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Ecosystems of actors that need to interact to create value for end users are becoming an integral part of firms' strategic realities as they reach new markets. However, the phenomenon of ecosystem internationalisation has not been explored in comparison to its practical prevalence. We conceptualise this phenomenon as agent-led structuration on new markets. We build on the structural ecosystem literature and literature on internationalisation challenges to create our recursive process model of ecosystem creation on foreign markets. Creating ecosystems on foreign markets necessitates new ecosystem structures that are adjusted to value propositions by orchestrators through interaction with foreign market actors. The model explains how ecosystem orchestrators drive the international expansion of ecosystems through blueprinting and aligning mechanisms and how these mechanisms help manage liabilities of foreignness. The model accounts for the agency of involved actors, and with the help of the bottleneck concept bridges international business and ecosystem literatures. [ABSTRACT FROM AUTHOR]

Tropical reef ecosystems are strongly influenced by the composition of coral species, but the factors influencing coral diversity and distributions are not fully understood. Here we demonstrate that large variations in the relative abundance of three major coral species across adjacent Caribbean reef sites are strongly related to their different low O2 tolerances. In laboratory experiments designed to mimic reef conditions, the cumulative effect of repeated nightly low O2 drove coral bleaching and mortality, with limited modulation by temperature. After four nights of repeated low O2, species responses also varied widely, from > 50% bleaching in Acropora cervicornis to no discernable sensitivity of Porites furcata. A simple metric of hypoxic pressure that combines these experimentally derived species sensitivities with high‐resolution field data accurately predicts the observed relative abundance of species across three reefs. Only the well‐oxygenated reef supported the framework‐building hypoxia‐sensitive Acropora cervicornis, while the hypoxia‐tolerant weedy species Porites furcata was dominant on the most frequently O2‐deplete reef. Physiological exclusion of acroporids from these O2‐deplete reefs underscores the need for hypoxia management to reduce extirpation risk. [ABSTRACT FROM AUTHOR]

Grasslands are among the most imperilled ecosystems worldwide, and many have experienced degradation due to the loss of historical disturbance regimes and subsequent woody encroachment. Management practitioners often use physical and chemical management interventions in combination with fire to counter encroachment, altering aboveground structure and belowground function, respectively. This may disrupt the feedbacks that perpetuate encroachment and restore the herbaceous community.We use a large‐scale field experiment to assess the initial effects of different management interventions on woody vegetation persistence, abiotic habitat conditions, and herbaceous community composition. We evaluate these effects across seven sites spanning a natural soil moisture gradient to capture one aspect of environmental heterogeneity with which managers regularly contend.We found that chemical intervention, both with and without the addition of physical intervention, was most effective at reducing woody plant cover and abundance, and a second application reduced woody plant abundance by more than one application alone. We also found that any management intervention increased light availability and air temperature and decreased soil moisture, with the combination of physical and chemical interventions having the greatest effects. Finally, none of the management interventions affected herbaceous richness and functional group cover within the study period, indicating delayed or nonexistent effects on herbaceous community composition.Synthesis and application. Our findings suggest that management should focus on chemical intervention for the greatest effects on woody plant persistence and abiotic habitat conditions. Changes to herbaceous community composition may occur in the long term and seem likely since short‐term effects of management were successful in altering processes related to encroachment feedbacks. [ABSTRACT FROM AUTHOR]

Plants adopt particular growth‐forms when they are exposed to extreme environmental conditions. In this study, we describe a unique woody plant growth‐form induced by large mammalian herbivores and discuss that this growth‐form could have evolved as a strategy for escaping the browser zone in herbivore driven ecosystems.We analysed responses of key architectural and morphological attributes (branching and thorn density, tree dimensions, presence of flowers and fruits) of three Eurasian spiny tree species (Malus sylvestris, Prunus cerasifera and Pyrus communis) to different levels of browsing by large herbivores in the temperate Białowieża Forest, Poland.Under high browsing pressure, studied trees displayed two distinct forms of the crown: a bottom sterile part developing into a densely branched structure with high density of thorns ('cage‐form'), and an upper reproductive part that escaped from herbivore control ('escaped‐form'). The size of cage‐form influenced the feeding behaviour of red deer (Cervus elaphus) by increasing the time deer spend foraging and increasing the bite rate. The height at which cages started to escape and their diameter matched with foraging reach of red deer.Synthesis. We argue that the frequency and cage dimensions of this woody growth‐form in the landscape could inform on the type and intensity of recent herbivory. Moreover, its distinctive inducibility suggests that this growth‐form did not emerge recently under anthropogenic pressure but could be the legacy of ancient herbivory effects. Observational evidence suggests that this growth‐form emerged in several herbivore‐driven systems around the globe and may be used to identify the dominant herbivores that control vegetation structure in these ecosystems. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Species' habitats are strongly influenced by the 3‐dimensional (3D) structure of ecosystems. The dominant technique used to measure 3D structure is Airborne Laser Scanning (ALS), a type of LiDAR (Light Detection and Ranging) technology. Airborne Laser Scanning captures fine‐scale structural information over large spatial extents and provides useful environmental predictors for habitat modeling. However, due to technical complexities of processing ALS data, the full potential of ALS is not yet realized in wildlife research, with most studies relying on a limited set of 3D predictors, such as vegetation metrics developed principally for forestry applications. Here, we highlight the full potential of ALS data for wildlife research and provide insight into how it can be best used to capture the environmental conditions, resources, and risks that directly determine a species' habitat. We provide a nontechnical overview of ALS data, covering data considerations and the modern options available for creating custom, ecologically relevant, ALS predictors. Options included the following: i) direct point cloud approaches that measure structure using grid, voxel, and point metrics, ii) object‐based approaches that identify user‐defined features in the point cloud, and iii) modeled environmental predictors that use additional modeling to infer a range of habitat characteristics, including the extrapolation of field acquired measurements over ALS data. By using custom ALS predictors that capture species‐specific resources, risks, and environmental conditions, wildlife practitioners can produce models that are tailored to a species' ecology, have greater biological realism, test a wider range of species‐environment relationships across scales, and provide more meaningful insights to inform wildlife conservation and management. [ABSTRACT FROM AUTHOR]

Recently, there has been a surge of interest in developing innovation ecosystems within targeted industry sectors to enhance national industry capabilities. However, academic discussions on innovation ecosystems within a sectoral context are notably lacking. Past research has primarily focused on innovation ecosystems centered around a single organization, initiated and led by the same organization. This study aims to address this gap by examining the enablers of sectoral innovation ecosystems (SIE) development. A systematic literature review was conducted using 57 empirical studies from the Web of Science database between 2010-2023. The study proposes a conceptual framework with three critical enablers for developing SIE: (1) Structural configurations (structural constructs and structural alignment), (2) capabilities (organizational capabilities and ecosystem capabilities), and (3) interactions (nature of interactions and drivers of interactions). This framework provides a comprehensive understanding of how sectoral innovation ecosystems can be structured and managed to enhance industry capabilities. The study underscores the pivotal role of intermediary organizations in orchestrating SIE development, highlighting their importance in facilitating interactions and aligning structures within the ecosystem. By advocating for the complementary use of structure-based and coevolution-based approaches, the study offers a dual perspective that enriches the theoretical understanding of SIE. The systematic literature review concludes with recommendations for future research, providing a pathway for further exploration of SIE.

Ecosystem structure and its heterogeneity shape ecosystem processes. Ecosystem heterogeneity has been characterized in smaller stream ecosystems dominated by benthic processes. However, in larger river ecosystems structured by water column characteristics including suspended sediment and phytoplankton, ecosystem heterogeneity has not been directly observed. We assessed flow‐dependent ecosystem structure along 230 km of a large, highly managed Great Plains river (The Kansas River) by analyzing 1‐dimensional, downstream color profiles across flow conditions derived from satellite imagery. River color is a robust metric that reflects the combined state of several important large‐river habitat features, specifically suspended sediment, chromophoric dissolved organic matter, and phytoplankton. We found that at flows above a flow threshold that we call Qpatch (240 m3 s−1), the entire river was uniformly yellow. At flows below Qpatch, the river was generally greener and often had patches of very green water that occurred upstream of run‐of‐river dams. Comparing color with in situ data showed the color patches were likely areas of elevated chlorophyll‐a concentrations from phytoplankton accumulation, indicating that the patches reflected biological processes. Flows were below Qpatch on 77% of days during the period of record (1985–present), indicating that the ecosystem spends significant time in a patchy state. Our findings uniquely demonstrate that the water column characteristics structuring temperate, large‐river ecosystems can be patchy. Plain Language Summary: An ecosystem represents a collection of smaller areas, or patches, that play different ecological roles. We can see and walk through patches in forests, however within flowing aquatic ecosystems like large rivers, it is difficult to see and characterize patches. Here, we present direct observations of downstream patches along a river and how they change across streamflow conditions. We measure spatial variation using satellite‐derived water color observations as a proxy for ecosystem properties along a highly managed Great Plains river, The Kansas River. Increases in algae floating in the river should make the river greener, while increases in sediment should make the river more yellow. We found that at high flows above a distinct threshold, the entire river was uniformly yellow. At flows below the threshold, the river was greener and often had particularly green patches behind small, in‐river dams. Comparing our color observations with in‐stream sensor measurements indicated that the green patches were likely caused by elevated algae accumulation and not a reduction in sediment. This work thus revealed a surprising feature of large rivers: they may have stable patches created largely by biological processes. Key Points: We use 1‐D profiles of water color on a large, managed Great Plains river to assess shifts in ecosystem structure across flow conditionsThe 77% percentile flow marked a threshold: above, the river was uniformly yellow. Below, the river was greener and showed green patchesIn situ data suggested these green patches were biologically driven, caused by increased phytoplankton growth upstream of run‐of‐river dams [ABSTRACT FROM AUTHOR]

Dam removal is increasingly considered as a river restoration tool for impoundments that harm the environment or have exceeded their lifespan. However, few studies report the ecological consequences of large dam removal.We performed a multiple before‐after/control‐impact (mBACI) study to investigate the consequences of the decommissioning of a large dam (42 m high) on instream habitat and invertebrate communities in a temperate, forested catchment of northern Spain.Before decommissioning, lack of fine sediments and high concentrations of manganese and iron occurred below the dam but decreased downstream. Invertebrate taxa richness and diversity were reduced, and pollution‐sensitive taxa were missing just below the dam.The drawdown of the reservoir, the first step towards its decommissioning, mobilized stored sediments causing frequent turbidity peaks downstream, which nevertheless, caused no detrimental effects on macroinvertebrate communities. One year after drawdown, the communities downstream from the dam, as well as those in the newly formed stream in the area formerly impounded by the reservoir, became very similar to those in control reaches, showing a successful restoration project.Synthesis and applications. Dam decommissioning helps restore instream habitats and facilitates the recovery of invertebrate communities in a very short time frame if there are nearby sources of potential colonizers. Slow drawdown reduces the transport of the sediments accumulated in the reservoir and their potential downstream impacts, even more if prior to drawdown the reservoir is kept full for years to promote the deposition of sediments in marginal areas that will later be readily colonized by trees. [ABSTRACT FROM AUTHOR]

Rocky desertification is a prominent ecological issue in Southwest China's karst region, ranking among the nation's three primary ecological challenges alongside soil erosion and desertification. The government initiated the Rocky Desertification Treatment Program in 2008, lacking a comprehensive evaluation of its benefits. This study evaluates the program's impact on ecosystem services over the last two decades using remote sensing, ecosystem models, and field data. The results indicated a continuous net decrease of rocky desertification, 48% in the eight southwestern provinces from 2005 to 2021. The average annual growth rate of vegetation cover reached 2.54% in key counties for rocky desertification control, significantly higher than that of all the 451 rocky desertification counties from 2016 to 2020. Additionally, ecosystem productivity increased by 35.8% in rocky desertification counties from 2000 to 2020, which is 1.34 times greater than that observed in non‐rocky desertification counties. It was found that the ecosystem service promotion after the net reduction of rocky desertification area in 2010–2020 is more significant, especially the carbon sequestration in 2010–2020 of key counties for rocky desertification control is 2.7 times than that in 2000–2010. It indicates that the rocky desertification treatment enters the stage of ecosystem service promotion on the basis of achieving rapid "greening," leading to significant improvements in ecosystem structures and services in the karst region of Southwest China. To mitigate the risk of rocky desertification, tailored measures must be implemented considering local climate, lithology, landform types, and human–land relations for effective treatment zoning and classification. [ABSTRACT FROM AUTHOR]

Abstract Species' habitats are strongly influenced by the 3‐dimensional (3D) structure of ecosystems. The dominant technique used to measure 3D structure is Airborne Laser Scanning (ALS), a type of LiDAR (Light Detection and Ranging) technology. Airborne Laser Scanning captures fine‐scale structural information over large spatial extents and provides useful environmental predictors for habitat modeling. However, due to technical complexities of processing ALS data, the full potential of ALS is not yet realized in wildlife research, with most studies relying on a limited set of 3D predictors, such as vegetation metrics developed principally for forestry applications. Here, we highlight the full potential of ALS data for wildlife research and provide insight into how it can be best used to capture the environmental conditions, resources, and risks that directly determine a species' habitat. We provide a nontechnical overview of ALS data, covering data considerations and the modern options available for creating custom, ecologically relevant, ALS predictors. Options included the following: i) direct point cloud approaches that measure structure using grid, voxel, and point metrics, ii) object‐based approaches that identify user‐defined features in the point cloud, and iii) modeled environmental predictors that use additional modeling to infer a range of habitat characteristics, including the extrapolation of field acquired measurements over ALS data. By using custom ALS predictors that capture species‐specific resources, risks, and environmental conditions, wildlife practitioners can produce models that are tailored to a species' ecology, have greater biological realism, test a wider range of species‐environment relationships across scales, and provide more meaningful insights to inform wildlife conservation and management.

Introduction: With the continuous changes in climate patterns due to global warming, drought has become an important limiting factor in the development of terrestrial ecosystems. However, a comprehensive understanding of the impact of drought on soil microbial activity at a global scale is lacking. Methods: In this study, we aimed to examine the effects of drought on soil microbial biomass (carbon [MBC], nitrogen [MBN], and phosphorus [MBP]) and enzyme activity (b-1, 4-glucosidase [BG]; b-D-cellobiosidase [CBH]; b-1, 4-Nacetylglucosaminidase [NAG]; L-leucine aminopeptidase [LAP]; and acid phosphatase [AP]). Additionally, we conducted a meta-analysis to determine the degree to which these effects are regulated by vegetation type, drought intensity, drought duration, and mean annual temperature (MAT). Result and discussion: Our results showed that drought significantly decreased the MBC, MBN, and MBP and the activity levels of BG and AP by 22.7%, 21.2%, 21.6%, 26.8%, and 16.1%, respectively. In terms of vegetation type, drought mainly affected the MBC and MBN in croplands and grasslands. Furthermore, the response ratio of BG, CBH, NAG, and LAP were negatively correlated with drought intensity, whereas MBN and MBP and the activity levels of BG and CBH were negatively correlated with drought duration. Additionally, the response ratio of BG and NAG were negatively correlated with MAT. In conclusion, drought significantly reduced soil microbial biomass and enzyme activity on a global scale. Our results highlight the strong impact of drought on soil microbial biomass and carbon- and phosphorus-acquiring enzyme activity. [ABSTRACT FROM AUTHOR]

Remote sensing data are important for assessing ecological change, but their value is often restricted by their limited temporal coverage. Major historical events that affected the environment, such as those associated with colonial history, World War II, or the Green Revolution are not captured by modern remote sensing. In the present article, we highlight the potential of globally available black-and-white satellite photographs to expand ecological and conservation assessments back to the 1960s and to illuminate ecological concepts such as shifting baselines, time-lag responses, and legacy effects. This historical satellite photography can be used to monitor ecosystem extent and structure, species' populations and habitats, and human pressures on the environment. Even though the data were declassified decades ago, their use in ecology and conservation remains limited. But recent advances in image processing and analysis can now unlock this research resource. We encourage the use of this opportunity to address important ecological and conservation questions. [ABSTRACT FROM AUTHOR]

Long-term fishing bans have spurred extensive debate regarding their impacts on ecosystem structures, functions, and water qualities. However, data on the effects of specific changes induced by fishing bans on ecosystem structures, functions, and water qualities in lakes are still lacking. Therefore, the present study addresses this knowledge gap by employing an Ecopath model to assess alterations in an ecosystem's structure and function before (2011) and after (2021) the implementation of the fishing ban in Caohai Lake and its association with changes in water quality. (1) We observed a substantial reduction in the area covered by submerged aquatic vegetation after the ban, amounting to a 65% decrease in coverage compared with that before the ban, and a 60% reduction in the total ecosystem's biomass. (2) Following the ban, the number of fish species increased from 7 to 14, and this was accompanied by a rise in the fish biomass from 14.16 t·km−2 to 25.81 t·km−2; a 4.5-fold increase in the total system consumption was observed, signifying accelerated energy and material flows within the ecosystem. (3) The fishing ban exhibited no significant impact on the total nitrogen concentration; however, it significantly reduced the water's transparency and increased the total phosphorus, ammonia nitrogen, chemical oxygen demand, and chlorophyll contents (p < 0.05). This shift in nutrient dynamics fostered a transformation from a macrophyte-dominant lake to an alga-dominant lake. The fish abundance and diversity increase in closed-type macrophytic lakes, thereby accelerating energy and material flows within food webs. These findings present novel insights into the effective policy management of fishing bans within the Yangtze River Basin, thus enhancing our understanding of sustainable lake ecosystem management. [ABSTRACT FROM AUTHOR]

Abstract Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large‐scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three‐dimensional vegetation structure at local scales. Here we demonstrate the potential of high‐frequency ground‐based laser scanning to systematically monitor structural changes in vegetation. We present a proof‐of‐concept high‐temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high‐temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.

The study of changes in land cover provides a better understanding of the interactions between humans and natural ecosystems. In this context, the present study focused on the dynamics of natural ecosystems in the Rif region of Northern Morocco. The methodology was based on the inspection and visual interpretation of Landsat and Google Earth image captures, the time series of five Landsat 4-8 image bands, and the Tasseled Cap indices for a random sample of 500 points from 1984 to 2022. The study found that changes affected practically the whole study region over the study period, with around a third of them being ignored due to their very tiny magnitudes or being false positives. The findings demonstrated a general declining trend in the measured changes, indicating a reduction in pressure on different ecosystems. Furthermore, this tendency may be due in part to the availability of Google Earth images during the 2000s, which has significantly reduced the number of false positives. In terms of the year of first change, only 5.7% of pixels experienced their first events after the year 2000, implying that these pixels underwent no change for at least the first 16 years of the study period. On the other hand, 2.5% of the pixels had their last events during the first ten years and have thus remained unmodified for at least 27 years. For the year 2020, the confidence rating of the visual land cover categorization is medium to high for 88.9% of pixels using high-resolution Google Earth photos, whereas the classification quality was inadequate for 64% of pixels in 1984. Despite the stresses on the ecosystems structured by shrubs/shrubs, forests, and herbaceous/shrubs caused by the different disturbances identified, the majority of these ecosystems have not been converted to new land cover classes. According to the study, agriculture is the primary driving force underlying the conversion of forests, herbaceous/shrublands, and even shrublands/shrublands. The area increases for the latter three ecosystems represent, on the one hand, their ability to regenerate themselves and, on the other, Morocco's restoration efforts.

The carbon cycle of terrestrial ecosystems is influenced by global climate change and human activities. Using remote sensing data and land cover products, the spatio-temporal variation characteristics and trends of NEP in the Yangtze River Delta from 2000 to 2020 were analyzed based on the soil respiration model. The driving influences of ecosystem structure evolution, temperature, rainfall, and human activities on NEP were studied. The results show that the NEP shows an overall distribution pattern of high in the southeast and low in the northwest. The area of carbon sinks is larger than that of the carbon sources. NEP spatial heterogeneity is significant. NEP change trend is basically unchanged or significantly better. The future change trend in most areas will be continuous decrease. Compared with temperature, NEP are more sensitive to precipitation. The positive influence of human activities on NEP is mainly observed in north-central Anhui and northern Jiangsu coastal areas, while the negative influence is mainly found in highly urbanized areas. In the process of ecosystem structure, the contribution of unchanged areas to NEP change is greater than that of changed areas. [ABSTRACT FROM AUTHOR]

Key message: The multiple functions of Mediterranean forest ecosystems primarily decrease with management operations, and secondarily with tree composition. This finding emphasizes the importance of a suitable management for maintaining ecosystem functioning in Mediterranean forests. In semi-arid ecosystems, forests are critical sites for supporting multifunctionality, which are endangered by multiple environmental stresses. In this regard, understanding how ecosystem multifunctionality (EMF) develops in semi-arid forests is important to set up actions preserving these delicate environments. Changes in species composition and management operations can have heavy effects on the Mediterranean forest ecosystem. To better understand the influence of these drivers on EMF of Mediterranean forests, this study compares ecosystem structure, properties and functions as well as the resulting EMF in four types of forests in Central-Eastern Spain: (1) a pure and unmanaged stand of Spanish black pine, assumed as control; (2) a pure, but managed stand of Spanish black pine; (3) two mixed and unmanaged stands of Spanish black pine and (3.a) Spanish juniper and (3.b) holm oak. Regarding the ecosystem structure, both forest management and stand composition altered plant diversity, but not soil covers (except for vegetation). About the ecosystem properties, soil characteristics significantly changed between pairs of stands (especially texture, pH and bulk density). Concerning the ecosystem functions, forest stand structure was a significant driver of waste decomposition, but not of wood production, while its effect on nutrient cycling, belowground carbon stocks and water cycle was different according to the specific tree species. The impacts of forest management on the ecosystem functions were in general significant compared to the unmanaged stand in terms of wood production, belowground carbon stocks and nutrient cycling, but not of water cycle and waste decomposition. Overall, this study demonstrates that the average EMF is primarily affected by forest management (with a decrease in EMF in managed stands compared to the unmanaged forest), and by stand composition only in the case of one mixed stand. As such, the forest management actions must be carefully adopted, to avoid EMF degradation. [ABSTRACT FROM AUTHOR]

Abstract Remote sensing (RS) and geospatial sciences already amount to a long history of fostering research in topics related to ecology. Data and methods have mainly been subject to research and experiments, but trends are now emerging that suggest the use of RS in practical applications like nationwide monitoring programs and assisting global conservation goals. However, use of active remote sensing for ecological and conservation is in its infancy, and the implications of active sensor data, including light detection and ranging and radio detection and ranging that mostly deliver three‐dimensional (3D) information, are still relatively primitive and have largely been limited to indirect use of their extracted proxies for ecological modelling. This cross‐journal special feature between Methods in Ecology and Evolution, Journal of Animal Ecology, Journal of Applied Ecology and Journal of Ecology includes 18 papers that include full research papers, reviews and technical applications. They are mostly novel in either or both their interpretation of proxies derived from active RS data and the direct usage of 3D RS techniques (terrestrial, airborne, UAV borne and spaceborne) to address ecological topics. We categorized the published contributions into the following thematic groups, with some degree of overlap: (i) ecosystem structural analysis by active data (nine studies); (ii) response of animal populations to climate dynamics as shown by active data; (iii) interactive effects of forest structure and wildlife monitoring (five studies); (iv) forest inventories assisted by active data (one study) and (v) tree type classification by active data (one study). Synthesis. The studies in this Special Feature and trends shown by other recent works at the interface of ecology and active RS confirm the ongoing shift from indirect and solely proxy‐based approaches to direct and more data‐science driven methods in approaching ecology and conservation problems by means of active sensors. Relatively affordable and accessible drone and citizen science‐based on‐demand active RS data acquisition are becoming common practice, and the future of sensor development is hypothesized to go beyond the current domination of very high spatial resolution data and towards multiple spaceborne platforms. These tools and methods will support spatial upscaling, uncertainty analysis, large‐scale mapping and monitoring of wildlife dynamics, among other topics that can take advantage of multitemporal/time series data. Nevertheless, access to demanding and costly very high‐resolution data sources may still be maintained and optimized by establishing international and public–private partnered data pools.

IntroductionAn unprecedented amount of Earth Observations and in-situ data has become available in recent decades, opening up the possibility of developing scalable and practical solutions to assess and monitor ecosystems across the globe. Essential Biodiversity Variables are an example of the integration between Earth Observations and in-situ data for monitoring biodiversity and ecosystem integrity, with applicability to assess and monitor ecosystem structure, function, and composition. However, studies have yet to explore how such metrics can be organized in an effective workflow to create a composite Ecosystem Integrity Index and differentiate between local plots at the global scale.MethodsUsing available Essential Biodiversity Variables, we present and test a framework to assess and monitor forest ecosystem integrity at the global scale. We first defined the theoretical framework used to develop the workflow. We then measured ecosystem integrity across 333 forest plots of 5 km2. We classified the plots across the globe using two main categories of ecosystem integrity (Top and Down) defined using different Essential Biodiversity Variables.Results and discussion:We found that ecosystem integrity was significantly higher in forest plots located in more intact areas than in forest plots with higher disturbance. On average, intact forests had an Ecosystem Integrity Index score of 5.88 (CI: 5.53–6.23), whereas higher disturbance lowered the average to 4.97 (CI: 4.67–5.26). Knowing the state and changes in forest ecosystem integrity may help to deliver funding to priority areas that would benefit from mitigation strategies targeting climate change and biodiversity loss. This study may further provide decision- and policymakers with relevant information about the effectiveness of forest management and policies concerning forests. Our proposed method provides a flexible and scalable solution that facilitates the integration of essential biodiversity variables to monitor forest ecosystems.

Understanding the future of Southern Ocean ecosystems requires approaches at micro to macro scales. The Southern Ocean has experienced both top-down and bottom-up perturbations driven by man. The removal of whales and finfish was a top-down disruption, removing enormous levels of biomass of consumers and driving competitive release for other predators. In contrast, climate change is altering physical conditions in complex, interrelated ways likely to change primary-producer community structure, with bottom-up consequences for the efficiency of energy transfer to top predators, and for the biological pump. The physiological effects of increasing ocean temperatures on animal species are likely to be less important than three key physical changes: loss of sea ice, changes to water-column stability, and patterns of water transport; these will affect krill abundances, primary producer community structure, and prey availability to land-breeding predators, respectively. The Southern Ocean is vast and critically influenced by global teleconnections, with different regions already exhibiting different patterns of physical and biological change. Given the strong physical forcing of these ecosystems, many of the initial consequences of climate change will operate through direct physiological effects on the primary producers and indirect effects on the larger organisms. This will disrupt species interactions and drive new ecological relationships. [ABSTRACT FROM AUTHOR]

In a recent perspective (Diversity and Distributions, 29, 39–50), '10 variables' were proposed to measure vegetation structure from airborne laser scanning (ALS) for assessing species distributions and habitat suitability. We worry about this list because the variables predominantly represent variation in vegetation height, the vertical variability of vegetation biomass is insufficiently captured, and variables of vegetation cover are ill‐defined or not ecosystem agnostic. We urge for a better defined, more comprehensive and more balanced list, and for assessing which information from ALS point clouds is truly essential to measure the major dimensions of 3D vegetation structure within and across ecosystems and animal habitats. We think that the currently proposed 'list of 10 ALS metrics' is premature and that researchers and stakeholders should be cautious in adopting this list. [ABSTRACT FROM AUTHOR]

Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large‐scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three‐dimensional vegetation structure at local scales. Here we demonstrate the potential of high‐frequency ground‐based laser scanning to systematically monitor structural changes in vegetation. We present a proof‐of‐concept high‐temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high‐temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways. [ABSTRACT FROM AUTHOR]

Abstract Lidar‐derived forest structural diversity (FSD) metrics—including measures of forest canopy height, vegetation arrangement, canopy cover (CC), structural complexity and leaf area and density—are increasingly used to describe forest structural characteristics and can be used to infer many ecosystem functions. Despite broad adoption, the importance of spatial resolution (grain and extent) over which these structural metrics are calculated remains largely unconsidered. Often researchers will quantify FSD at the spatial grain size of the process of interest without considering the scale dependency or statistical behaviour of the FSD metric employed. We investigated the appropriate scale of inference for eight lidar‐derived spatial metrics—CC, canopy relief ratio, foliar height diversity, leaf area index, mean and median canopy height, mean outer canopy height, and rugosity (RT)‐‐representing five FSD categories—canopy arrangement, CC, canopy height, leaf area and density, and canopy complexity. Optimal scale was determined using the representative elementary area (REA) concept whereby the REA is the smallest grain size representative of the extent. Structural metrics were calculated at increasing canopy spatial grain (from 5 to 1000 m) from aerial lidar data collected at nine different forested ecosystems including sub‐boreal, broadleaf temperate, needleleaf temperate, dry tropical, woodland and savanna systems, all sites are part of the National Ecological Observatory Network within the conterminous United States. To identify the REA of each FSD metric, we used changepoint analysis via segmented or piecewise regression which identifies significant changepoints for both the magnitude and variance of each metric. We find that using a spatial grain size between 25 and 75 m sufficiently captures the REA of CC, canopy arrangement, canopy leaf area and canopy complexity metrics across multiple forest types and a grain size of 30–150 m captures the REA of canopy height metrics. However, differences were evident among forest types with higher REA necessary to characterize CC in evergreen needleleaf forests, and canopy height in deciduous broadleaved forests. These findings indicate the appropriate range of spatial grain sizes from which inferences can be drawn from this set of FSD metrics, informing the use of lidar‐derived structural metrics for research and management applications.

Remote sensing (RS) and geospatial sciences already amount to a long history of fostering research in topics related to ecology. Data and methods have mainly been subject to research and experiments, but trends are now emerging that suggest the use of RS in practical applications like nationwide monitoring programs and assisting global conservation goals. However, use of active remote sensing for ecological and conservation is in its infancy, and the implications of active sensor data, including light detection and ranging and radio detection and ranging that mostly deliver three‐dimensional (3D) information, are still relatively primitive and have largely been limited to indirect use of their extracted proxies for ecological modelling.This cross‐journal special feature between Methods in Ecology and Evolution, Journal of Animal Ecology, Journal of Applied Ecology and Journal of Ecology includes 18 papers that include full research papers, reviews and technical applications. They are mostly novel in either or both their interpretation of proxies derived from active RS data and the direct usage of 3D RS techniques (terrestrial, airborne, UAV borne and spaceborne) to address ecological topics.We categorized the published contributions into the following thematic groups, with some degree of overlap: (i) ecosystem structural analysis by active data (nine studies); (ii) response of animal populations to climate dynamics as shown by active data; (iii) interactive effects of forest structure and wildlife monitoring (five studies); (iv) forest inventories assisted by active data (one study) and (v) tree type classification by active data (one study).Synthesis. The studies in this Special Feature and trends shown by other recent works at the interface of ecology and active RS confirm the ongoing shift from indirect and solely proxy‐based approaches to direct and more data‐science driven methods in approaching ecology and conservation problems by means of active sensors. Relatively affordable and accessible drone and citizen science‐based on‐demand active RS data acquisition are becoming common practice, and the future of sensor development is hypothesized to go beyond the current domination of very high spatial resolution data and towards multiple spaceborne platforms. These tools and methods will support spatial upscaling, uncertainty analysis, large‐scale mapping and monitoring of wildlife dynamics, among other topics that can take advantage of multitemporal/time series data. Nevertheless, access to demanding and costly very high‐resolution data sources may still be maintained and optimized by establishing international and public–private partnered data pools. [ABSTRACT FROM AUTHOR]

Solar‐induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three‐dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi‐sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5–10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real‐world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales. [ABSTRACT FROM AUTHOR]

IntroductionWith the continuous changes in climate patterns due to global warming, drought has become an important limiting factor in the development of terrestrial ecosystems. However, a comprehensive understanding of the impact of drought on soil microbial activity at a global scale is lacking.MethodsIn this study, we aimed to examine the effects of drought on soil microbial biomass (carbon [MBC], nitrogen [MBN], and phosphorus [MBP]) and enzyme activity (β-1, 4-glucosidase [BG]; β-D-cellobiosidase [CBH]; β-1, 4-N-acetylglucosaminidase [NAG]; L-leucine aminopeptidase [LAP]; and acid phosphatase [AP]). Additionally, we conducted a meta-analysis to determine the degree to which these effects are regulated by vegetation type, drought intensity, drought duration, and mean annual temperature (MAT).Result and discussionOur results showed that drought significantly decreased the MBC, MBN, and MBP and the activity levels of BG and AP by 22.7%, 21.2%, 21.6%, 26.8%, and 16.1%, respectively. In terms of vegetation type, drought mainly affected the MBC and MBN in croplands and grasslands. Furthermore, the response ratio of BG, CBH, NAG, and LAP were negatively correlated with drought intensity, whereas MBN and MBP and the activity levels of BG and CBH were negatively correlated with drought duration. Additionally, the response ratio of BG and NAG were negatively correlated with MAT. In conclusion, drought significantly reduced soil microbial biomass and enzyme activity on a global scale. Our results highlight the strong impact of drought on soil microbial biomass and carbon- and phosphorus-acquiring enzyme activity.

The Global Ecosystem Dynamics Investigation (GEDI) lidar is a multibeam laser altimeter on the International Space Station (ISS). GEDI is the first spaceborne instrument designed to measure vegetation height and to quantify aboveground carbon stocks in temperate and tropical forests and woodlands. This document describes the algorithm theoretical basis underpinning the development of the GEDI Level‐4A (GEDI04_A) footprint aboveground biomass density (AGBD) data product. The GEDI04_A data product contains estimates of AGBD for individual GEDI footprints and associated prediction intervals. The algorithm uses GEDI02_A relative height metrics and 13 linear models to predict AGBD in 32 combinations of plant functional type and world region within the observation limits of the ISS. GEDI04_A models for the release 1 and release 2 data products were developed using 8,587 quality‐filtered simulated GEDI waveforms associated with field estimates of AGBD in 21 countries. Although this is the most geographically comprehensive data available for the development of AGBD models using lidar remote sensing, important regions are underrepresented, including the forests of continental Asia, deciduous broadleaf forests and savannas of the dry tropics, and evergreen broadleaf forests north of Australia. We describe the scientific and statistical assumptions required to develop globally representative estimates of AGBD using GEDI lidar, including generalization beyond training data, and exclusion of GEDI02_A observations that do not meet requirements of the GEDI04_A algorithm. The footprint‐level predictions generated by this process provide globally comprehensive estimates of AGBD. These footprint‐level predictions are a prerequisite for the GEDI04_B gridded AGBD data product. Plain Language Summary: The amount of carbon stored in aboveground vegetation is uncertain. This uncertainty limits our ability to calculate fluxes of carbon between the land surface and the atmosphere, and prevents rigorous carbon offset crediting in forests. Much of this uncertainty is attributed to inconsistent measurement techniques and the use of Earth‐observation methods that were not designed to quantify carbon density. The Global Ecosystem Dynamics Investigation (GEDI) can largely overcome these challenges by producing measurements of vegetation height using a lidar sensor on the International Space Station. This document describes methods developed by the GEDI Science Team to convert spaceborne measurements of vegetation height into estimates of aboveground biomass density. The algorithms depend on the geographic world region and the type of vegetation that is present at a sampled location. For example, evergreen broadleaf forests of the humid tropics in South America and deciduous broadleaf forests of Europe use different algorithms. Statistical models were developed using comprehensive field measurements and simulated GEDI data. This document describes the importance of filtering GEDI data to reduce the impact of measurement artifacts on aboveground biomass predictions. Quality flags and ancillary data contained in the GEDI04_A data product ensure that the best predictions can be used. Key Points: Global Ecosystem Dynamics Investigation (GEDI) aboveground biomass density is from models trained on a comprehensive database of field measurements and simulated GEDI waveformsOn‐orbit prediction requires stratification by plant functional type and world regionQuality flags and metrics distinguish GEDI measurements that are representative of the conditions under which models were developed [ABSTRACT FROM AUTHOR]

Fir species have been threatened by extreme weather and climate conditions in many parts of the Mediterranean Basin. However, there are almost no studies focused on the mortality of Taurus fir in the Eastern Mediterranean basin and Turkey. This study aims to quantify the mortality pattern of Taurus fir stands in Hadim Forest Enterprise from 1971 to 2016 and to assess this pattern considering the long-term trends and fluctuations in the observed climate data. To this end, spatiotemporal changes in forest cover were analyzed using historical stand type maps in GIS. Statistical and graphical time-series analyses were performed on observed climate data. As a result, rapid areal losses were detected in pure fir stands, even though the annual rate of forestation is 0.5% for the entire forest. More than half of the stands transformed into pure or mixed stands dominated by black pine. Both fir stands and the entire forest became much more fragmented and drought-induced deadwood remarkably increased in almost all fir stands. Regarding the climatic analyses, statistically significant increased trends (p < 0.01) were detected particularly in annual, summer, and autumn mean and average maximum and minimum air temperatures of the Hadim station; strong decreased trends were observed in all relative humidity series; and rapid warming in the surrounding region along Hadim was observed. In addition, series of the Aridity Index and the Standardized Precipitation-Evapotranspiration Index revealed that more arid conditions and significant droughts have dominated the study district since the 1990s. This period has been characterized mostly by long-term agricultural and hydrological droughts. We conclude that selective tree mortality events in the Hadim's forests are likely caused by adverse impacts of observed climate variations and long-term droughts in the sub-region. [ABSTRACT FROM AUTHOR]

Lidar‐derived forest structural diversity (FSD) metrics—including measures of forest canopy height, vegetation arrangement, canopy cover (CC), structural complexity and leaf area and density—are increasingly used to describe forest structural characteristics and can be used to infer many ecosystem functions. Despite broad adoption, the importance of spatial resolution (grain and extent) over which these structural metrics are calculated remains largely unconsidered. Often researchers will quantify FSD at the spatial grain size of the process of interest without considering the scale dependency or statistical behaviour of the FSD metric employed.We investigated the appropriate scale of inference for eight lidar‐derived spatial metrics—CC, canopy relief ratio, foliar height diversity, leaf area index, mean and median canopy height, mean outer canopy height, and rugosity (RT)‐‐representing five FSD categories—canopy arrangement, CC, canopy height, leaf area and density, and canopy complexity. Optimal scale was determined using the representative elementary area (REA) concept whereby the REA is the smallest grain size representative of the extent. Structural metrics were calculated at increasing canopy spatial grain (from 5 to 1000 m) from aerial lidar data collected at nine different forested ecosystems including sub‐boreal, broadleaf temperate, needleleaf temperate, dry tropical, woodland and savanna systems, all sites are part of the National Ecological Observatory Network within the conterminous United States. To identify the REA of each FSD metric, we used changepoint analysis via segmented or piecewise regression which identifies significant changepoints for both the magnitude and variance of each metric.We find that using a spatial grain size between 25 and 75 m sufficiently captures the REA of CC, canopy arrangement, canopy leaf area and canopy complexity metrics across multiple forest types and a grain size of 30–150 m captures the REA of canopy height metrics. However, differences were evident among forest types with higher REA necessary to characterize CC in evergreen needleleaf forests, and canopy height in deciduous broadleaved forests.These findings indicate the appropriate range of spatial grain sizes from which inferences can be drawn from this set of FSD metrics, informing the use of lidar‐derived structural metrics for research and management applications. [ABSTRACT FROM AUTHOR]

Abstract The Global Ecosystem Dynamics Investigation (GEDI) lidar is a multibeam laser altimeter on the International Space Station (ISS). GEDI is the first spaceborne instrument designed to measure vegetation height and to quantify aboveground carbon stocks in temperate and tropical forests and woodlands. This document describes the algorithm theoretical basis underpinning the development of the GEDI Level‐4A (GEDI04_A) footprint aboveground biomass density (AGBD) data product. The GEDI04_A data product contains estimates of AGBD for individual GEDI footprints and associated prediction intervals. The algorithm uses GEDI02_A relative height metrics and 13 linear models to predict AGBD in 32 combinations of plant functional type and world region within the observation limits of the ISS. GEDI04_A models for the release 1 and release 2 data products were developed using 8,587 quality‐filtered simulated GEDI waveforms associated with field estimates of AGBD in 21 countries. Although this is the most geographically comprehensive data available for the development of AGBD models using lidar remote sensing, important regions are underrepresented, including the forests of continental Asia, deciduous broadleaf forests and savannas of the dry tropics, and evergreen broadleaf forests north of Australia. We describe the scientific and statistical assumptions required to develop globally representative estimates of AGBD using GEDI lidar, including generalization beyond training data, and exclusion of GEDI02_A observations that do not meet requirements of the GEDI04_A algorithm. The footprint‐level predictions generated by this process provide globally comprehensive estimates of AGBD. These footprint‐level predictions are a prerequisite for the GEDI04_B gridded AGBD data product.

A huge proportion of the world’s population resides in urban areas along the coast. As cities expand, the ability of coastal ecosystems to provide the benefits people derive from nature, ranging from food from fisheries to coastal defense to maritime transportation and beyond, is in question. While it is well understood that coastal development changes ecosystems, quantitative insights about how terrestrial urbanization fundamentally alters ecosystem structure and function in adjacent freshwater and downstream coastal marine habitats remain rare, though a general expectation is that impacts of terrestrial urbanization will attenuate from land to freshwater to coastal marine habitats. Empirical assessments of these phenomena are especially important for species that rely on freshwater and coastal marine habitats at multiple points in their life cycles, including endangered and threatened Pacific salmon (Oncorhynchus spp.). We investigated associations between landscape-scale urbanization and ecosystem structure (biodiversity of epibenthic invertebrate taxa) and function (benthic net primary productivity and decomposition) in freshwater and coastal marine habitats across six pairs of more and less urbanized, coastal watersheds in Puget Sound, WA, USA, using principal components analysis, analysis of covariance, and Mantel tests. Greater upland urbanization was associated with greater reductions in freshwater biodiversity, measured as the density and evenness of epibenthic invertebrate families. In contrast and surprisingly, however, coastal marine biodiversity (measured as the density and evenness of epibenthic invertebrate families) tended to be higher at more urbanized sites, suggesting the potential role of low to moderate levels of urbanization-related disturbance in determining coastal marine biodiversity patterns. We found no statistical association between urbanization and freshwater and coastal marine ecosystem functions, estimated from changes in accumulated algal biomass on tiles (benthic net primary productivity) and loss of biomass from litter bags (decomposition). In addition, there was no evidence that changes in ecosystem structure and function with urbanization were more severe in freshwater than coastal marine habitats, as might be expected if the land-sea boundary diminished effects of landscape-scale urbanization. Our results suggest that the effects of urbanization can be complex and that attention to terrestrial, freshwater, and coastal marine systems in concert will produce more effective, ecosystem-based management.

The frequently used term ecology is currently interpreted in various ways. This scientific discipline has undergone relatively dynamic development since its inception, and its character is still widening and changing. Therefore, in this contribution we attempt to briefly summarize the subject and contents of current ecology, as well as to propose its more systemic and comprehensive definition. We try to enhance its present definitions especially by putting emphasis on the dynamics of nature (the dynamics of natural processes). We define current ecology as the science dealing with the structure, dynamics and functions of nature including evolution, where structure involves the distribution and abundance of individual organisms, habitats and ecosystems; dynamics include all the aspects of their life trajectories and cycles, including growth, development, reproduction or renewal, interactions and their changes, the cycling of matter, flows of energy and information and their transformations; and functions involve the properties, traits and niches of individual organisms and species in an ecosystem, as well as the properties and niches of ecosystems in the landscape, ecoregion or in the whole Earth system.

Forage fishes are an important component of marine, estuarine, and aquatic food webs that facilitate the transfer of energy and nutrients from primary producers to upper trophic levels. Previous studies of forage fishes have focused primarily on pelagic planktivorous species in pelagic environments. However, benthically associated taxa can be just as important as planktivorous species, particularly in highly productive estuarine environments that provide critical habitat for many predators. In this study, we analyzed a 20‐year forage fish community composition and abundance dataset across four eastern Gulf of Mexico estuaries spanning a broad latitudinal gradient to investigate spatiotemporal variability in community structure and quantify associations with habitat. Our analyses revealed significant regional structuring of forage fish communities, coupled with a strong association with habitat characteristics related to latitudinal effects and basal resource regime. Communities in the two northern estuaries and two southern estuaries were associated primarily with planktonically reliant and benthically reliant taxa, respectively. Despite regional differences, we uncovered a coherent annual cycle in forage fish communities across all estuaries related to seasonal shifts in abundances of several abundant and ubiquitous species. We additionally revealed significant subdecadal periodicity potentially associated with bottom‐up effects of global climatic cycles. The significant association of forage fish communities with habitat regime shown in this study underlies the importance of continued monitoring of these communities. This study represents a novel approach to assess this critical ecosystem component in diverse estuarine systems globally. [ABSTRACT FROM AUTHOR]

Abstract Forage fishes are an important component of marine, estuarine, and aquatic food webs that facilitate the transfer of energy and nutrients from primary producers to upper trophic levels. Previous studies of forage fishes have focused primarily on pelagic planktivorous species in pelagic environments. However, benthically associated taxa can be just as important as planktivorous species, particularly in highly productive estuarine environments that provide critical habitat for many predators. In this study, we analyzed a 20‐year forage fish community composition and abundance dataset across four eastern Gulf of Mexico estuaries spanning a broad latitudinal gradient to investigate spatiotemporal variability in community structure and quantify associations with habitat. Our analyses revealed significant regional structuring of forage fish communities, coupled with a strong association with habitat characteristics related to latitudinal effects and basal resource regime. Communities in the two northern estuaries and two southern estuaries were associated primarily with planktonically reliant and benthically reliant taxa, respectively. Despite regional differences, we uncovered a coherent annual cycle in forage fish communities across all estuaries related to seasonal shifts in abundances of several abundant and ubiquitous species. We additionally revealed significant subdecadal periodicity potentially associated with bottom‐up effects of global climatic cycles. The significant association of forage fish communities with habitat regime shown in this study underlies the importance of continued monitoring of these communities. This study represents a novel approach to assess this critical ecosystem component in diverse estuarine systems globally.

The Scotia Sea is a productive pelagic ecosystem in the Southern Ocean, which is rapidly changing as a consequence of global warming. Species range shifts are particularly evident, as sub-Antarctic species expand their range from North to South, potentially rearranging the structure of this ecosystem. Thus, studies are needed to determine the current extent of variation in food web structure between these two biogeographic regions of the Scotia Sea and to investigate whether the observed patterns are consistent among depth zones. We compiled a database of 10,888 feeding interactions among 228 pelagic taxa, underpinned by surveys and dietary studies conducted in the Scotia Sea. Network analysis indicated that the Northern Scotia Sea (NSS), relative to the Southern Scotia Sea (SSS), is more complex: with higher species richness (more nodes) and trophic interactions (more links) is more connected overall (greater connectance and linkage density). Moreover, the NSS is characterised by more groups of strongly interacting organisms (greater node clustering) than the SSS, suggesting a higher trophic specialisation of Antarctic compared to sub-Antarctic species. Depth also played a key role in structuring these networks, with higher mean trophic position and more dietary generalism in the mesopelagic and bathypelagic zones relative to the epipelagic zones. This suggests that direct access to primary producers is a key factor influencing the trophic structure of these communities. Our results suggest that under current levels of warming the SSS ecosystem will likely become more connected and less modular, resembling the current structure of the NSS. [ABSTRACT FROM AUTHOR]

With about 11,100 islands and islets of which ca. 250 are regularly inhabited by human, the Mediterranean Sea represents one of the regions of the world with the most islands and archipelagos. These numerous islands represent a significant component of the Mediterranean biodiversity, notably with the presence of range-restricted species and peculiar vegetation types. The aim of this review is to provide a balanced view of this highly diverse phytoecological heritage, but also taking into account the medium sized islands and the smaller ones that have not been highlighted so far. Mediterranean islands constitute both a museum for ancient lineages (paleoendemic taxa) and cradle for recent plant diversification. The complex historical biogeography (paleogeographical events of the Neogene, Messinian salinity crisis, climatic and eustatic changes of the Pleistocene, influence of glacial events) has profoundly influenced the current patterns of plant diversity. These insular landscapes were also precociously impacted by prehistoric man, possibly by Neanderthals. Among the 157 large Mediterranean islands (i.e. with a surface area exceeding 10 km2), 49 have a surface greater than 100 km2. The main patterns and dynamics of vegetation on the largests islands (Balearic Islands, Corsica, Sardinia, Sicily, Croatian islands, Greek islands, Crete, Cyprus) are summarized. Then, the specific ecosystem functioning (disturbance, plant-animal interactions) and vegetation structures of the small Mediterranean islands (i.e. a surface area less than 10 km2 or 1000 ha), are highlighted by evoking successively the small rocky islands, the volcanic ones, and the sandy and flat islands. Owing to their uniqueness and fragility, Mediterranean islands urgently need some integrated and ambitious conservation planning, aiming at the long-term preservation of their outstanding biotic and cultural heritage. [ABSTRACT FROM AUTHOR]

The trophic position concept is central in system ecology, and in this study, trophic position (TP) estimates from stable-isotopes and an Ecopath mass-balance food web model for the Barents Sea were compared. Two alternative models for estimating TP from stable isotopes, with fixed or scaled trophic fractionation were applied. The mass-balance model was parametrized and balanced for year 2000, was comprised of 108 functional groups (Gs), and was based on biomass and diet data largely based on predator stomach data. Literature search for the Barents Sea Large Marine Ecosystem revealed 93 sources with stable isotope data (δ15N values) for 83 FGs, and 25 of the publications had trophic position estimated from nitrogen stable isotopes. Trophic positions estimated from the mass-balance model ranged to 5.1 TP and were highly correlated with group mean δ15N values, and also highly correlated with the original literature estimates of trophic positions from stable isotopes. On average, TP from the mass-balance model was 0.1 TP higher than the original literature TP estimates (TPSIR) from stable isotopes. A trophic enrichment factor (TEF) was estimated assuming fixed fractionation and minimizing differences between trophic positions from Ecopath and TP predicted from δ15N values assuming a baseline value for δ15N calculated for pelagic particulate organic matter at a baseline TP of 1.0. The estimated TEF of 3.0‰ was lower than the most commonly used TEF of 3.4 and 3.8‰ in the literature. The pelagic whales and pelagic invertebrates functional groups tended to have higher trophic positions from Ecopath than from stable isotopes while benthic invertebrate functional groups tended to show an opposite pattern. Trophic positions calculated using the scaled trophic fractionation approach resulted in lower TP than from Ecopath for intermediate TPs and also a larger TP range in the BS. It is concluded that TPs estimated from δ15N values using a linear model compared better to the Ecopath model than the TPs from scaled fractionation approach.

Background: Increasing nitrogen (N) deposition has altered plant communities globally, however the changes in species abundances with short-term vs. long-term N enrichment remains unclear. Stoichiometric homeostasis, quantified by the homoeostatic regulation coefficient (H) is a key trait predictive of plant species dominance and species responses to short-term global changes. It is unknown whether H changes with N enrichment over time, thereby affecting species responses to long-term N addition. Methods: Here we investigated three representative plant species how species dominance changed to short-term and long-term N addition with a field N addition experiment (2006–2013) in an Inner Mongolia grassland. Changes in species H with long-term N addition were analyzed using a sand culture experiment, and the correlation between species H and species abundances were explored to address the above research gaps. Results: The abundance of Leymus chinensis decreased with short-term N addition, and increased with long-term N addition, while Chenopodium glaucum exhibited the opposite pattern. Cleistogenes squarrosa was only favored by 1-year N addition, and depressed by two or more years of N addition. The H values of L. chinensis and C. glaucum decreased significantly with long-term N addition, but did not change for C. squarrosa. The H values were significantly related with the abundance both in Control and long-term N addition treatments. Conclusion: Species abundance had opposite responses to short-term vs. long-term N addition. The decrease of H suggested the nutrients use strategy became more progressive, which mediated the responses of species abundances to short- and long-term N addition. [ABSTRACT FROM AUTHOR]

Monitoring ecological environment with remote sensing technology is an effective means of environmental management and sustainable development. Based on Landsat image data and field survey data, this paper used the unweighted voting multi-classifier ensemble method to extract the ecosystem cover data of the water-land interaction area of Nansi Lake from 1987 to 2017, and analyzed the evolution characteristics of the ecosystem structure with the help of the transfer matrix and landscape pattern index. The results showed: (1) The accuracy of multi-classifier ensemble was higher than that of single classifier, with a maximum improvement of 4.17%. (2) In 2006, the change inflection point of ecosystem structure appeared in the study area, which showed that the trend of increase and decrease of ecosystem area changed, and the degree of landscape fragmentation was the lowest. The structure and type transfer of the ecosystem in the study area showed the characteristics of "ring" distribution, and the distribution and transfer of ecosystem at the junction of land and water and land were more complex. (3) Human activities under the intervention of China's policies, climate change and ecosystem self-regulation were the main driving factors for the change of ecosystem structure in the study area. This study provided technical methods for the further exploration of the ecosystem, and provided constructive guidance for the protection and sustainable development of ecological environment. [ABSTRACT FROM AUTHOR]

Nature-based solutions have emerged as a concept for integrating ecosystem-based approaches whilst addressing multiple sustainable development goals. However, implementing nature-based solutions is inherently complex and requires consideration of a range of environmental and socio-economic conditions that may impact on their effectiveness. This research assesses ecosystem services within the Valletta urban agglomeration, Malta, and evaluates the implications arising from existing distributional patterns. Proxy-based indicators and expert knowledge were used to map and assess a set of 14 ecosystem services. Proximity and correlation analyses were used to assess distributional inequalities arising from differentiated availability of ecosystem types with high ecosystem service capacities for groups with different socio-economic characteristics. Data relating to schooling, employment, sickness, disability, and old age, were combined to identify areas of relative advantage and disadvantage. The highest ecosystem service capacities were in the urban fringes and the lowest in dense urban cores. Private gardens and urban trees had the highest regulating ecosystem service capacities per unit area. Contrastingly, public gardens had low effectiveness for regulating ecosystem services but the highest cultural ecosystem service capacities. Availability of urban green infrastructure and tree cover differ according to socio-economic advantage, and disadvantaged communities generally had reduced proximity to ecosystems with high ecosystem service capacities. Considering these findings, we argue that urban ecosystem service assessments can support greening strategies by identifying the most effective nature-based solutions that can play a redistributive role by addressing existing inequalities in green infrastructure and ecosystem services capacities distribution in cities.

Habitat degradation and land‐use change driven by the livestock sector are among the major causes of global biodiversity loss. Forests are crucial in maintaining biodiversity and mitigating climate change. Apart from continuing deforestation, forests also face increasing pressure from livestock grazing in the system, which is less understood compared to grasslands. Through a meta‐analysis of 156 articles with 1936 data entries, this study assesses the effect of livestock on forest biodiversity, structure, and functions, varying with livestock types, livestock density, grazing history, and climatic factors. Our results show that livestock overall had a negative impact on the forest structure and functions, reduced species abundance but increased richness. Medium and large mammals, plant communities, and soil were more negatively affected compared to other groups such as birds and invertebrates. Livestock also influenced the role of forests in mitigating climate change. They changed forest carbon stock by reducing plant biomass; however, they did not significantly impact the soil carbon stock or soil greenhouse gas emissions. Ecosystem attributes were more affected in warmer and drier regions and by single species grazing than the mixed grazing. Past livestock grazing history moderates the impacts of livestock, with the strongest negative effect occurred with a history of 1–5 years. Nonetheless, livestock activities also had a positive impact on forest management, such as reducing forest flammability. Our results also indicate the lack of studies on how higher trophic levels respond to livestock disturbances and how grazing intensity moderates the effect, which includes grazing duration and livestock density. The complex responses of forests to livestock in different conditions call for more adaptive management depending on the conservation targets and evolution history. [ABSTRACT FROM AUTHOR]

Ecosystem-based management relies on understanding how perturbations influence ecosystem structure and function (e.g., invasive species, exploitation, abiotic changes). However, data on unimpacted systems are scarce; therefore, we often rely on impacted systems to make inferences about 'natural states.' Among the Laurentian Great Lakes, Lake Superior provides a unique case study to address non-native species impacts because the food web is dominated by native species. Additionally, Lake Superior is both vertically (benthic versus pelagic) and horizontally (nearshore versus offshore) structured by depth, providing an opportunity to compare the function of these sub-food webs. We developed an updated Lake Superior EcoPath model using data from the 2005/2006 lake-wide multi-agency surveys covering multiple trophic levels. We then compared trophic transfer efficiency (TTE) to previously published EcoPath models. Finally, we compared ecosystem function of the 2005/2006 ecosystem to that with non-native linkages removed and compared native versus non-native species-specific approximations of TTE and trophic flow. Lake Superior was relatively efficient (TTE = 0.14) compared to systems reported in a global review (average TTE = 0.09), and the microbial loop was highly efficient (TTE > 0.20). Non-native species represented a very small proportion (<0.01%) of total biomass and were generally more efficient and had higher trophic flow compared to native species. Our results provide valuable insight into the importance of the microbial loop and represent a baseline estimate of non-native species impacts on Lake Superior. Finally, this work is a starting point for further model development to predict future changes in the Lake Superior ecosystem. [ABSTRACT FROM AUTHOR]

Vegetation responds dynamically to local microclimates at both short and long time scales via mechanisms ranging from physiological behaviors, such as stomatal closure, to acclimation and adaptation. These responses influence the carbon, water, and energy cycles directly and are therefore crucial to understanding and predicting Earth system responses to a changing climate. Several recent studies have demonstrated that differences in microclimate can induce structural and functional acclimations, and potentially adaptations, within the same ecosystem. Such microclimate divergence can be caused by variability in slopes, disturbance history, or even localized resource availability. Ecosystem stressors such as low soil water availability, limited photoperiod, or high vapor pressure deficit have been shown to reveal the large impact of the subtle differences within these systems such as the number of sun versus shade leaves or differences in whole‐plant water acquisition and use. These findings highlight the linkages between plant canopy structure and ecosystem function, alongside the need for comprehensive analyses of vegetation within the broader context of its environment. This commentary addresses some of the key implications of ecosystem stress responses and accompanying acclimations across three ecosystem types for ecosystem ecology, plant physiology, ecohydrology and trait‐based modeling of vegetation‐climate dynamics. Plain Language Summary: Plants dynamically interact with their environment, including above and below ground influences. Recent work has shown that these subsurface‐plant‐atmosphere feedbacks shape ecosystem structure and function on both large and small scales at both short and long time frames. Subtle differences in vegetation acclimation reveal the importance of long‐term ecosystem observations during periods of stress as well as normal function to fully understand water, carbon, and energy cycles in a changing climate. Key Points: Subtle differences in vegetation types or acclimation can shape plant‐environment feedbacks in meaningful waysEnvironmental stressors can reveal divergent behaviors between similar ecosystemsEcosystem function and stress response can shape ecosystem structure [ABSTRACT FROM AUTHOR]

Assessing and monitoring ecosystem health are critical components of ecosystem management as they provide information on natural resource destruction and the causes and factors leading to it. The need for comprehensive and multidimensional indices for assessing and predicting the status of ecosystems has become increasingly important. The ecosystem health index (EHI) was calculated by assessing multiple criteria, including vigor, organization, and resilience criteria, in an ecotone ecosystem in Ardabil province. Different weighting approaches were used to evaluate the index value, and sub-watersheds were prioritized based on the index weighting. The EHI values varied among the studied sub-watersheds, ranging from 0.32 to 0.79, depending on the weighting method. Sub-watershed SW1 had a higher health status with a value of 0.77 compared to other studied sub-watersheds in the Iril watershed, while SW5 had a lower health status with a value of 0.34 in the equal weighting approach. The average value of the EHI for all studied sub-watersheds in the Iril watershed was found to be 0.50, indicating a relatively undesirable ecosystem health status. The EHI is a useful tool for prioritizing areas and an effective step in ecosystem management, considering the multidimensional nature of the index and the factors affecting ecosystem restoration or destruction. Assessing the extent of ecosystem degradation across various regions depends on the health status of the studied ecosystem, the feasibility of index calculation, and may involve different selection criteria. [ABSTRACT FROM AUTHOR]