Ecosystem Behavior Research Articles

Measurements of suspended ashes concentration in turbulent flow with acoustic doppler velocimeter

Measuring and estimating dispersion coefficients for ash particles released in watercourses is required for a broad understanding of their transport and behaviour in aquatic ecosystems. Calibration of a high-frequency acoustic backscattering system and estimates of its sensitivity to particulates of known size distribution and concentration are presented. Laboratory experiments were conducted to derive the relationship between suspended sediment concentration (SSC) of biomass ashes and the signal-to-noise ratio (SNR) measured by a 10 MHz ADV. Small portions of ashes were added in steps (0.006–20 gl−1) into a stirred water tank while ADV was recording changes in SNR, with various combinations of ADV settings, which included power (LOW, LOW+), transmit length (TL = 0.3 mm, 0.6 mm) and frequencies of data acquisition (25 Hz, 100 Hz). Samples were collected for gravimetric and particle size distribution (PSD) analysis. As expected, the salinity and pH of the collected samples increased with SSC. Different backscatter responses were detected depending on the ADV settings and SSC. To maximize the calibration range, the ADV settings power LOW+, TL = 0.3 mm and sample frequency 25 Hz were combined, resulting in a calibrated SSC range of 10–500 mgl−1, where a linear relationship was obtained. The results suggest that it may be possible to apply a single-frequency acoustic technique to the detection of suspended ashes. The particle type and size distribution changed with a concentration above 0.5 gl−1, which may lead to errors in the acoustic estimates of SSC in ash-laden flows.

Geological evolution of offshore pollution and its long-term potential impacts on marine ecosystems

Populations and metropolitan centers are accumulated in coastal areas around the world. In view of the fact that they are geographically adjacent to coasts and intense anthropogenic activities, increasing global offshore pollution has been an important worldwide concern over the past several decades and has become a very serious problem that needs to be addressed urgently. Due to offshore pollution, various geological disasters occur in high frequency, including intensified erosion and salinization of coastal soils, frequent geological collapses and landslides and increasing seismic activities. Moreover, offshore pollution shows increasingly serious impacts on the topography and geomorphology of offshore and coastal areas, including coastal degradation, retreating coastlines and estuary delta erosion. Offshore sedimentation processes are strongly influenced by the pH changes of terrestrial discharges, and sedimentary dynamics have become extremely acute and complex due to offshore pollution. The seabed topography and hydrodynamic environment determine the fate and transport of pollutants entering offshore regions. Coastal estuaries, port basins and lagoons that have relatively moderate ocean currents and winds are more likely to accumulate pollutants. Offshore regions and undersea canyons can be used as conduits for transporting pollutants from the continent to the seabed. It is particularly noteworthy that the spatial/temporal distribution of species, community structures, and ecological functions in offshore areas have undergone unprecedented changes in recent decades. Due to increasing offshore pollution, the stable succession and development trend of marine ecosystems has been broken. It is thus important to identify and regulate the quantity, composition and transportation of pollutants in offshore regions and their behavior in marine ecosystems. In particular, crucial actions for stabilizing marine ecosystems, including increasing species and biodiversity, should be implemented to enhance their anti-interference capabilities. This review provides an overview of the current situation of offshore pollution, as well as major trends of pollutant fate and transportation from continent to marine ecosystems, transformation of pollutants in sediments, and their bioaccumulation and diffusion. This study retrospectively reviews the long-term geological evolution of offshore pollution from the perspective of marine geology, and analyses their long-term potential impacts on marine ecosystems. Due to ecological risks associated with pollutants released from offshore sediments, more research on the influence of global offshore pollution based on marine geology is undoubtedly needed.

Drought Reduces Release of Plant Matter Into Dissolved Organic Matter Potentially Restraining Ecosystem Recovery

Future climate scenarios indicate increasing drought intensity that threatens ecosystem functioning. However, the behavior of ecosystems during intense drought, such as the 2018 drought in Northern Europe, and their respective response following rewetting is not fully understood. We investigated the effect of drought on four different vegetation types in a temperate climate by analyzing dissolved organic matter (DOM) concentration and composition present in soil leachate, and compared it to two accompanying years. DOM is known to play an important role in ecosystem recovery and holds information on matter flows between plants, soil microorganisms and soil organic matter. Knowledge about DOM opens the possibility to better disentangle the role of plants and microorganisms in ecosystem recovery. We found that the average annual DOM concentration significantly decreased during the 2018 drought year compared to the normal year. This suggests a stimulation of DOM release under normal conditions, which include a summer drought followed by a rewetting period. The rewetting period, which holds high DOM concentrations, was suppressed under more intense drought. Our detailed molecular analysis of DOM using ultrahigh resolution mass spectrometry showed that DOM present at the beginning of the rewetting period resembles plant matter, whereas in later phases the DOM molecular composition was modified by microorganisms. We observed this pattern in all four vegetation types analyzed, although vegetation types differed in DOM concentration and composition. Our results suggest that plant matter drives ecosystem recovery and that increasing drought intensity may lower the potential for ecosystem recovery.

Ecosystem guidance for the incorporation of renewable utilities in a multi-use campus network.

Configuring the network connections in industrial, power, and water networks to mimic the structural patterns of ecological food webs has been shown to improve the resilience of human networks. This work investigates the ability of food web inspiration to specifically guide the incorporation of renewable energy and water sources for resilience. Feasibility is tested using the water and electricity networks of the Texas A&M University main campus, demonstrating the potential of university campus case studies as analogies for other multi-use networks, such as cities or industrial-commercial regions, due to the variety of functions met within the system boundaries. Ecological robustness, the unique and characteristic behavior of ecosystems to slightly favor redundancy over efficiency, is used to correlate the incorporation and supply-levels of solar power and rainwater collection in a realistic campus model with the overall resilience of the electricity and domestic water networks. Non-obviously, the results suggest that the ecologically-similar resilience is achieved when less than 100% of utilities come from renewable sources, indicating an important potential tradeoff between efforts to shift to 100% renewable sources and network resilience concerns.

Review essay: Perils of aggregating a global zeitgeist

This essay reviews the works ‘The Digital Frontier: Infrastructures of Control on the Global Web’ (Indiana University Press) by Sangeet Kumar and ‘The Platform Society: Public Values in a Connective World’ (Oxford University Press) by José van Dijck, Thomas Poell, and Martijn de Waal as recent contributions to the field of global internet studies. The essay explores how each book formulates the interplay between technological infrastructures and the social architecture that guide human behavior in contemporary digital ecosystems.

Fuel reduction treatments reduce modeled fire intensity in the sagebrush steppe

AbstractIncreased fire size and frequency coupled with annual grass invasion pose major challenges to sagebrush (Artemisia spp.) ecosystem conservation, which is currently focused on protecting sagebrush community composition and structure. A common strategy for mitigating potential fire is to use fuel treatments that alter the structure and amount of burnable material, thus reducing fire behavior and creating access points for fire suppression resources. While there is some recent information on the impacts of fuel treatments on ecological communities, we have little information on fuel treatment effectiveness at modifying fire behavior in sagebrush ecosystems. We present 10 years of data on fuel accumulation and the resultant modeled fire behavior in prescribed fire, mowed, herbicide (tebuthiuron or imazapic), and untreated control plots in the Sagebrush Treatment Evaluation Project (SageSTEP) network in the Great Basin, USA. Fuel data (i.e., aboveground burnable live and dead biomass) were collected in each treatment plot at Years 0 (pretreatment), 1, 2, 3, 6, and 10 posttreatment. We used the Fuel and Fire Tool fire behavior modeling program to test whether treatments impacted potential fire behavior. Prescribed fire initially removed 49% of the total fuel load and 75% of shrubs, and fuel loads remained reduced through Year 10. Mowing shifted fuels from the shrub canopy to the ground surface but did not change the total fuel amount. Prescribed fire and mowing increased herbaceous fuel by the second posttreatment year and that trend persisted through Year 10. Tebuthiuron treatments were ineffective at altering fuel loads. Imazapic suppressed herbaceous vegetation by 30% in Years 2 and 3 following treatment. The modified fuel beds in fire and mow treatments resulted in modeled flame lengths that were significantly lower than untreated control plots for the duration of the study, with shorter term reductions in reaction intensity and rate of spread. Understanding fuel treatment effectiveness will allow natural resource managers to evaluate trade‐offs between protecting wildlife habitat and reducing the potential for high‐intensity wildfire.

Analysis and control of a delayed population model with an Allee effect

Based on the population model with an Allee effect, the corresponding delayed model is built up. According to the qualitative theory of differential equations, the model is analyzed completely to describe various intriguing dynamic properties as singular point of high order, Hopf bifurcation, etc. Next, combined impulse control theory with the ecological principles, the control models with impulse effects are proposed and the corresponding controllers are designed not only to avoid the extinction of the populations but also to prevent outbreak of the populations. The study would not only reveal the complexity dynamic behavior of ecosystems, but also provide the theory reference for the management of populations.

Gradients and consequences of heterogeneity in biofilms.

Historically, appreciation for the roles of resource gradients in biology has fluctuated inversely to the popularity of genetic mechanisms. Nevertheless, in microbiology specifically, widespread recognition of the multicellular lifestyle has recently brought new emphasis to the importance of resource gradients. Most microorganisms grow in assemblages such as biofilms or spatially constrained communities with gradients that influence, and are influenced by, metabolism. In this Review, we discuss examples of gradient formation and physiological differentiation in microbial assemblages growing in diverse settings. We highlight consequences of physiological heterogeneity in microbial assemblages, including division of labour and increased resistance to stress. Our impressions of microbial behaviour in various ecosystems are not complete without complementary maps of the chemical and physical geographies that influence cellular activities. A holistic view, incorporating these geographies and the genetically encoded functions that operate within them, will be essential for understanding microbial assemblages in their many roles and potential applications.

Evidences of soil warming from long-term trends (1951\u20132018) in North Rhine-Westphalia, Germany

Soil temperature (ST) is an important property of soils and driver of below ground biogeochemical processes. Global change is responsible that besides variable meteorological conditions, climate-driven shifts in ST are observed throughout the world. In this study, we examined long-term records in ST by a trend decomposition procedure from eleven stations in western Germany starting from earliest in 1951 until 2018. Concomitantly to ST data from multiple depths (5, 10, 20, 50, and 100 cm), various meteorological variables were measured and included in the multivariate statistical analysis to explain spatiotemporal trends in soil warming. A significant positive increase in temperature was more pronounced for ST (1.76 ± 0.59 °C) compared with air temperature (AT; 1.35 ± 0.35 °C) among all study sites. Air temperature was the best explanatory variable to explain trends in soil warming by an average 0.29 ± 0.21 °C per decade and the trend peaked during the period from 1991–2000. Especially, the summer months (June to August) contributed most to the soil warming effect, whereby the increase in maximum ST (STmax) was nearby fivefold with 4.89 °C compared with an increase of minimum ST (STmin) of 1.02 °C. This widening between STmax and STmin fostered enhanced diurnal ST fluctuations at ten out of eleven stations. Subsoil warming up to + 2.3 °C in 100-cm depth is critical in many ways for ecosystem behavior, e.g., by enhanced mineral weathering or organic carbon decomposition rates. Thus, spatiotemporal patterns of soil warming need to be evaluated by trend decomposition procedures under a changing climate.Graphical abstract

Variability of Phenological Behaviours of Wild Fruit Tree Species Based on Discriminant Analysis.

Vegetation phenology is considered an important biological indicator in understanding the behaviour of ecosystems and how it responds to environmental cues. The aim of this paper is to provide information on the variability of phenological behaviours based on discriminant analysis using the R software package with the following libraries: ggplot2, heplots, candisc, MASS, car, and klaR. Three phenological phases were analysed with eight wild fruit tree species from a forest ecosystem in the southwestern part of Romania (44°05′19.5” N 23°54′03.5” E). It was found that there is a large and very large variability for the “bud burst” phenophase, medium and low for “full flowering”, and reduced for the “all petals fallen” phenophase. For the analyzed data, the discriminant analysis model has high accuracy (accuracy: 0.9583; 95% CI: (0.7888, 0.9989). Partition plots show the results of “full flowering” and “all petals fallen” as a function of the “bud burst” of pockmarks when separated into eight clusters and eight clusters of “full flowering” as a function of “all petals fallen”. The differences observed, from a phenological point of view, are not only due to the different cold requirements of these species but also to the temperatures during the spring.

Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and Advanced Erosion Modeling in Malesina, Central Greece

Earth’s ecosystems are extremely valuable to humanity, playing a key role ecologically, economically, and socially. Wildfires constitute a significant threat to the environment, especially in vulnerable ecosystems, such as those that are commonly found in the Mediterranean. Due to their strong impact on the environment, they provide a crucial factor in managing ecosystems behavior, causing dramatic modifications to land surface processes dynamics leading to land degradation. The soil erosion phenomenon downgrades soil quality in ecosystems and reduces land productivity. Thus, it is imperative to implement advanced erosion prediction models to assess fire effects on soil characteristics. This study focuses on examining the wildfire case that burned 30 km2 in Malesina of Central Greece in 2014. The added value of remote sensing today, such as the high accuracy of satellite data, has contributed to visualizing the burned area concerning the severity of the event. Additional data from local weather stations were used to quantify soil loss on a seasonal basis using RUSLE modeling before and after the wildfire. Results of this study revealed that there is a remarkable variety of high soil loss values, especially in winter periods. More particularly, there was a 30% soil loss rise one year after the wildfire, while five years after the event, an almost double reduction was observed. In specific areas with high soil erosion values, infrastructure works were carried out validating the applied methodology. The approach adopted in this study underlines the significance of using remote sensing and geoinformation techniques to assess the post-fire effects of identifying vulnerable areas based on soil erosion parameters on a local scale.

BASIN-3D: A brokering framework to integrate diverse environmental data

Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, particularly due to differences in the structure and formats of data provided by various sources. Here, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a data integration framework designed to dynamically retrieve and transform heterogeneous data from different sources into a common format to provide an integrated view. BASIN-3D enables users to adopt a standardized approach for data retrieval and avoid customizations for the data type or source. We demonstrate the value of BASIN-3D with two use cases that require integration of data from regional to watershed spatial scales. The first application uses the BASIN-3D Python library to integrate time-series hydrological and meteorological data to provide standardized inputs to analytical and machine learning codes in order to predict the impacts of hydrological disturbances on large river corridors of the United States. The second application uses the BASIN-3D Django framework to integrate diverse time-series data in a mountainous watershed in East River, Colorado, United States to enable scientific researchers to explore and download data through an interactive web portal. Thus, BASIN-3D can be used to support data integration for both web-based tools, as well as data analytics using Python scripting and extensions like Jupyter notebooks. The framework is expected to be transferable to and useful for many other field and modeling studies.

The Hg behaviors in mangrove ecosystems revealed by Hg stable isotopes: a case study of Maowei mangrove.

As one of the most productive marine ecosystems in the tropics and subtropics, mangroves are an important part of the global mercury (Hg) cycling. The environmental processes and effects of Hg in mangroves are complex and affect human Hg exposure, and it is crucial to understand Hg behaviors in the mangrove ecosystem. However, clarifying Hg behaviors in the mangrove ecosystem remains difficult because of an insufficient understanding of the dominant pathways. In this study, measurements of mercury (Hg) concentration and isotope ratios in sediment and plant tissues from a mangrove wetland were used to investigate Hg isotope fractionation in mangrove plants and sediments. Spatial patterns in Hg concentration and isotope signatures indicate that Hg re-emission in the sediment was suppressed by mangrove plants. The ratio of Δ199Hg/Δ201Hg was 0.93 for all sediments, indicating that Hg mass-independent fractionation in the mangrove ecosystem was primarily affected by photoreduction, while the ratios of Δ199Hg/Δ201Hg and Δ199Hg/δ202Hg for plant tissues suggested that natural organic matter reduction of Hg(II) was occurred in the plants. The distinct positive Δ199Hg values found in mangrove plants were supposed to be the results of the unique physiological characteristics of mangroves. The exterior Hg sources from atmosphere and seawater emphasize the role of mangrove ecosystems in the global Hg biogeochemistry. Our study highlights the distinct Hg isotope signatures in the mangrove from that in forests and indicates unique Hg behaviors in the mangrove ecosystem.

Seasonal Vegetation Response to Climate Variability on Land use Land Cover Changes using In-Situ and Satellite Imagery Observation Data for Semi-Arid Maasai Mara National Reserve Rangeland Ecosystem, Kenya

Monitoring vegetation response through enhanced change detection by remote sensing and geographical information systems has tremendously improved real time information on surface features. Over the last few decades biomass monitoring at large scale has been made possible from information and metrics derived from satellite sensors. Maasai Mara National Reserve has been utilized in many decades as Kenyan natural grassland for wildlife grazing without periodic assessment of biomass production as affected by impact of climate variability yet it’s a tourism hub and one Kenyan economic contributor. This research evaluates the use of high spatial resolution satellite imagery such as the Moderate Resolution Imaging Spectro-radiometer or the Project for On-Board Autonomy–Vegetation and latest SENTINEL-2 for deriving the Normalized Difference Vegetation Index values in relations to in-situ measurements of biomass production between 2009 and 2019 in Mara, Kenya. Area frame sampling of biomass per unit area in Kgha-1clipped from 50cm by 50cm quadrats were used in destructive sampling. The reserve grassland area coverage was estimated to be 717.203km2 (46.75%) where the in-situ total above ground grass biomass projected in dry season was 35.094 tonha-1. This was approximated as 2,516,952.208 tonnes per the season reserve cover while in wet season, 42.123 tonha-1 was approximated as 3,021,074.197 tonnes. The error matrices developed to assess the accuracies of the ecosystem classification indicated values that ranged between 80-100% and 87.5-100% for producer’s and user’s accuracy respectively. 3 out of 7 satellite imagery maps (2017, 2018, and 2019) were assessed for accuracy using reference data collected during fieldwork in 2018 and 2019 in ecosystem. The overall accuracy was 95.22% with Kappa index of 0.94 for 14 land cover classes shown in table 7. From the findings, potential factors influencing vegetation growth in different climatic regions are varied and complex. It can be noted that climate variability influence vegetation response in spatial scale to supply sustainable quality vegetation/pasture for wildlife feeds and ecosystem development. Vegetation mapping and monitoring of ecosystem behavior help stakeholders with information of vegetation characteristics Decision policy formulation and wildlife planning.

How wild bees find a way in European cities: Pollen metabarcoding unravels multiple feeding strategies and their effects on distribution patterns in four wild bee species

Abstract Urban ecosystems can sustain populations of wild bees, partly because of their rich native and exotic floral resources. A better understanding of the urban bee diet, particularly at the larval stage, is necessary to understand biotic interactions and feeding behaviour in urban ecosystems, and to promote bees by improving the management of urban floral resources. We investigated the larval diet and distribution patterns of four solitary wild bee species with different diet specialization (i.e. Chelostoma florisomne, Osmia bicornis, Osmia cornuta and Hylaeus communis) along urban intensity gradients in five European cities (Antwerp, Paris, Poznan, Tartu and Zurich) using two complementary analyses. Specifically, using trap‐nests and pollen metabarcoding techniques, we characterized the species' larval diet, assessed diet consistency across cities and modelled the distribution of wild bees using species distribution models (SDMs). Our results demonstrate that urban wild bees display different successful strategies to exploit existing urban floral resources: not only broad generalism (i.e. H. communis) but also intermediate generalism, with some degree of diet conservatism at the plant family or genus level (i.e. O. cornuta and O. bicornis), or even strict specialization on widely available urban pollen hosts (i.e. C. florisomne). Furthermore, we detected important diet variation in H. communis, with a switch from an herbaceous pollen diet to a tree pollen diet with increasing urban intensity. Species distribution modelling indicated that wild bee distribution ranges inside urban ecosystems ultimately depend on their degree of specialization, and that broader diets result in less sensitivity to urban intensity. Policy implications. Satisfying larval dietary requirements is critical to preserving and enhancing wild bee distributions within urban gradients. For high to intermediate levels of feeding specialization, we found considerable consistency in the preferred plant families or genera across the studied cities, which could be generalized to other cities where these bees occur. Identifying larval floral preferences (e.g. using pollen metabarcoding) could be helpful for identifying key plant taxa and traits for bee survival and for improving strategies to develop bee‐friendly cities.

Partitioning evapotranspiration based on the total ecosystem conductance fractions of soil, interception, and canopy in different biomes

Partitioning evapotranspiration (ET) into soil evaporation (Esoil), canopy interception evaporation (Eic), and transpiration (T) yields both comprehensive insight into hydrological processes and better water management, but it is challenging. This study proposes a modified ecosystem conductance-based Priestley-Taylor (MEC-PT) algorithm for ET partitioning based on the total ecosystem conductance (GTotal) fractions of soil, interception, and canopy. Datasets from 24 flux towers around the world were used to estimate GTotal by coupling aerodynamic conductance and surface conductance (Gs). Results from the MEC-PT model were compared with those from an original best-fit ecosystem-level conductance (m-order) model that only partitions Gs into soil and canopy domains. The superior performance of the MEC-PT model, with the inclusion of an intercepted contributor and ability to fill the data gap associated with the m-order during wet conditions, describes the robustness of this approach for partitioning ET. The MEC-PT model results might reflect dew formation that produces minimal Eic volume under non-rainfall conditions with support from the diurnal temperature (DT) presence. The ratio of T to total ET (T/ET) was found highest in forest with 0.72 (±0.17 of standard deviation), followed by savanna (0.57 ± 0.11), cropland (0.48 ± 0.10), and grassland (0.39 ± 0.17). Also, sensitivity analysis was conducted with main input variables of the MEC-PT and m-order models over four land cover types and the whole study period of each site used in this study. The results demonstrated that, in general conditions, net radiation was the key driver controlling T/ET variations, whereas air temperature and wind speed indirectly and slightly affected T/ET. This study underlines that the inclusion of Eic might bridge the gap in knowledge about ET and its components regarding canopy dynamics and ecosystem behaviors in the context of climate change.

Three-dimensional dynamic characteristics of vegetation and its response to climatic factors in the Qilian Mountains

Understanding the trend of vegetation change and its reaction to climate variation is important for revealing the mechanism of ecosystem behavior. However, current research rarely systematically analyzes the time effects of climate variation on vegetation dynamics (time-lag and time-accumulation effects), especially in arid and semi-arid mountainous terrain. The typical mountainous terrain—the Qilian Mountains was taken as the study area, and the spatiotemporal changes and vertical zonality distributions of the normalized vegetation index (NDVI) were explored. This study explored the time-lag and time-accumulation effects of the NDVI response to climate factors (precipitation, temperature), identified the main controlling factors that influence the variation of NDVI. The results show that in the growing season from 2000 to 2019, the NDVI represented an overall upward trend, especially in the northwest, and the growth rate of NDVI at low-altitude was greater. The time-accumulation effect of precipitation has an obvious effect on vegetation, especially on deserta and meadow; and the time-lag and time-accumulation effects of temperature have an obvious influence. Regarding the climate-vegetation response mechanism, this study finds that considering the optimal time effect is of great significance. In addition, compared with precipitation, the temperature has a more significant promotion effect on vegetation growth in the Qilian Mountains. The above results indicate that when the existing climate models study vegetation-climate interactions, considering the time effects of vegetation response to climate is of great significance for accurately monitoring vegetation dynamics under environmental changes.

Production, stability and degradation of Trichoderma gliotoxin in growth medium, irrigation water and agricultural soil

Gliotoxin produced by Trichoderma virens is inhibitory against various phytopathogenic fungi and bacteria. However, its stability in soil-ecosystem has not yet been well-defined. This study aimed to decipher its persistence and behaviour in growth media, irrigation water and soil ecosystems. Gliotoxin production was noticed at logarithmic growth phase and converted into bis-thiomethyl gliotoxin at late stationary growth phase of T. virens in acidic growth medium. But, no gliotoxin production was observed in neutral and alkaline growth medium. Gliotoxin was stable for several days in acidic water but degraded in alkaline water. Degradation of gliotoxin was more in unsterile soil than sterile soil and also that was higher under wet soil than dry soil. Degradation of gliotoxin was hastened by alkaline pH in wet soil but not in dry soil. Under unsterile soil conditions, high soil moisture increased the degradation of gliotoxin and the degradation of gliotoxin occurred quickly in alkaline soil (in 5 days) compared to acidic soil (in 10 days). Under sterile soil conditions, high soil moisture also enhanced the degradation of gliotoxin but level of degradation was less compared to unsterile conditions. Thus, gliotoxin stability is influenced mainly by the soil wetness, soil microbial community and pH conditions.

Climate Change Induced Trends and Uncertainties in Phytoplankton Spring Bloom Dynamics

Spring phytoplankton blooms in the southern North Sea substantially contribute to annual primary production and largely influence food web dynamics. Studying long-term changes in spring bloom dynamics is therefore crucial for understanding future climate responses and predicting implications on the marine ecosystem. This paper aims to study long term changes in spring bloom dynamics in the Dutch coastal waters, using historical coastalin-situdata and satellite observations as well as projected future solar radiation and air temperature trajectories from regional climate models as driving forces covering the twenty-first century. The main objective is to derive long-term trends and quantify climate induced uncertainties in future coastal phytoplankton phenology. The three main methodological steps to achieve this goal include (1) developing a data fusion model to interlace coastalin-situmeasurements and satellitechlorophyll-aobservations into a single multi-decadal signal; (2) applying a Bayesian structural time series model to produce long-term projections of chlorophyll-a concentrations over the twenty-first century; and (3) developing a feature extraction method to derive the cardinal dates (beginning, peak, end) of the spring bloom to track the historical and the projected changes in its dynamics. The data fusion model produced an enhanced chlorophyll-a time series with improved accuracy by correcting the satellite observed signal within-situobservations. The applied structural time series model proved to have sufficient goodness-of-fit to produce long term chlorophyll-a projections, and the feature extraction method was found to be robust in detecting cardinal dates when spring blooms were present. The main research findings indicate that at the study site location the spring bloom characteristics are impacted by the changing climatic conditions. Our results suggest that toward the end of the twenty-first century spring blooms will steadily shift earlier, resulting in longer spring bloom duration. Spring bloom magnitudes are also projected to increase with a 0.4%year−1trend. Based on the ensemble simulation the largest uncertainty lies in the timing of the spring bloom beginning and -end timing, while the peak timing has less variation. Further studies would be required to link the findings of this paper and ecosystem behavior to better understand possible consequences to the ecosystem.

Estimating fine-scale visibility in a temperate forest landscape using airborne laser scanning

Visibility is a key factor influencing animal behavior in forest ecosystems. Fine-scale visibility in forested areas has been measured by ground-based approaches at the plot level, using site-specific methods that have limited spatial coverage. Here we examine airborne laser scanning (ALS) as a novel tool to quantify fine-scale visibility in the temperate forests of Germany at a landscape scale. We validate the (vertically-derived) ALS-derived visibility measures using proven (horizontally-derived) terrestrial laser scanning (TLS) estimates of true visibility. Our results indicate that there is a good agreement between the visibility resulting from ALS and TLS with an R2 ranging from 0.53 to 0.84 and a normalized RMSE varying from 15.92% to 11.81% at various plot sizes, with the highest accuracy achieved using a plot size of 35 × 35 m. Our study demonstrates for the first time that ALS can be successfully applied to quantify fine-scale visibility in temperate forests at a landscape level. This approach holds potential for studying the spatial behavior of animals (e.g., habitat selection and predator–prey relationships) in forest ecosystems.