of these efforts is a more targeted operational definition of resilience for managers by using quantifiable metrics that help limit chances of spatiotemporal mismatches among restoration responses owing to differences in engineering resilience between sagebrush ecosystem processes and sage-grouse population dynamics. Moreover, spatial resilience can be promoted though explicit consideration of sage-grouse and sagebrush predicted responses to active and passive management treatments across space and time. We describe tools that include multi-scale geospatial overlays and simulation analyses of post-disturbance land cover recovery aimed at prioritizing primary threats to sagebrush ecosystems in the Great Basin in the western portion of sage-grouse range (i.e., grass-fire cycles and conifer expansion), but underlying concepts have broader application to a range of ecosystems.

Integrating eddy fluxes and remote sensing products in a rotational grazing native tallgrass prairie pasture

Eddy covariance (EC) systems provide integrated fluxes within their footprint areas. Spatial heterogeneity of up-scaled areas and spatio-temporal mismatches between EC footprint and remote sensing pixels jeopardize the performance of most satellite-based models. To examine the impact of spatial resolution of satellite products on up-scaling of fluxes, we compared the relationships between measured eddy fluxes and enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 and 250 m spatial resolutions, Visible Infrared Imaging Radiometer Suite (VIIRS) at 500 m spatial resolution, and Landsat at 30 m spatial resolution but integrated at the paddock-scale. The experiment was conducted over a grazed native tallgrass prairie pasture, which was divided into nine paddocks for rotational grazing. The EVI data from all satellites showed consistency in detecting vegetation phenology. Seasonality of EC-measured fluxes corresponded well with remotely-sensed vegetation phenology. Approximately 80% of contribution to eddy fluxes came from within 80 m upwind distance of the 2.7 m tall EC tower. As a result, the major contributing area for the measured fluxes was mostly limited to the paddock containing the EC tower. Different timings and duration of grazing caused some heterogeneity among paddocks within the pasture. The EVI of different spatial scales showed strong relationships with CO2 fluxes. However, Landsat-derived EVI integrated for the paddock containing the EC tower showed substantially stronger relationships with CO2 fluxes than did MODIS and VIIRS-derived EVI integrated for multiple paddocks, most likely due to similar spatial resolutions of remote sensing and EC observations. Results illustrate that satellite products of fine-scale spatial resolution that are comparable to EC footprints can help improve the performance of satellite-based models for modeling or up-scaling of eddy fluxes, especially in heterogeneous ecosystems.

Anonymization and De-Anonymization of Mobility Trajectories: Dissecting the Gaps Between Theory and Practice

Human mobility trajectories are increasingly collected by ISPs to assist academic research and commercial applications. Meanwhile, there is a growing concern that individual trajectories can be de-anonymized when the data is shared, using information from external sources (e.g., online social networks). To understand this risk, prior works either estimate the theoretical privacy bound or simulate de-anonymization attacks on synthetically created datasets. However, it is not clear how well the theoretical estimations are preserved in practice. In this article, we collected a large-scale ground-truth trajectory dataset from 2,161,500 users of a cellular network, and two matched external trajectory datasets from a large social network (56,683 users) and a check-in/review service (45,790 users) on the same user population. The two sets of large ground-truth data provide a rare opportunity to extensively evaluate a variety of de-anonymization algorithms (nine in total). We find that their performance in the real-world dataset is far from the theoretical bound. Further analysis shows that most algorithms have under-estimated the impact of spatio-temporal mismatches between the data from different sources, and the high sparsity of user generated data also contributes to the under-performance. Based on these insights, we propose four new algorithms that are specially designed to tolerate spatial or temporal mismatches (or both) and model location contexts and time contexts. Extensive evaluations show that our algorithms achieve more than 17 percent performance gain over the best existing algorithms, confirming our insights. Further, we propose two new location-privacy preserving mechanisms utilizing the spatio-temporal mismatches to better protect users' privacy against the de-anonymization attack. Evaluation results show that our proposed mechanisms can reduce the performance of de-anonymization attacks by over 8.0 percent, demonstrating the effectiveness of our insights.

Earlier colony arrival but no trend in hatching timing in two congeneric seabirds (Uria spp.) across the North Atlantic.

A global analysis recently showed that seabird breeding phenology (as the timing of egg-laying and hatching) does not, on average, respond to temperature changes or advance with time (Keogan et al. 2018 Nat. Clim. Change8, 313-318). This group, the most threatened of all birds, is therefore prone to spatio-temporal mismatches with their food resources. Yet, other aspects of the breeding phenology may also have a marked influence on breeding success, such as the arrival date of adults at the breeding site following winter migration. Here, we used a large tracking dataset of two congeneric seabirds breeding in 14 colonies across 18° latitudes, to show that arrival date at the colony was highly variable between colonies and species (ranging 80 days) and advanced 1.4 days/year while timing of egg-laying remained unchanged, resulting in an increasing pre-laying duration between 2009 and 2018. Thus, we demonstrate that potentially not all components of seabird breeding phenology are insensitive to changing environmental conditions.

Space oddity: The mission for spatial integration

Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability and, ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.

Spatio-Temporal Relationships between Optical Information and Carbon Fluxes in a Mediterranean Tree-Grass Ecosystem

Spatio-temporal mismatches between Remote Sensing (RS) and Eddy Covariance (EC) data as well as spatial heterogeneity jeopardize terrestrial Gross Primary Production (GPP) modeling. This article combines: (a) high spatial resolution hyperspectral imagery; (b) EC footprint climatology estimates; and (c) semi-empirical models of increasing complexity to analyze the impact of these factors on GPP estimation. Analyses are carried out in a Mediterranean Tree-Grass Ecosystem (TGE) that combines vegetation with very different physiologies and structure. Half-hourly GPP (GPPhh) were predicted with relative errors ~36%. Results suggest that, at EC footprint scale, the ecosystem signals are quite homogeneous, despite tree and grass mixture. Models fit using EC and RS data with high degree of spatial and temporal match did not significantly improved models performance; in fact, errors were explained by meteorological variables instead. In addition, the performance of the different models was quite similar. This suggests that none of the models accurately represented light use efficiency or the fraction of absorbed photosynthetically active radiation. This is partly due to model formulation; however, results also suggest that the mixture of the different vegetation types might contribute to hamper such modeling, and should be accounted for GPP models in TGE and other heterogeneous ecosystems.

Zip code caveat: bias due to spatiotemporal mismatches between zip codes and US census-defined geographic areas--the Public Health Disparities Geocoding Project.

Zip code caveat: bias due to spatiotemporal mismatches between zip codes and US census-defined geographic areas--the Public Health Disparities Geocoding Project.