Natural Environmental Changes Research Articles

Empirical food webs of 12 tropical reservoirs in Singapore.

Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised trophic links between predators and prey and can be presented as empirical food webs, in which the relative strength/importance of the respective links are quantified. Some common methods used in food web research include gut content analysis (GCA) and stable isotope analysis (SIA). We combine both methods to construct empirical food web models as a basis for monitoring and studying ecosystem-level outcomes of natural (e.g. species turnover in fish assemblage) and intentional environmental change (e.g. biomanipulation). We present 12 food webs from tropical reservoir communities in Singapore and summarise the topology of each with widely-used network indices (e.g. connectance, link density). Each reservoir was surveyed over 4-6 sampling occasions, during which, representative animal groups (i.e. fish species and taxonomic/functional groups of zooplankton and benthic macroinvertebrates) and all likely sources of primary production (i.e. macrophytes, periphyton, phytoplankton and riparian terrestrial plants) were collected. We analysed gut content in fishes and bulk isotope (d13C and d15N) profiles of all animals (i.e. fishes and invertebrates) and plants collected. Both sets of information were used to estimate the relative strength of trophic relationships using Bayesian mixing models. We document our protocol here, alongside a script in the R programming language for executing data management/analyses/visualisation procedures used in our study. These data can be used to glean insights into trends in inter- and intra-specific or guild interactions in analogous freshwater lake habitats.

Implementing Sustainability into Virtual Simulation Games in Business Higher Education

The paper aims to determine how sustainability can be implemented into virtual business simulators dedicated to higher education due to the need for raising environmental awareness among students. Climate and natural environmental changes caused by human activities require adjustments in society’s mindsets and activities, especially in the business-related sector, which makes the implementation of sustainability in business higher education of crucial importance. Virtual business simulators are innovative tools in business higher education. Their use, as a part of game-based learning, is attracting increasing interest, as this method allows us to understand interactions between business decisions and their results. In this paper, we present our case study of an IT-based business simulator, which includes aspects of sustainability, and the initial experience of a group of test students participating in the business game. The paper discusses the authors’ own IT solutions and the possibilities of implementing the concept of sustainability into business-oriented higher education. This paper proposed the manner of implementing sustainability, including pseudocodes, into a virtual business simulator. The results show how challenging it is to implement sustainability into game-based business education, as it increases the complexity of interactions among different aspects of running a business, including the goal of making a company more diversified.

On the Exploration of Social Development during a Historical Period in the Eastern Tienshan Mountains via Archaeological and Geopolitical Perspectives

Natural and social environment changes have played important roles in social evolution in different times and spaces. Geopolitical change, in particular, might play a decisive role in social evolution during historical periods. The eastern Tienshan Mountains was a transportation hub for communication between the East and the West, where the natural environment is fragile and the social environment has been complex during the historical period. However, geopolitical change and its impact on local social development remain unclear due to fragmented historical records and limited studies. This study investigates the spatiotemporal variations of military facilities in the Hami region, and compares historical documents and archaeological and paleoclimate records to discuss geopolitical changes and social evolution during the historical period in the eastern Tienshan Mountains. A total of 84 visible organic remains from 38 historic beacon towers and 8 dak sites in the Hami region of the eastern Xinjiang Uygur Autonomous Region, northwestern China, were collected and the radiocarbon (14C) dates of these ruins were systematically determined with accelerator mass spectrometry. The dating results show that these sites were mainly built during two major periods: ca. 600–900 cal AD and ca. 1600–1950 cal AD, which roughly correspond to the Tang Dynasty (618–907 AD) and the Qing Dynasty (1636–1912 AD) in ancient China. Human settlement intensity was high during the Han, Tang, and Qing dynasties, and relatively low when the area was controlled by nomadic or local regimes. This suggests that agricultural empires and nomadic/local regimes adopted different strategies for regional management. Climate change might have affected geopolitical patterns, which, in turn, profoundly influenced human activities and social evolution in the eastern Tienshan Mountains over the last two millennia. This study systematically reveals the spatiotemporal variations of beacon towers and dak ruins in the region through a large number of reliable direct 14C dating, it reveals the remarkable differences in human activities in the eastern Tienshan Mountains under different administrations, and it explores the influence of geopolitics and climate change on social evolution in the eastern Tienshan Mountains from a multidisciplinary perspective.

Construction and Analysis of Urban Traffic Noise Prediction Model Based on PSO Algorithm and BRF Network Structure

Due to the current nonlinear traffic noise and changing natural environment, accurate prediction of traffic noise has become a major challenge. In order to improve the accuracy of traffic noise prediction, this paper constructs a short-term traffic noise prediction model based on PSO algorithm and BRF network structure. The model can predict the noise state of future traffic according to historical traffic information. Particle swarm optimization (PSO) network is used for short-term traffic prediction to deal with the problems of low accuracy and long-time consumption. A BRF (one-dimensional convolution)-PSO short-term traffic noise prediction model is proposed. BRF method is used to extract the spatial features of traffic noise and compared with PCA (principal component analysis)-PSO model and PSO model. The results show that the prediction accuracy of BRF-PSO model is 2% higher than that of PCA-PSO model and 6% higher than that of PSO model, which proves the effectiveness of BRF-PSO model. This study provides a technical reference for the short-term traffic noise prediction of intelligent city and the effective improvement of urban traffic environment.

The national nature reserves in China: Are they effective in conserving mangroves?

Mangroves are high-productive ecosystems and globally protected. Establishing nature reserves aimed at counteracting the negative effects of anthropogenic activities is one of the most pivotal approaches to conserve mangrove ecosystems. Evaluation of the conservation effectiveness for mangrove nature reserves is thus indispensable for making knowledge-based conservation policies and funding-decisions by government and managers. In this study, using composited Landsat images by the Google Earth Engine cloud platform and object-oriented deep learning classification method, the land cover maps of national mangrove nature reserves (NMNRs) in China were obtained from 1987 to 2019. The systematic evaluation of conservation effectiveness for each NMNR was conducted by landscape metrics and an entropy weight model. Combined with the dynamics in mangrove distribution, human interference intensity, and natural environment change, the driving force factors affecting the conservation effectiveness for NMNRs were investigated. The results show that the total mangrove area in all NMNRs increased 968.6 ha during the study period, a 21.8 % rate of increase. Except for one NMNR with a slight decline, the conservation of remaining NMNRs was considered effective with increase varied from 14.8 % to 87.5 % in the level of protective efficacy. The conservation effectiveness of NMNRs was affected by both anthropogenic and natural factors, while the improvement to the conservation effectiveness was largely attributed to the implementation of protection policies, such as reforestation engineering. Further direct or indirect challenges in mangrove conservation effectiveness, e.g., pollution, natural disasters, and exotic species invasion, still require close attention. This study provides an effective and efficient approach to quantify the conservation effectiveness of mangrove nature reserves, which would facilitate mangrove conservation and management in the future.

Si isotope ratio of radiolaria across Triassic–Jurassic transition in a pelagic deep-sea bedded chert (Inuyama, Japan)

The end-Triassic extinction event (ETE) marks one of the “Big five” mass extinction events of the Phanerozoic, yet the timing and nature of environmental changes on a global scale remain elusive. Here we report a mm-scale high-resolution δ30Si profile of sea surface-dwelling radiolaria, preserved as moulds, spanning the end-Triassic radiolarian turnover interval of the deep-sea succession at the Katsuyama section, Inuyama, Japan. The δ30Si of the Triassic-Jurassic radiolaria between − 0.6 ± 0.5‰ and 2.6 ± 0.3‰ overlap with available radiolarian δ30Si data for Triassic to Cenozoic, including modern samples. The mass balance of Si with dominant radiolaria up to 90% in chert supports negligible impact of diagenesis on δ30Si of radiolarian moulds. The cm-scale δ30Si variations up to 2 ‰ are overall associated with changes in silica contents. Here we hypothesize that the δ30Si of radiolarian reflect radiolarian productivity. We detected negative silicon isotope excursions within and above the end-Triassic radiolarian turnover interval, named here the SIE 1 and 2. The first SIE of 2 ‰ is detected from 0 mm to 10 mm above the base of purple chert interval, probably linked with the initial massive volcanism in the Central Atlantic magmatic provinces (CAMP) and associated deep-sea acidification and the onset of the end-Triassic radiolarian turnover. Subsequent positive SIE up to 2 ‰ ca. 10 mm above the first negative SIEs may record recovery of biosiliceous productivity, which could may be related with the first appearance of several Jurassic radiolarian taxa within the radiolarian turnover interval. We also detected data that is suggestive of SIE 2 in the lowermost dusky red chert bed, suggesting similar changes in productivity. These negative SIEs occurred within ~ 1 mm interval, implying the occurrence of kyr- or shorter-scale drastic environmental perturbations across the end-Triassic radiolarian turnover interval.

Host-parasite coevolution: Partitioning the effects of natural selection and environmental change using coupled Price equations.

George Price showed how the effects of natural selection and environmental change could be mathematically partitioned. This partitioning may be especially useful for understanding host–parasite coevolution, where each species represents the environment for the other species. Here, we use coupled Price equations to study this kind of antagonistic coevolution. We made the common assumption that parasites must genetically match their host's genotype to avoid detection by the host's self/nonself recognition system, but we allowed for the possibility that non‐matching parasites have some fitness. Our results show how natural selection on one species results in environmental change for the other species. Numerical iterations of the model show that these environmental changes can periodically exceed the changes in mean fitness due to natural selection, as suggested by R.A. Fisher. Taken together, the results give an algebraic dissection of the eco‐evolutionary feedbacks created during host–parasite coevolution.

Seasonal Dynamics in Carbon Cycling of Marine Bacterioplankton Are Lifestyle Dependent.

Although free-living (FL) and particle-attached (PA) bacteria are recognized as ecologically distinct compartments of marine microbial food-webs, few, if any, studies have determined their dynamics in abundance, function (production, respiration and substrate utilization) and taxonomy over a yearly cycle. In the Baltic Sea, abundance and production of PA bacteria (defined as the size-fraction >3.0 μm) peaked over 3 months in summer (6 months for FL bacteria), largely coinciding with blooms of Chitinophagales (Bacteroidetes). Pronounced changes in the growth efficiency (range 0.05–0.27) of FL bacteria (defined as the size-fraction <3.0 μm) indicated the magnitude of seasonal variability of ecological settings bacteria experience. Accordingly, 16S rRNA gene analyses of bacterial community composition uncovered distinct correlations between taxa, environmental variables and metabolisms, including Firmicutes associated with elevated hydrolytic enzyme activity in winter and Verrucomicrobia with utilization of algal-derived substrates during summer. Further, our results suggested a substrate-controlled succession in the PA fraction, from Bacteroidetes using polymers to Actinobacteria and Betaproteobacteria using monomers across the spring to autumn phytoplankton bloom transition. Collectively, our findings emphasize pronounced seasonal changes in both the composition of the bacterial community in the PA and FL size-fractions and their contribution to organic matter utilization and carbon cycling. This is important for interpreting microbial ecosystem function-responses to natural and human-induced environmental changes.

Role of Mobile Phones in Creating Environmental Awareness Among Fishers in the Indus Delta of Pakistan

Mobile phones changed the patterns of communication and flow of information in human society. This study assesses their importance in creating awareness about issues related to the natural environment and climate change, where responsiveness at a community is essential. It examines particularly the role of mobile phones in creating environmental awareness among fishers in the Indus Delta region of Pakistan. Mobile usage patterns, mobile phones as a source of environmental information and the use of social media for environmental discourse among the fishing communities are analysed. The results indicate that mobile communication is ranked as the fifth major source of information about environmental problems in the Indus Delta after personal observation, television, radio and newspapers. Although mobile phones offer high potential for receiving, accessing and reporting information about environmental issues through the use of social media, they are still not widely used for such purposes in these fishing communities.

Assessment of the Vulnerability of the Lucana Coastal Zones (South Italy) to Natural Hazards

Coasts are highly dynamic and geo-morphologically complex systems that are exposed to several factors such as waves, extreme meteorological events and climate change. It is also well-recognized that coastal zones, characterized by an increasing population growth, are vulnerable to climate change. In addition, coastal erosion, resulting from natural environment changes and human activities, acts worldwide. Consequently, it is necessary to quantify coastal hazards vulnerability and develop tools to monitor coastal risks and support making targeted climate adaptation policies. In this paper, a framework to estimate coastal vulnerability to flooding and erosion has been developed for the Ionian Basilicata coast. It is based on two methods: the integrated vulnerability index (flooding and erosion) and the CeD physical vulnerability index (multi-risk assessment). Our results are in agreement with the recent shoreline evolution: the integrated coastal risk of the Ionian Basilicata coast is generally medium to high, while the “physical erosion vulnerability” is generally high to very high. In addition, the results highlight a spatial variability of the vulnerability, probably due to the morphology of the beach, which requires developing a strategic approach to coastal management and defining mitigation measures, considering relevant risk aspects as the vulnerability and exposure degree.

Ambulatory Assessment in Concussion Clinical Care and Rehabilitation.

Concussion is a mild traumatic brain injury that is characterized by a wide range of physical, emotional, and cognitive symptoms as well as neurocognitive, vestibular, and ocular impairments that can negatively affect daily functioning and quality of life. Clinical consensus statements recommend a targeted, clinical profile-based approach for management and treatment. This approach requires that clinicians utilize information obtained via a clinical interview and a multi-domain assessment battery to identify clinical profile(s) (e.g., vestibular, mood/anxiety, ocular, migraine, cognitive fatigue) and prescribe a corresponding treatment/rehabilitation program. Despite this comprehensive approach, the clinical picture can be limited by the accuracy and specificity of patient reports (which often conflate timing and severity of symptomology), as well as frequency and duration of exposure to symptom exacerbating environments (e.g., busy hallways, sitting in the back seat of a car). Given that modern rehabilitation programs leverage the natural environment as a tool to promote recovery (e.g., expose-recover approach), accurate characterization of the patient clinical profile is essential to improving recovery outcomes. Ambulatory assessment methodology could greatly benefit concussion clinical care by providing a window into the symptoms and impairments experienced by patients over the course of their daily lives. Moreover, by evaluating the timing, onset, and severity of symptoms and impairments in response to changes in a patient's natural environment, ambulatory assessments can provide clinicians with a tool to confirm clinical profiles and gauge effectiveness of the rehabilitation program. In this perspective report, we review the motivations for utilizing ambulatory assessment methodology in concussion clinical care and report on data from a pilot project utilizing smart phone-based, ambulatory assessments to capture patient reports of symptom severity, environmental exposures, and performance-based assessments of cognition for 7 days following their initial evaluation.

Antioxidant capacity and carbon-based scope for growth of brackish water clams Corbicula japonica under the combined effects of natural and anthropogenic factors

Changes in natural estuarine environment and anthropogenic disturbances are becoming significant threats to organisms, particularly bivalves. A deeper understanding of the relationship between biochemical- and individual-level responses is necessary to assess the combined effects of natural and anthropogenic factors on bivalves. To the best of our knowledge, this is the first study where the oxygen radical absorbance capacity (ORAC) and carbon-based scope for growth (C-SFG) were applied as biomarkers to evaluate the response of the brackish water clam Corbicula japonica to four spatiotemporally varying environmental factors. High water temperature and food availability supported C-SFG while high salinity inhibited it. Most of wastewater (WW) treatments resulted in negative C-SFG values because of a reduced clearance rate and increased excretion rate. In particular, high food availability with WW treatment resulted in the lowest C-SFG value of −114 μg C·ind−1 h−1. The ORAC was activated in response to high salinity with WW treatment (p < 0.05). To ascertain the combined effects of the natural and anthropogenic factors, principal component and cluster analyses were performed on the ORAC and C-SFG data. Anthropogenic WW was found to have different effects on the physiological and biochemical biomarkers according to the natural conditions. A roughly negative correlation was observed between ORAC and C-SFG because activation of the antioxidant capacity can influence the growth potential of the clams through the additional use of available metabolic energy. However, some exceptions were observed where both the ORAC and C-SFG values were either high or low, which could be because the C-SFG response varies depending on different metabolic behaviors even when the ORAC response remains the same. These results indicate that the biochemical-level response (i.e., ORAC) of C. japonica can be interpreted using individual-level response (i.e., C-SFG), but careful attention must be given to over- or underestimation.

Multidecadal monitoring highlighted long-term stability of protected assemblages within a Mediterranean marine reserve

Marine Protected Areas (MPAs) are at the core of management and conservation plans aimed at counteracting the ongoing widespread degradation of marine ecosystems. Although the outcomes of protection in enhancing marine biodiversity and restoring populations of exploited species are widely recognized, the putative effect of MPAs in increasing the resilience of marine communities and ecosystems is still underexplored. In this study, long-term data from a no-take area of a Mediterranean MPA and unprotected locations were used to investigate the effects of full protection on the temporal stability of sessile assemblages on shallow subtidal rocky reefs. Results highlighted that assemblages within the no-take area exhibited a more consistent structure over 20 years of study, whereas a significantly larger temporal variability characterized assemblages at the unprotected locations. Reduced levels of human pressure and stabilizing processes related to the re-establishment of the integrity of trophic networks within the MPA could underlie the observed patterns. Assessing whether MPAs may improve the ability of marine communities to absorb disturbance, from local to large scale sources, is essential to ascertain their contribution to future adaptive conservation strategies in the face of global change. This study provided evidence that MPAs, if well managed, can represent an effective tool to smooth fluctuations in the structure of marine communities, thus potentially reducing their vulnerability to natural and human-driven environmental changes.

Single Plant Fertilization Using a Robotic Platform in an Organic Cropping Environment

The growing demand for organically produced vegetables requires the adoption of new cropping systems such as strip-cropping. To counteract the additional labour mixed cropping entails, automation and robotics play a key role. This research focuses on the development of a proof-of-concept platform that combines optical sensors and an actuation system for targeted precision fertilization that encircles selected plants rather than a local field area. Two sensor types are used for the detection of a fertilisation need: a multispectral camera and light detection and ranging (LiDAR) devices in order to acquire information on plant health status and three-dimensional characterisation. Specific algorithms were developed to more accurately detect a change in fertilization need. An analysis of their results yields a prescription map for automatic fertilisation through a robotic arm. The relative location of the platform within the prescription map is essential for the correct application of fertilizers, and is acquired through live comparison of a LiDAR pushbroom with the known 3D world model. The geometry of each single plant is taken into account for the application of the sprayed fertiliser. This resulted in a reliable method for the detection of delayed growth and prototype localization within a changing natural environment without relying on external markers.

Climate Risks and Opportunities of the Marine Fishery Industry: A Case Study in Taiwan

As climate change and extreme weather intensify, forecasting natural environmental changes involves high uncertainty and variation. Planned policy changes and the ability of fisheries to withstand these changes and impacts are major challenges in regard to addressing future climate hazards in Taiwan. Taiwan’s geographic location is favourable for the marine fishery industry, which is an important primary industry and a source of animal protein for residents of Taiwan. Recently, both long-term climate change and extreme climate hazards have led to shocks in the marine fishery industry. The resulting instability of the industry directly affects the market supply of and demand for seafood. We conduct a case study of a marine fishery industry in Taiwan that incorporates social concern assessments of risk perception and judgements of risk acceptance through risk management processes. Furthermore, we incorporate stakeholder participatory processes to reduce the gap in awareness of adaptation and to increase the opportunity to reach consensus and develop an integrated risk management model that enables decision-makers to better meet the needs of society. These measures will enhance all parties’ willingness to adapt and help achieve the goal of public–private collaboration in facing climate change challenges.

Long-term stochastic model predictive control and efficiency assessment for hydro-wind-solar renewable energy supply system

It is popular to combine the hydropower plant with the wind and solar power plants to supply electricity, and the joint is termed as the hydro-wind-solar renewable energy supply system (RESS). The long-term optimal operation of the RESS is a challenging task, due to the nature of different spatial and temporal variabilities associated with renewable energy resources, and the significant operation uncertainties due to the changing natural environment. To address the task, the stochastic model predictive control (MPC), based on probabilistic forecasting and rolling stochastic optimization, is designed and implemented for the long-term operations of the RESSs in Yunnan province, China. The paper tests out the system efficiencies for different penetration levels of wind and solar power, and finds out that (1) the Long Short-Term Memory performs best among candidate point prediction algorithms; (2) the stochastic MPC considering the correlations among renewable resources helps the RESS operate with a higher efficiency; (3) the large-scale hydropower plant has great potential to offset the effects of seasonal uncertainties and demand-generation mismatch, but cannot completely avoid the electricity shortage enabled by unexpected scenarios of renewable resources.

Several major issues concerning the environmental transmission and risk prevention of SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) is the most serious infectious disease pandemic in the world in a century, and has had a serious impact on the health, safety, and social and economic development of all mankind. Since the earth entered the “Anthropocene”, human activities have become the most important driving force of the evolution of the earth system. At the same time, the epidemic frequency of major human infectious diseases worldwide has been increasing, with more than 70% of novel diseases having zoonotic origins. The review of several major epidemics in human history shows that there is a common rule, i.e., changes in the natural environment have an important and profound impact on the occurrence and development of epidemics. Therefore, the impact of the natural environment on the current COVID-19 pandemic and its mechanisms have become scientific issues that need to be resolved urgently. From the perspective of the natural environment, this study systematically investigated several major issues concerning the environmental transmission and risk prevention of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). From a macroscopic temporal and spatial scale, the research focus on understand the impact of the destruction of the natural environment and global changes on the outbreak of infectious diseases; the threat of zoonotic diseases to human health; the regularity for virus diffusion, migration and mutation in environmental media; the mechanisms of virus transmission from animals and environmental media to humans; and environmental safety, secondary risk prevention and control of major epidemics. Suggestions were made for future key research directions and issues that need attention, with a view to providing a reference for the prevention and control of the global coronavirus disease 2019, and to improving the ability of response to major public health emergencies.

Emergency response recommendation for long-distance oil and gas pipeline based on an accident case representation model

Long-distance oil and gas pipelines undergo great changes in natural environments and geographical conditions along length. Inadequate communications provided limited and vague information about accidents. Scattered emergency resources need adequate response preparations to reduce recovery time after an accident. Examining historic similar cases in the database in order to propose effectual accident responses is worth studying. In emergency response case-based reasoning (CBR), information on new accidents, such as type, degree, hazard object, etc. need to be as detailed as possible. The anticipated quality and efficiency of traditionally case recommendations might have been directly negatively influenced, by the delayed and ambiguous information available from new pipeline accidents. Thus, to fully extract the required information, and to minimize limitations on reasoning caused by a lack of accident information, this study proposes an accident Case Representation Model. The model contains: (i) an accident features dataset featuring a bipartite graph from hundreds of pipeline cases, and (ii) cases vectorization obtained by applying graph representation learning. As a result, (iii) recommendations of any new accident can be given based on similar case responses. In order to examine the accuracy of the recommended results, a relative similarity concept is proposed, showing that the proposed model's recommendation accuracy is basically maintained at 96.7%. Compared to other case vectorization methods, the accuracy increased by 4%–23%. Taking a block valve failure accident as a case study, this model expands on two related scenarios: overpressure in upstream pipeline and interruption of communication system. The supplementary responses increase the preparation comprehensiveness.

Multiple factors drive imbalance in the global microbial assemblage in soil

Soil microbial assemblages play a critical role in biogeochemical cycling processes in terrestrial ecosystems. Dynamic global information for these assemblages considering multiple factors is critical for predicting ecological safety concerns but remains unpredictable. Here, we collected microbial data from soil datasets worldwide and used a feature-explicable machine learning (FEML) approach to address this problem. Multiple-factor and factor interaction network analysis based on FEML can be used to visualize the restrictive relationships among multiple factors (e.g., fertilizer application, land use, and changing global climate and natural environments), which are difficult to explore based on limited experimental data and traditional machine learning methods. The FEML approach predicted that areas of bacterial hotspots in South America and Africa will expand by approximately 27% and 83%, respectively, in scenario RCP8.5 in 2100. In contrast, the areas of fungal hotspots in Asia and North America will decline by approximately 34% and 62%, respectively, under RCP8.5. The unbalanced ratios of bacteria to fungi affect the soil ecosystem, and bacterial-dominated communities contribute to the reduction of easily decomposing nutrients, the growth of the bacterivore community and a high proportion of microaggregates in the soil. Therefore, mitigating climate change is critical to reduce the remarkable imbalance between soil bacteria and fungi and predict risks to soil microbial assemblages based on multiple factors.

Direct observation of adaptive tracking on ecological time scales in Drosophila.

Direct observation of evolution in response to natural environmental change can resolve fundamental questions about adaptation, including its pace, temporal dynamics, and underlying phenotypic and genomic architecture. We tracked the evolution of fitness-associated phenotypes and allele frequencies genome-wide in 10 replicate field populations of Drosophila melanogaster over 10 generations from summer to late fall. Adaptation was evident over each sampling interval (one to four generations), with exceptionally rapid phenotypic adaptation and large allele frequency shifts at many independent loci. The direction and basis of the adaptive response shifted repeatedly over time, consistent with the action of strong and rapidly fluctuating selection. Overall, we found clear phenotypic and genomic evidence of adaptive tracking occurring contemporaneously with environmental change, thus demonstrating the temporally dynamic nature of adaptation.