Ecological Field Studies Research Articles

A targeted study to determine the conservation status of a Data Deficient montane lizard, the Eungella shadeskink (Saproscincus eungellensis)

Context Combatting biodiversity loss is often hamstrung by a lack of species-specific knowledge. Species considered Data Deficient (DD) on the IUCN Red List are poorly understood and often neglected in conservation investment, despite evidence they are often threatened. Reptiles have the highest percentage of DD species for any terrestrial vertebrate group. Aims We aimed to assess the conservation status of the DD Eungella shadeskink (Saproscincus eungellensis), which is endemic to Eungella National Park, Queensland, Australia. Methods A combination of a targeted field survey, ecological studies, and species distribution modelling were used. Key results Saproscincus eungellensis typically occurred within 25 m of streams, at elevations between 700 and 1000 m. The species is thigmothermic, with a low active body temperature (~23–26°C) and was predominantly observed on rocks and fallen palm fronds. The species has a highly restricted distribution with an estimated Area of Occupancy of 36 km2 and Extent of Occurrence of 81.7 km2, comprising one location (defined by the threat of climate change) with an estimated 16,352–52,892 mature individuals. The main threats are fire, invasive alien species and climate change, with the species forecast to lose all suitable habitat by 2080 under all climate change scenarios. Conclusions The species meets listing criteria for Critically Endangered under Criterion B of the International Union for Conservation of Nature. Implications Our results support recent studies indicating that some DD species are highly threatened. Our approach provides a template for conducting targeted studies to determine the conservation status of DD species, especially those with restricted ranges.

Remote sensing for site selection in vegetation survey along a successional gradient in post-industrial vegetation.

Vegetation characteristics are an important proxy to measure the outcome of ecological restoration and monitor vegetation changes. Similarly, the classification of remotely sensed images is a prerequisite for many field ecological studies. We have a limited understanding of how the remote sensing approach can be utilized to classify spontaneous vegetation in post-industrial spoil heaps that dominate urban areas. We aimed to assess whether an objective a priori classification of vegetation using remotely sensed data allows for ecologically interpretable division. We hypothesized that remote sensing-based vegetation clusters will differ in alpha diversity, species, and functional composition; thereby providing ecologically interpretable division of study sites for further analyses. We acquired remote-sensing data from Sentinel 2A for each studied heap from July to September 2020. We recorded vascular plant species and their abundance across 400 plots on a post-coal mine in Upper Silesia, Poland. We assessed differences in alpha diversity indices and community-weighted means (CWMs) among remote sensing-based vegetation units. Analysis of remotely sensed characteristics revealed five clusters that reflected transition in vegetation across successional gradients. Analysis of species composition showed that the 1st (early-succession), 3rd (late-succession), and 5th (mid-succession) clusters had 13, 10, and 12 exclusive indicator species, respectively, however, the 2nd and 4th clusters had only one species. While the 1st, 2nd, and 4th can be combined into a single cluster (early-succession), we found the lowest species richness in the 3rd cluster (late-succession) and the highest in the 5th cluster (mid-succession). Shannon's diversity index revealed a similar trend. In contrast, the 3rd cluster (late-succession) had significantly higher phylogenetic diversity. The 3rd cluster (late-succession) had the lowest functional richness and the highest functional dispersion. Our approach underscored the significance of a priori classification of vegetation using remote sensing for vegetation surveys. It also highlighted differences between vegetation types along a successional gradient in post-mining spoil heaps.

Colony identity clues for Syntermes grandis (Blattodea: Termitidae) individuals using near-infrared spectroscopy and PLS-DA approach.

Termites are social insects with high species diversity in tropical ecosystems. Multivariate analysis with near-infrared spectroscopy (NIRS) and data interpretation can separate social insects belonging to different colonies of the same species. The objective of this study was to propose the use of discriminant analysis by partial least squares (PLS-DA) combined with NIRS to identify the colonial origin of the Syntermes grandis (Rambur, 1842) (Blattodea: Termitidae) in 2 castes. Six ground S. grandis colonies were identified and mapped; 30 workers and 30 soldier termites in each colony were submitted to spectral measurement with NIRS. PLS-DA applied to the termites' spectral absorbance was used to detect a spectral pattern per S. grandis colony by caste. PLS-DA regression with NIRS proved to be an approach with 99.9% accuracy for identifying the colonial origin of S. grandis workers and 98.3% for soldiers. The methodology showed the importance of qualitatively characterizing the colonial phenotypic response of this species. NIRS is a high-precision approach to identifying the colony origin of S. grandis workers and soldiers. The PLS-DA can be used to design ecological field studies to identify colony territorial competition and foraging behavior of subterranean termite species.

Ecological Flow Analysis through an Ecohydraulic-Based Catchment Scale Approach

Ecological flow regime analysis through developing a novel ecohydraulic optimization method is the objective of this study in which three components are linked. Hydrological analysis is the first component in which average monthly flow is assessed in different hydrological conditions by applying a drought index in the selected control points or representative reaches in the river basin. Another component is the ecological model in which field ecological studies are used for selecting the target species, and habitat loss was modelled through the fuzzy method. The outputs of the hydrological analysis and hydraulic habitat simulation were then applied in the structure of the optimization model in which minimizing ecological impacts and water supply loss were defined as the purposes. Different evolutionary algorithms were used in the optimization process. A decision-making system was utilized to finalize ecological flow by selecting the privileged algorithm. According to the outputs, the proposed method can mitigate ecological impacts and water supply losses simultaneously. Either particle swarm optimization or differential evolution algorithm is the best approach for ecological flow in this research work. The outputs of optimization indicated that the reliability of the water supply in dry years is less than 32%, while it is more than 80% in wet years, which means that changing the hydrological condition will increase the portion of ecological flow regime significantly. In other words, the reliability of the water supply can be reduced by more than 50%. Hence, using other water resources such as groundwater is necessary in dry years in the study area.

Examining the exposure-reception-retention link in realistic communication environments via VR and eye-tracking: The VR billboard paradigm.

Exposure is key to message effects. No effects can ensue if a health, political, or commercial message is not noticed. Yet, existing research in communication, advertising, and related disciplines often measures 'opportunities for exposure' at an aggregate level, whereas knowing whether recipients were 'actually exposed' to a message requires a micro-level approach. Micro-level research, on the other hand, focuses on message processing and retention, takes place under highly controlled laboratory conditions with forced message exposure, and largely ignores how recipients attend selectively to messages under more natural conditions. Eye-tracking enables us to assess actual exposure, but its previous applications were restricted to screen-based reading paradigms lacking ecological validity or field studies that suffer from limited experimental control. Our solution is to measure eye-tracking within an immersive VR environment that creates the message delivery and reception context. Specifically, we simulate a car ride down a highway alongside which billboards are placed. The VR headset (HP Omnicept Pro) provides an interactive 3D view of the environment and holds a seamlessly integrated binocular eye tracker that records the drivers' gaze and detects all fixations on the billboards. This allows us to quantify the nexus between exposure and reception rigorously, and to link our measures to subsequent memory, i.e., whether messages were remembered, forgotten, or not even encoded. An empirical study shows that incidental memory for messages differs based on participants' gaze behavior while passing the billboards. The study further shows how an experimental manipulation of attentional demands directly impacts drivers' gaze behavior and memory. We discuss the large potential of this paradigm to quantify exposure and message reception in realistic communication environments and the equally promising applications in new media contexts (e.g., the Metaverse).

Assessment of the impact of recreation load on the development of responsible community tourism

The concept of sustainable development is based on the interdependence of three key aspects of development – environmental, economic and social. Tourism and recreational nature use are seen as effective tools for achieving financial self-sufficiency of local communities, development of private entrepreneurship, positive impact on the social sphere and minimizing the exploitation of natural resource. However, excessive recreational activity can lead to the degradation of natural complexes. In order to preserve biodiversity and sustainable development of territories, it is necessary to monitor the condition of zones with intensive recreational innovation to prevent their degradation and develop responsible tourism. To monitor the environmental condition, there are used modern methods of remote sensing of the Earth, which should be combined with field ecological studies. In the course of the research, there was proved the existence of interrelationships between the enzymatic activity of soils, soil density and the vegetation condition according to NDVI. Currently, there is an urgent issue of maintaining a balance between the population’s requests for recreation and the ability of natural resources to satisfy them. The given research method is able to provide information to ensure the responsible attitude of the community to nature-protected zones, to influence ecological awareness and to ensure the effective use of the ecosystem. Calculations were carried out on the example of complex slope ecosystems of the Barmakivske tract, which are subjected to a strong recreational load.

A high-quality genome for the slender anole (Anolis apletophallus): an emerging model for field studies of tropical ecology and evolution.

The slender anole, Anolis apletophallus, is a small arboreal lizard of the rainforest understory of central and eastern Panama. This species has been the subject of numerous ecological and evolutionary studies over the past 60 years as a result of attributes that make it especially amenable to field and laboratory science. Slender anoles are highly abundant, short-lived (nearly 100% annual turnover), easy to manipulate in both the lab and field, and are ubiquitous in the forests surrounding the Smithsonian Tropical Research Institute in Panama, where researchers have access to high-quality laboratory facilities. Here, we present a high-quality genome for the slender anole, which is an important new resource for studying this model species. We assembled and annotated the slender anole genome by combining 3 technologies: Oxford Nanopore, 10× Genomics Linked-Reads, and Dovetail Omni-C. We compared this genome with the recently published brown anole (Anolis sagrei) and the canonical green anole (Anolis carolinensis) genomes. Our genome is the first assembled for an Anolis lizard from mainland Central or South America, the regions that host the majority of diversity in the genus. This new reference genome is one of the most complete genomes of any anole assembled to date and should facilitate deeper studies of slender anole evolution, as well as broader scale comparative genomic studies of both mainland and island species. In turn, such studies will further our understanding of the well-known adaptive radiation of Anolis lizards.

Variation in the Drought Tolerance of Tropical Understory Plant Communities across an Extreme Elevation and Precipitation Gradient.

Little is known about how differences in water availability within the "super humid" tropics can influence the physiology of understory plant species and the composition of understory plant communities. We investigated the variation in the physiological drought tolerances of hundreds of understory plants in dozens of plant communities across an extreme elevation and precipitation gradient. Specifically, we established 58 understory plots along a gradient of 400-3600 m asl elevation and 1000-6000 mm yr-1 rainfall in and around Manu National Park in southeastern Peru. Within the plots, we sampled all understory woody plants and measured three metrics of physiological leaf drought tolerance-turgor loss point (TLP), cuticular conductance (Gmin), and solute leakage (SL)-and assessed how the community-level means of these three traits related to the mean annual precipitation (MAP) and elevation (along the study gradient, the temperature decreases linearly, and the vapor pressure deficit increases monotonically with elevation). We did not find any correlations between the three metrics of leaf drought tolerance, suggesting that they represent independent strategies for coping with a low water availability. Despite being widely used metrics of leaf drought tolerance, neither the TLP nor Gmin showed any significant relationships with elevation or the MAP. In contrast, SL, which has only recently been developed for use in ecological field studies, increased significantly at higher precipitations and at lower elevations (i.e., plants in colder and drier habitats have a lower average SL, indicating greater drought tolerances). Our results illustrate that differences in water availability may affect the physiology of tropical montane plants and thus play a strong role in structuring plant communities even in the super humid tropics. Our results also highlight the potential for SL assays to be efficient and effective tools for measuring drought tolerances in the field.

Treeline remote sensing: from tracking treeline shifts to multi‐dimensional monitoring of ecotonal change

AbstractRemote sensing applications have a long history in treeline research. Recent reviews have examined the topic mainly from a methodological point of view. Here, we propose a question‐oriented review of remote sensing in treeline ecology to relate remote sensing methodologies to key ecological metrics and identify knowledge gaps and promising areas for future research. We performed a meta‐analysis to assess the role of remote sensing as a tool for measuring spatial patterns and dynamics of alpine and Arctic treeline ecotone globally. We assessed the geographic distribution, scale of analysis, and relationships between remote sensing techniques and treeline ecological metrics through co‐occurrence mapping and multivariate statistics. Our analysis revealed that only 10% of treeline ecology studies applied remote sensing tools, often associated with the keyword ‘climate change’. Monitoring studies adopted coarser spatial resolutions over longer temporal extents in comparison with other treeline studies. A multiscale and multi‐sensor spatial approach was implemented in just 19% of papers. Long‐term research commonly relied on aerial and oblique photography to measure treeline shifts through photointerpretation within a multidisciplinary framework. More recent treeline dynamics were often quantified using greenness trends derived from the pixel‐based classification of satellite images. Many recent short‐term studies focused on delineating tree scale metrics derived from the object‐based classification of uncrewed aerial vehicle (UAV) images or LiDAR data. Over the past decade, high‐resolution and low‐cost UAV remote sensing has emerged as an interesting opportunity to fill the gap between local‐scale ecological patterns and coarse‐resolution satellite sensors. Additionally, treeline remote sensing applications would strongly benefit from multidisciplinary frameworks that integrate field studies in ecology and environmental science. The multi‐dimensional structural complexity of treelines typically responds to environmental drivers over multiple scales and thus is best described with multiscale and multi‐sensor approaches.

Digital whole-community phenotyping: tracking morphological and physiological responses of plant communities to environmental changes in the field.

Plant traits are informative for ecosystem functions and processes and help to derive general rules and predictions about responses to environmental gradients, global change and perturbations. Ecological field studies often use 'low-throughput' methods to assess plant phenotypes and integrate species-specific traits to community-wide indices. In contrast, agricultural greenhouse or lab-based studies often employ 'high-throughput phenotyping' to assess plant individuals tracking their growth or fertilizer and water demand. In ecological field studies, remote sensing makes use of freely movable devices like satellites or unmanned aerial vehicles (UAVs) which provide large-scale spatial and temporal data. Adopting such methods for community ecology on a smaller scale may provide novel insights on the phenotypic properties of plant communities and fill the gap between traditional field measurements and airborne remote sensing. However, the trade-off between spatial resolution, temporal resolution and scope of the respective study requires highly specific setups so that the measurements fit the scientific question. We introduce small-scale, high-resolution digital automated phenotyping as a novel source of quantitative trait data in ecological field studies that provides complementary multi-faceted data of plant communities. We customized an automated plant phenotyping system for its mobile application in the field for 'digital whole-community phenotyping' (DWCP), capturing the 3-dimensional structure and multispectral information of plant communities. We demonstrated the potential of DWCP by recording plant community responses to experimental land-use treatments over two years. DWCP captured changes in morphological and physiological community properties in response to mowing and fertilizer treatments and thus reliably informed about changes in land-use. In contrast, manually measured community-weighted mean traits and species composition remained largely unaffected and were not informative about these treatments. DWCP proved to be an efficient method for characterizing plant communities, complements other methods in trait-based ecology, provides indicators of ecosystem states, and may help to forecast tipping points in plant communities often associated with irreversible changes in ecosystems.

Coloring coral larvae allows tracking of local dispersal and settlement.

Quantifying patterns of dispersal and settlement in marine benthic invertebrates is challenging, largely due the complexity of life history traits, small sizes of larvae (<1 mm), and potential for large-scale dispersal (>100 km) in the marine environment. Here, we develop a novel method that allows for immediate differentiation and visual tracking of large numbers of coral larvae (106 to 109) from dispersal to settlement. Neutral red and Nile blue stains were extremely effective in coloring larvae, with minimal impacts on survival and settlement following optimization of incubation times and stain concentrations. Field validation to wild-captured larvae from the Great Barrier Reef demonstrates the efficacy of staining across diverse taxa. The method provides a simple, rapid (<60 minutes), low-cost (approximately USD$1 per 105 larva) tool to color coral larvae that facilitates a wide range of de novo laboratory and field studies of larval behavior and ecology with potential applications for conservation planning and understanding patterns of connectivity.

The Habit in Cohabitation

As human and nonhuman animals increasingly share space, however enthusiastically or reluctantly, the concepts of habit, cohabitation, and habituation bear further scrutiny when applied to these makeshift arrangements. Even when researchers have critically examined the work these terms do in discussions of more-than-human relations, they have tended to ignore the temporalities embedded in "habit" and its cognates. A discourse of habit traps animals in an ethnographic present of the sort long critiqued within anthropology in its application to humans. One alternative is to approach more-than-human animals as what Mahesh Rangarajan calls "animals with histories," instead of treating them as members of species with fairly set characteristics who make cameo appearances in ecological histories, ethnographies, and field studies. Studies of human-tiger relations in Rajasthan, India, and auto-ethnographic material on human-bear relations in Alaska suggestively illustrate what a historical orientation has to offer by way of moving discussions of multispecies relations beyond a colonial discourse of encounter and the blurring of human/nonhuman boundaries. Acknowledgment that nonhuman animals have historically inflected backstories, even when their memories and experiences are not accessible to humans, is a step in the direction of more expansive possibilities for co-worlding.

An innovative approach to using an intensive field course to build scientific and professional skills.

This paper reports on the design and evaluation of Field Studies in Functional Ecology (FSFE), a two‐week intensive residential field course that enables students to master core content in functional ecology alongside skills that facilitate their transition from “student” to “scientist.” We provide an overview of the course structure, showing how the constituent elements have been designed and refined over successive iterations of the course. We detail how FSFE students: (1) Work closely with discipline specialists to develop a small group project that tests an hypothesis to answer a genuine scientific question in the field; (2) Learn critical skills of data management and communication; and (3) Analyze, interpret, and present their results in the format of a scientific symposium. This process is repeated in an iterative “cognitive apprenticeship” model, supported by a series of workshops that name and explicitly instruct the students in “hard” and “soft” skills (e.g., statistics and teamwork, respectively) critically relevant for research and other careers. FSFE students develop a coherent and nuanced understanding of how to approach and execute ecological studies. The sophisticated knowledge and ecological research skills that they develop during the course is demonstrated through high‐quality presentations and peer‐reviewed publications in an open‐access, student‐led journal. We outline our course structure and evaluate its efficacy to show how this novel combination of field course elements allows students to gain maximum value from their educational journey, and to develop cognitive, affective, and reflective tools to help apply their skills as scientists.

Detecting and reducing heterogeneity of error in acoustic classification

Abstract Passive acoustic monitoring can be an effective method for monitoring species, allowing the assembly of large audio datasets, removing logistical constraints in data collection and reducing anthropogenic monitoring disturbances. However, the analysis of large acoustic datasets is challenging and fully automated machine learning processes are rarely developed or implemented in ecological field studies. One of the greatest uncertainties hindering the development of these methods is spatial generalisability—can an algorithm trained on data from one place be used elsewhere? We demonstrate that heterogeneity of error across space is a problem that could go undetected using common classification accuracy metrics. Second, we develop a method to assess the extent of heterogeneity of error in a random forest classification model for six Amazonian bird species. Finally, we propose two complementary ways to reduce heterogeneity of error, by (i) accounting for it in the thresholding process and (ii) using a secondary classifier that uses contextual data. We found that using a thresholding approach that accounted for heterogeneity of precision error reduced the coefficient of variation of the precision score from a mean of 0.61 ± 0.17 (SD) to 0.41 ± 0.25 in comparison to the initial classification with threshold selection based on F‐score. The use of a secondary, contextual classification with thresholding selection accounting for heterogeneity of precision reduced it further still, to 0.16 ± 0.13, and was significantly lower than the initial classification in all but one species. Mean average precision scores increased, from 0.66 ± 0.4 for the initial classification, to 0.95 ± 0.19, a significant improvement for all species. We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.

Геолого-геоморфологический анализ оползневых процессов в заповеднике «Гобустан» в целях туристско-рекреационной деятельности

In article analyzes landslide processes, taking into account the intensive expansion of tourist and recreational activities in the Gobustan National Reserve, located in the southeastern part of the Greater Caucasus. The importance of this problem lies in the fact that it is planned to create a National Geopark of international importance on the territory of Gobustan. Based on own field ecological, geological and geomorphological studies, fund and cartographic material, as well as using aerospace images (ASI) from 1996, 2000-2020 and scale 1:60 000, it was found that over the past 50 years, the area of Gobustan, subjected to landslide processes, has increased by 1.5-2 times. The data obtained made it possible to compile a map of zoning of the Greater Caucasus with a scale of 1:1 000 000 according to landslide hazard (in points), which objectively reflects the quantitative and qualitative characteristics of landslide processes. The research results will make it possible to use the obtained data for the development of the Program for the safe and sustainable functioning and development for the recreational and tourist development of Azerbaijan's geosystems.

Evergreen forest types of the central plains in Cambodia: floristic composition and ecological characteristics

Current vegetation maps show evergreen forests of Cambodia as one homogenous forest type. However, ecological field studies in the central plains demonstrated a heterogenous mosaic of different evergreen forest types, each with a unique species composition and ecological characteristics. Based on six botanical expeditions, we describe four lowland evergreen forest types: 1) riverine forest dominated by Dipterocarpus costatus (Dipterocarpaceae); 2) tall dipterocarp forest dominated by Anisoptera costata (Dipterocarpaceae); 3) swamp forest dominated by Macaranga triloba (Euphorbiaceae); and 4) ‘Sralao', an open forest with a monodominance of Lagerstroemia cochinchinensis (Lythraceae). Ordination by non‐metric multi‐dimensional scaling (NMDS) indicated that the four forest types represent well‐separated floristic entities with Sralao as the most deviant community. The highest species diversity was found in the riverine forest ( = 2.65), followed by tall dipterocarp forest ( = 2.53) and swamp forest ( = 2.34), whereas the Sralao forest had the lowest species diversity ( = 1.64). We argue that botanical fieldwork remains essential to refine vegetation maps otherwise based on remote sensing, and that knowledge of species composition is essential to conserve Indochina's vanishing evergreen forest biodiversity.

Identification of sex chromosomes using genomic and cytogenetic methods in a range-expanding spider,Argiope bruennichi(Araneae: Araneidae)

AbstractDifferences between sexes in growth, ecology and behaviour strongly shape species biology. In some animal groups, such as spiders, it is difficult or impossible to identify the sex of juveniles based on external morphology. This information would be useful for field surveys, behavioural experiments and ecological studies, such as those on sex ratios and dispersal. In species with sex chromosomes, sex can be determined based on the specific sex chromosome complement. Additionally, information on the sequence of sex chromosomes provides the basis for studying sex chromosome evolution. We combined cytogenetic and genomic data to identify the sex chromosomes in the sexually dimorphic spider Argiope bruennichi and designed quantitative real-time polymerase chain reaction sex markers. We found that the genome size and GC content of this spider fall into the ranges reported for the majority of araneids. The male karyotype is formed by 24 acrocentric chromosomes with an X1X20 sex chromosome system, with little similarity between X chromosomes, suggesting an origin of these chromosomes by X chromosome fission or early duplication of an X chromosome and subsequent independent differentiation of the copies. Our data suggest X chromosomes of similar sizes in A. bruennichi. They are smaller chromosomes of the complement. Our findings open the door to new directions in spider evolutionary and ecological research.

Remote sensing of phenology: Towards the comprehensive indicators of plant community dynamics from species to regional scales

Abstract Remote sensing of vegetation phenology has long been used to characterize ecosystem functions and responses to climate at spatial and temporal scales unfeasible to field surveys. However, the potential of remote sensing to elucidate mechanistic drivers of phenology and the underlying plant community processes at such scales remains under‐discussed. This review synthesizes possibilities to advance this knowledge using multi‐temporal remote sensing and discusses remaining challenges and progress in instruments and analytical tools. Recent evidence indicates that, besides documenting vegetation seasonality and responses to climate, remote sensing of phenology can help meet emerging needs for indicators of plant diversity, vegetation structure and ecosystem change. Responses of phenological metrics to stressors over large, heterogeneous regions may provide clues on ecological resilience manifested in asynchronies, recovery of vegetation cycles and stable microrefugia. At the same time, important barriers persist in relation to choosing among phenological estimation methods and paradigms, characterizing phenological events beyond changes in photosynthetically active biomass, and mechanistic interpretation of phenological patterns. Synthesis. Increasing temporal frequency of products, opportunities for multi‐sensor data fusion, and advances in historically less available hyperspectral, active microwave and lidar instruments promise to help navigate these barriers and enable more comprehensive assessments of seasonality. Progress in customizable local platforms such as unoccupied aerial vehicles and phenocams may further enrich ground‐level understanding of phenology and validate satellite‐based assessments. However, remote sensing analyses alone are insufficient for mechanistic interpretation of phenology, which can be challenged by artefacts in remote sensing data and sensitivity of estimated metrics to landscape structure and spatial resolution of the inputs. Robust and informative phenological assessments call for rigorous collaborations with field ecological studies, strategic selection of ancillary environmental and geographic data, and wider adoption of causal inference approaches to address these needs and support novel explorations in plant ecology.

Squeeze it or leave it? An ecological-economic assessment of the impact of mower conditioners on arthropod populations in grassland

This study addresses the use of conditioners as a driver of arthropod loss in agricultural landscapes. Conditioners compress the freshly cut mowing material mechanically to destroy the evaporation-inhibiting wax layer of the grass material. This compression potentially increases the physical damage to several arthropod groups during the mowing process. We have combined an ecological field study on the impact of conditioners on arthropods at the plot level with an analysis of the economic rationale of applying conditioners in differently managed grasslands in the study region, in order to understand the impact of applying conditioners on the damage to arthropods at the landscape level. The use of conditioners in the mowing process significantly increased the overall percentage of damaged individuals by 18% from 52% without to 70% with conditioner use. Aphids and plant lice, beetles, thrips and mites were most severely affected by additional damage. We also found that the use of conditioners takes place on substantially more than 20% of all grasslands in the study region. Depending on the respective grassland area managed with conditioners in the future, grasslands could be losing an additional 4% to 18% of their overall arthropod numbers only due to the use of conditioners compared to a scenario without conditioners. As the damage due to the use of conditioners is presumably higher in extensively managed grasslands, and the profit of their use is higher in intensively managed grasslands, we suggest, as an implication for insect conservation, concentrating measures to disincentivise the use of conditioners on extensively managed grassland.

Tundra vegetation change and impacts on permafrost

Tundra vegetation productivity and composition are responding rapidly to climatic changes in the Arctic. These changes can, in turn, mitigate or amplify permafrost thaw. In this Review, we synthesize remotely sensed and field-observed vegetation change across the tundra biome, and outline how these shifts could influence permafrost thaw. Permafrost ice content appears to be an important control on local vegetation changes; woody vegetation generally increases in ice-poor uplands, whereas replacement of woody vegetation by (aquatic) graminoids following abrupt permafrost thaw is more frequent in ice-rich Arctic lowlands. These locally observed vegetation changes contribute to regional satellite-observed greening trends, although the interpretation of greening and browning is complicated. Increases in vegetation cover and height generally mitigate permafrost thaw in summer, yet, increase annual soil temperatures through snow-related winter soil warming effects. Strong vegetation–soil feedbacks currently alleviate the consequences of thaw-related disturbances. However, if the increasing scale and frequency of disturbances in a warming Arctic exceeds the capacity for vegetation and permafrost recovery, changes to Arctic ecosystems could be irreversible. To better disentangle vegetation–soil–permafrost interactions, ecological field studies remain crucial, but require better integration with geophysical assessments. Greening and vegetation community shifts have been observed across Arctic environments. This Review examines these changes and their impact on underlying permafrost.