Individual Species Research Articles

Beyond species richness: Forest structure and edaphic conditions have similar importance but different effects on multi-taxon biodiversity

Managed forests represent a major fraction of the global forest area and are known to host impoverished biodiversity compared to natural forests. The effect of forest management has focused mainly on aggregated community metrics such as species richness of single taxa and on simplistic managed vs. unmanaged comparisons. However, the effect of forest management is expected to vary among species and taxa and to be contingent on site-specific conditions. In this study, we focus on fine-scale multi-taxon biodiversity patterns to disentangle the impact of forest management on the forest structure and the abiotic soil conditions of the stands. We base our comparisons on carefully selected pairs of managed and unmanaged stands to minimize regional differences that could confound the effects of management. We found that the total effect of forest management on alpha diversity was positive on plants and rove beetles, neutral on ground beetles and mosses, and negative on crane flies, fungi, and lichens. However, using joint species distribution modeling we show that individual species’ responses to the local underlying soil conditions can be as important as the forest structural changes induced by management, but this varied among the different taxa. Based on these responses we disclose synergies and trade-offs among some of the taxa. Our results indicate that the balance between forest management and abiotic conditions can shape the patterns of forest multi-taxon biodiversity. Considering these conditions can be important in predicting the response of biodiversity to forest management and act as key criteria when prioritizing areas for the conservation of biodiversity.

LC-HRMS analysis of phospholipids bearing oxylipins

BackgroundSeveral oxylipins including hydroxy- and epoxy-polyunsaturated fatty acids act as lipid mediators. In biological samples they can be present as non-esterified form, but the major part occurs esterified in phospholipids (PL) or other lipids. Esterified oxylipins are quantified indirectly after alkaline hydrolysis as non-esterified oxylipins. However, in this indirect analysis the information in which lipid class oxylipins are bound is lost. In this work, an untargeted liquid chromatography high-resolution mass spectrometry (LC-HRMS) method for the direct analysis of PL bearing oxylipins was developed. ResultsOptimized reversed-phase LC separation achieved a sufficient separation of isobaric and isomeric PL from different lipid classes bearing oxylipin positional isomers. Individual PL species bearing oxylipins were identified based on retention time, precursor ion and characteristic product ions. The bound oxylipin could be characterized based on product ions resulting from the α-cleavage occurring at the hydroxy/epoxy group. PL sn-1/sn-2 isomers were identified based on the neutral loss of the fatty acyl in the sn-2 position. A total of 422 individual oxPL species from 7 different lipid classes i.e., PI, PS, PC, PE, PC-P, PC-O, and PE-P were detected in human serum and cells. This method enabled to determine in which PL class supplemented oxylipins are incorporated in HEK293 cells: 20:4;15OH, 20:4;14Ep, and 20:5;14Ep were mostly bound to PI. 20:4;8Ep and 20:5;8Ep were esterified to PC and PE while other oxylipins were mainly found in PC. SignificanceThe developed LC-HRMS method enables the comprehensive detection as well as the semi-quantification of isobaric and isomeric PL species bearing oxylipins. With this method, we show that the position of the oxidation has a great impact and directs the incorporation of oxylipins into the different PL classes in human cells.

Arsenic speciation analysis in human urine for long term epidemiological studies: The Multi-Ethnic Study of Atherosclerosis (MESA)

Arsenic is a ubiquitous toxic metalloid causing serious health problems. Speciation analysis of arsenic in human urine provides valuable insights for large-scale epidemiological studies and informs on sources of exposure as well as human metabolism. The Multi-Ethnic Study of Atherosclerosis (MESA) is a valuable cohort for assessing chronic low-moderate arsenic exposure and health effects in an ethnically diverse US population. We present a state-of-the-art arsenic speciation analysis methodology and its application to 7677 MESA spot urine samples based on high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. This method is fast, robust and detects a total of 11 individual As species at method detection limits of 0.02–0.03 μg arsenic/L urine for each individual species. Our analytical approach features excellent mean method accuracy (98%) and precision (5%) for the main arsenic species in urine (arsenobetaine, methylarsonic acid, dimethylarsinic acid, and total inorganic As); intra- (3–6%) and inter-day coefficients of variability (5–6%); column recovery (96 ± 7%); and spike recovery (97 ± 6%). The main arsenic species were detectable in ≥95% of urine samples due to the implementation of an oxidation step. Each individual minor arsenic species was detectable in ≤25% of all urines, although at least one of them was detected in almost half the participants. We identified two minor urinary arsenic species as dimethylarsinoylacetic acid and dimethylarsinoylpropionic acid, potential metabolites of seafood-related arsenicals. We observed differences in individual As species excretion by race/ethnicity, with Asian-American participants featuring 3–4 times higher concentrations compared to other participants. We also found differences by site, body mass index, smoking status, rice intake, and water arsenic levels, potentially indicating different exposures or related to individual bio-metabolism. The proposed approach is suitable for epidemiological studies and the collected data will constitute the base for future research on potential health effects of chronic low-level arsenic exposure.

Analysis of subcellular energy metabolism in five Lacertidae lizards across varied environmental conditions

Aerobic respiration is the main energy source for most eukaryotes, and efficient mitochondrial energy transfer greatly influences organismal fitness. To survive environmental changes, cells have evolved to adjust their biochemistry. Thus, measuring energy metabolism at the subcellular level can enhance our understanding of individual performance, population dynamics, and species distribution ranges. We investigated three important metabolic traits at the subcellular level in five lacertid lizard species sampled from different elevations, from sea level up to 2000 m. We examined hemoglobin concentration, two markers of oxidative stress (catalase activity and carbonyl concentration) and maximum rate of metabolic respiration at the subcellular level (potential metabolic activity at the electron transport system). The traits were analysed in laboratory acclimated adult male lizards to investigate the adaptive metabolic responses to the variable environmental conditions at the local sampling sites. Potential metabolic activity at the cellular level was measured at four temperatures – 28 °C, 30 °C, 32 °C and 34 °C – covering the range of preferred body temperatures of the species studied. Hemoglobin content, carbonyl concentration and potential metabolic activity did not differ significantly among species. Interspecific differences were found in the catalase activity, Potential metabolic activity increased with temperature in parallel in all five species. The highest response of the metabolic rate with temperature (Q10) and Arrhenius activation energy (Ea) was recorded in the high-mountain species Iberolacerta monticola.

Ca2+-dependent lipid preferences shape synaptotagmin-1 C2A and C2B dynamics: Insights from experiments and simulations

Signal transmission between neurons requires exocytosis of neurotransmitters from the lumen of synaptic vesicles into the synaptic cleft. Following an influx of Ca2+, this process is facilitated by the Ca2+ sensor synaptotagmin-1. The underlying mechanisms involve electrostatic and hydrophobic interactions tuning the lipid preferences of the two C2 domains of synaptotagmin-1; however, the details are still controversially discussed. We, therefore, follow a multidisciplinary approach and characterize lipid and membrane binding of the isolated C2A and C2B domains. We first target interactions with individual lipid species, and then study interactions with model membranes of liposomes. Finally, we perform molecular dynamics simulations to unravel differences in membrane binding. We found that both C2 domains, as a response to Ca2+, insert into the lipid membrane; however, C2A adopts a more perpendicular orientation while C2B remains parallel. These findings allow us to propose a mechanism for synaptotagmin-1 during membrane fusion.

A new perspective on tree growing season determination

AbstractDefining plant development timing through seasonal growth and dormancy phases is a valuable proxy for studying climate change and serves as an annual bioindicator. However, current methods for determining the growing season vary due to species‐specific interpretations and differing understandings of its main drivers. Körner et al. (2023) introduced four non‐interchangeable definitions of growing seasons to clarify this complex issue. While some studies have paired different methods, none have simultaneously applied a full set of methods at the individual tree or species level. Here, I aim to present a new perspective to understanding growing season timing by focusing on all facets of above‐ground tree growth and measurable biological and phenological markers. This approach calls for simultaneous, continuous monitoring during active and dormancy periods on the same trees and across different species at a large spatial scale. The goal is to comprehensively understand each method's errors, temporal lags, and the factors determining each growing season, as defined by Körner et al. (2023, Ecology Letters, 26, 1277). Accurate estimation of growing season timing can reshape our understanding of its environmental drivers, improve terrestrial ecosystem models, assess the impact of climate change on tree growth, determine the biological zero for various species, verify remote sensing indices and forecast species distribution.

Using joint species distribution modelling to identify climatic and non‐climatic drivers of Afrotropical ungulate distributions

The relative importance of the different processes that determine the distribution of species and the assembly of communities is a key question in ecology. The distribution of any individual species is affected by a wide range of environmental variables as well as through interactions with other species; the resulting distributions determine the pool of species available to form local communities at fine spatial scales. A challenge in community ecology is that these interactions (e.g. competition, facilitation, etc.) often are not directly measurable. Here, we used hierarchical modelling of species communities (HMSC), a recently developed framework for joint species distribution modelling, to estimate the role of biotic effects alongside environmental factors using latent variables. We investigate the role of these factors determining species distributions in communities of Artiodactyla, Perissodactyla and Proboscidea in the Afrotropics, an area of peak species richness for hoofed mammals. We also calculate pairwise trait dissimilarity between these species, from a mixture of morphological and behavioural traits, and investigate the relationship between dissimilarity and estimated residual co‐occurrence in the model. We find that while ungulate distributions appear to be predominantly determined (~ 70%) by climatic variables, such as precipitation, a substantial proportion of the variance in ungulate species distributions (~ 30%) can also be attributed to modelled latent variables that likely represent a combination of dispersal barriers and biotic factors. Although we find only a weak relationship between residual co‐occurrence and trait dissimilarity, we suggest that our results may show evidence that biotic factors, likely influenced by historical barriers to species dispersal, are important in determining species communities over a continental area. The HMSC framework can be used to provide insight into factors affecting community assembly at broad scales, and to make more powerful predictions about future species distributions as we enter an era of increasing impacts from anthropogenic change.

Understory Vegetation Influences Insect Diversity in Rubber Plantations of Kanyakumari, India

Insects play a crucial role in maintaining ecological balance, and their decline has detrimental effects on various organisms. Globally, rubber plantations have been associated with a reduction in insect diversity. However, the impact of monoculture rubber plantations on biodiversity in India, particularly in Kanyakumari, is not well understood and has received little research attention. This study aimed to assess the status of insect diversity in rubber plantations in this region. Kanyakumari, Tamil Nadu, with its extensive monoculture rubber plantations, provides an ideal setting for this investigation. Three adjacent rubber plantations with varying topography and understory vegetation were selected for the study. Data was collected between July 2021 to January 2022 and analysis was done using biodiversity indices - Simpson and Shannon-Weiner indices. Results indicated that insect diversity was significantly higher in one plantation when compared to the other two plantations. Canopy and understory vegetation were identified as key factors influencing insect diversity. Plantations with dense understory vegetation consisting of diverse native plant species exhibited greater insect richness. The predominant insect orders across all plantations were Hymenoptera (29.70%) and Diptera (29.40 %). However, the impact of rubber plantations on individual insect species varied based on their habitat preferences. Seasonal fluctuations in diversity were particularly noticeable during the monsoon season. Further comparative studies are needed to understand the broader implications of rubber plantations on insect diversity across the district.

Field-based multispecies weed and crop detection using ground robots and advanced YOLO models: A data and model-centric approach

The implementation of a machine-vision system for real-time precision weed management is a crucial step towards the development of smart spraying robotic vehicles. The intelligent machine-vision system, constructed using deep learning object detection models, has the potential to accurately detect weeds and crops from images. Both data-centric and model-centric approaches of deep learning model development offer advantages depending on environment and non-environment factors. To assess the performance of weed detection in real-field conditions for eight crop species, the Yolov8, Yolov9, and customized Yolov9 deep learning models were trained and evaluated using RGB images from four locations (Casselton, Fargo, and Carrington) over a two-year period in the Great Plains region of the U.S. The experiment encompassed eight crop species—dry bean, canola, corn, field pea, flax, lentil, soybean, and sugar beet—and five weed species—horseweed, kochia, redroot pigweed, common ragweed, and water hemp. Six Yolov8 and eight Yolov9 model variants were trained using annotated weed and crop images gathered from four different sites including combined dataset from four sites. The Yolov8 and Yolov9 models’ performance in weed detection were assessed based on mean average precision (mAP50) metrics for five datasets, eight crop species, and five weed species. The results of the weed and crop detection evaluation showed high mAP50 values of 86.2 %. The mAP50 values for individual weed and crop species detection ranged from 80.8 % to 98 %. The results demonstrated that the performance of the model varied by model type (model-centric), location due to environment (data-centric), data size (data-centric), data quality (data-centric), and object size in the image (data-centric). Nevertheless, the Yolov9 customized lightweight model has the potential to play a significant role in building a real time machine-vision-based precision weed management system.

Shifts in the altitudinal distribution of alien and native synanthropic plants along roadsides over a 40-year period

Disturbed areas alongside roads shape unique vegetation communities dominated by synanthropic native and alien plant species, facilitated by roads serving as corridors for dispersal, penetration, and integration of synanthropic plants into new areas. We collected presence/absence data for individual species along roads in the Orlické Mountains, Czech Republic, in three time periods during 1970–2010. The distribution of species was mapped using a 1-square-kilometer grid. Analyzing 107 plant species (44 native, 63 alien), we found archaeophyte species favor lower elevations (foothills), while neophytes thrive at higher elevations. Over 40 years, neophyte frequency significantly rose at lower elevations, contrasting the decline at higher elevations, with no marked change in archaeophyte frequency. Native species decline notably at 400–500 m elevations. Some thermophilous native synanthropic species and alien archaeophytes spread from foothills to higher elevations, while some psychrophilic higher-elevation species shift upwards, diminishing at lower elevations. We emphasize human disturbance and global warming as pivotal factors influencing the altitudinal distribution shift in both native and alien plant species.

Leaf transcriptomes from C3, C3-C4 intermediate, and C4 Neurachne species give insights into C4 photosynthesis evolution.

The C4 photosynthetic pathway is hypothesized to have evolved from the ancestral C3 pathway through progressive changes in leaf anatomy and biochemistry with extant C3-C4 photosynthetic intermediate species representing phenotypes between species demonstrating full C3 and full C4 states. The Australian endemic genus Neurachne is the only known grass group that contains distinct, closely related species that carry out C3, C3-C4 intermediate, or C4 photosynthesis. To explore and understand the molecular mechanisms underlying C4 photosynthesis evolution in this genus, leaf transcriptomes were generated from two C3, three photosynthetic intermediate (proto-Kranz, C2-like, and C2), and two C4 Neurachne species. The data were used to reconstruct phylogenetic relationships in Neurachne, which confirmed two independent C4 origins in the genus. Relative transcript abundances substantiated the photosynthetic phenotypes of individual species and highlighted transcriptional investment differences between species, including between the two C4 species. The data also revealed proteins potentially involved in C4 cycle intermediate transport and identified molecular mechanisms responsible for the evolution of C4-associated proteins in the genus.

Taxonomic reintroduction of the holarctic saprotrophic fungus Crepidotus cinnamomeus

Crepidotus is a genus of common saprotrophic fungi well known especially in the Northern Hemisphere, but distribution patterns of individual species are not sufficiently understood. We redefined a taxonomic circumscription of Crepidotus cinnamomeus based on morphological and molecular congruencies between the type material and recent collections. The species is well delimited from other similar and currently accepted species of the genus. Crepidotus cinnamomeus was found to have a broad holarctic distribution with occurrences in North America, Europe and Asia where it grows on twigs and branches of deciduous trees and shrubs in preferably cold humid habitats. Here we present the first multilocus phylogeny of the genus, including portions of the RPB2 gene. Our study highlights the importance of sufficient sampling from broader areas supported by sequence data, which is essential for estimation of species delimitation, distribution and correct name assignment for Crepidotus species.

Scaling up ocean conservation through recognition of key biodiversity areas in the Southern Ocean from multispecies tracking data.

Biodiversity is critical for maintaining ecosystem function but is threatened by increasing anthropogenic pressures. In the Southern Ocean, a highly biologically productive region containing many endemic species, proactive management is urgently needed to mitigate increasing pressures from fishing, climate change, and tourism. Site-based conservation is one important tool for managing the negative impacts of human activities on ecosystems. The Key Biodiversity Area (KBA) Standard is a standardized framework used to define sites vital for the persistence of global biodiversity based on criteria and quantitative thresholds. We used tracking data from 14 species of Antarctic and subantarctic seabirds and pinnipeds from the publicly available Retrospective Analysis of Antarctic Tracking Data (RAATD) data set to define KBAs for a diverse suite of marine predators. We used track2kba, an R package that supports identification of KBAs from telemetry data through identification of highly used habitat areas and estimates of local abundance within sites. We compared abundance estimates at each site with thresholds for KBA criteria A1, B1, and D1 (related to globally threatened species, individual geographically restricted species, and demographic aggregations, respectively). We identified 30 potential KBAs for 13 species distributed throughout the Southern Ocean that were vital for each individual species, population, and life-history stage for which they were determined. These areas were identified as highly used by these populations based on observational data and complement the ongoing habitat modeling and bioregionalization work that has been used to prioritize conservation areas in this region. Although further work is needed to identify potential KBAs based on additional current and future data sets, we highlight the benefits of utilizing KBAs as part of a holistic approach to marine conservation, given their significant value as a global conservation tool.

The path to scientifically sound biodiversity valuation in the context of the Global Biodiversity Framework

Successful implementation of the Kunming-Montreal Global Biodiversity Framework requires identifying a process for measuring and valuing changes in biodiversity that build on the recognition that economics and valuation must play a key role in “halting and reversing” biodiversity loss. Here, we discuss considerations for a practical path to valuing changes in biodiversity. Framing changes in the value of biodiversity as a summary of changes in certain natural assets enables leveraging existing approaches and international standards associated with environmental-economic accounting. We discuss why an approach that builds from individual species, evolutionary groups, or functional groups into a practical, hierarchical statistical classification system is better than the development of any one biodiversity index. We merge techniques from ecology and other natural sciences, national and environmental-economic accounting, and economics, which are all on the cusp of making measurement of the change in the value of biodiversity possible. The focus should be on scaling and integrating these approaches. The path forward appears to begin with imperfect but useful measures, grounded in robust concepts, while establishing ambition to further scale-up measurements—just like the past evolution of many other official statistical series.

High-Fat Feeding Alters Circulating Triglyceride Composition: Roles of FFA Desaturation and ω-3 Fatty Acid Availability.

Hypertriglyceridemia is a risk factor for type 2 diabetes and cardiovascular disease (CVD). Plasma triglycerides (TGs) are a key factor for assessing the risk of diabetes or CVD. However, previous lipidomics studies have demonstrated that not all TG molecules behave the same way. Individual TGs with different fatty acid compositions are regulated differentially under various conditions. In addition, distinct groups of TGs were identified to be associated with increased diabetes risk (TGs with lower carbon number [C#] and double-bond number [DB#]), or with decreased risk (TGs with higher C# and DB#). In this study, we examined the effects of high-fat feeding in rats on plasma lipid profiles with special attention to TG profiles. Wistar rats were maintained on either a low-fat (control) or high-fat diet (HFD) for 2 weeks. Plasma samples were obtained before and 2.5 h after a meal (n = 10 each) and subjected to lipidomics analyses. High-fat feeding significantly impacted circulating lipid profiles, with the most significant effects observed on TG profile. The effects of an HFD on individual TG species depended on DB# in their fatty acid chains; an HFD increased TGs with low DB#, associated with increased diabetes risk, but decreased TGs with high DB#, associated with decreased risk. These changes in TGs with an HFD were associated with decreased indices of hepatic stearoyl-CoA desaturase (SCD) activity, assessed from hepatic fatty acid profiles. Decreased SCD activity would reduce the conversion of saturated to monounsaturated fatty acids, contributing to the increases in saturated TGs or TGs with low DB#. In addition, an HFD selectively depleted ω-3 polyunsaturated fatty acids (PUFAs), contributing to the decreases in TGs with high DB#. Thus, an HFD had profound impacts on circulating TG profiles. Some of these changes were at least partly explained by decreased hepatic SCD activity and depleted ω-3 PUFA.

Personalized identification of autism-related bacteria in the gut microbiome using explainable artificial intelligence

Autism spectrum disorder (ASD) affects social interaction and communication. Emerging evidence links ASD to gut microbiome alterations, suggesting that microbial composition may play a role in the disorder. This study employs explainable artificial intelligence (XAI) to examine the contributions of individual microbial species to ASD. By using local explanation embeddings and unsupervised clustering, the research identifies distinct ASD subgroups, underscoring the disorder's heterogeneity. Specific microbial biomarkers associated with ASD are revealed, and the best classifiers achieved an AU-ROC of 0.965± 0.005 and an AU-PRC of 0.967± 0.008. The findings support the notion that gut microbiome composition varies significantly among individuals with ASD. This work's broader significance lies in its potential to inform personalized interventions, enhancing precision in ASD management and classification. These insights highlight the importance of individualized microbiome profiles for developing tailored therapeutic strategies for ASD.

Effect of mowing versus abandonment of mesic grasslands in Central Europe on biomass use for biogas production: Implications for semi-natural ecosystem conservation

The economic management of lignocellulosic biomass from semi-natural grasslands is now a challenge across Europe. The abandonment of mowing these grasslands leads to the gradual degradation of these ecosystems. This study investigates how chemical and biological factors affect the suitability of biomass from abandoned grasslands for biogas production. We sampled 30 mown and 30 abandoned grassland sites in the Sudetes Mountains (Poland and Czechia). The cover contribution of short herbs was found to be significantly higher in mown grasslands (p < 0.001), while that of tall herbs was more prevalent in abandoned grasslands (p < 0.01). The specific biogas yield (SBY, NL kg−1 volatile solids) is negatively affected by an increased percentage of herbs in the biomass of mown and abandoned grasslands. This is due to the inhibitory effect of herbs on biodegradation, the increase in lignin content and the decrease in cellulose. This study highlights the importance of individual plant species in assessing grassland biomass for area biogas yield (ABY, m3 ha−1) and provides new insights into a field that has not yet been extensively investigated. In mown grasslands, ABY was most positively correlated with grass species (Arrhenatherum elatius, Trisetum flavescens and Festuca pratensis). In abandoned grasslands, the ABY was most correlated with herbaceous species (Galium aparine, Urtica dioica and Chaerophyllum aromaticum) and grasses (A. elatius and Elymus repens). Mown grasslands had significantly higher species richness (p < 0.001) compared to abandoned grasslands, but the number of species sampled did not correlate with SBY and ABY. This study contributes to the development of a sustainable bio-economy by highlighting the need for efficient use of grassland biomass. This approach helps protect semi-natural ecosystems and facilitates sustainable management of renewable resources.

Model-based investigation of the pH-dependent chromatographic separation of itaconic acid from aqueous solution using strongly hydrophobic adsorbents

In this study, we propose a model for the simulation of the pH-dependent separation of dicarboxylic acids from aqueous solutions using strongly hydrophobic adsorbents. Building upon results of our previous study, where we experimentally investigated the pH-dependent adsorption behavior of the individual acid species of itaconic acid (IA) on a strongly hydrophobic adsorbent using in-line Raman spectroscopy, we utilize a transport-dispersive model as the basis for our simulation model. Instead of considering IA as a single component in our model, we simulated each acid species of IA individually. For this purpose, we expanded the transport-dispersive model with reaction terms in all aqueous phases. The reaction terms include all dissociation reactions of all involved components for each time step and spatial discretization. This model enables the time and spatial dependent simulation of the pH value in the chromatographic column and thus the time and spatial dependent knowledge of each acid species concentration. The consideration of activity coefficients due to high local ionic strength is achieved using the Truesdell–Jones (TdJ) model. The simulation model is successfully validated using experimental data from our previous study and used in a simulation study that demonstrates the potential of the model approach for analyzing associated separation tasks.

Unravelling the complexities of biotic homogenization and heterogenization in the British avifauna.

Biotic homogenization is a process whereby species assemblages become more similar through time. The standard way of identifying the process of biotic homogenization is to look for decreases in spatial beta-diversity. However, using a single assemblage-level metric to assess homogenization can mask important changes in the occupancy patterns of individual species. Here, we analysed changes in the spatial beta-diversity patterns (i.e. biotic heterogenization or homogenization) of British bird assemblages within 30 km × 30 km regions between two periods (1988-1991 and 2008-2011). We partitioned the change in spatial beta-diversity into extirpation and colonization-resultant change (i.e. change in spatial beta-diversity within each region resulting from both extirpation and colonization). We used measures of abiotic change in combination with Bayesian modelling to disentangle the drivers of biotic heterogenization and homogenization. We detected both heterogenization and homogenization across the two time periods and three measures of diversity (taxonomic, phylogenetic, and functional). In addition, both extirpation and colonization contributed to the observed changes, with heterogenization mainly driven by extirpation and homogenization by colonization. These assemblage-level changes were primarily due to shifting occupancy patterns of generalist species. Compared to habitat generalists, habitat specialists had significantly (i) higher average contributions to colonization-resultant change (indicating heterogenization within a region due to colonization) and (ii) lower average contributions to extirpation-resultant change (indicating homogenization from extirpation). Generalists showed the opposite pattern. Increased extirpation-resultant homogenization within regions was associated with increased urban land cover and decreased habitat diversity, precipitation, and temperature. Changes in extirpation-resultant heterogenization and colonization-resultant heterogenization were associated with differences in elevation between regions and changes in temperature and land cover. Many of the 'winners' (i.e. species that increased in occupancy) were species that had benefitted from conservation action (e.g. buzzard (Buteo buteo)). The 'losers' (i.e. those that decreased in occupancy) consisted primarily of previously common species, such as cuckoo (Cuculus canorus). Our results show that focusing purely on changes in spatial beta-diversity over time may obscure important information about how changes in the occupancy patterns of individual species contribute to homogenization and heterogenization.

Exploration of large-scale vegetation transition in wet ecosystems: a comparison of conifer seedling abundance across burned vs. unburned forest-peatland ecotones in Western Patagonia

Altered fire regimes, combined with a warmer and drier climate, have been eroding the resilience of temperate rainforests and peatlands worldwide and leading to alternative post-fire vegetation communities. Chronic anthropogenic burning of temperate rainforests at the forest-peatland ecotone in western Patagonia appears to have shifted vegetation communities in poorly-drained sites from forests dominated by the threatened conifer, Pilgerodendron uviferum, to peat-accumulating wetlands covered by Sphagnum mosses. We collected and modeled post-reburn field data using ordinations and hierarchical Bayesian regressions to examine mechanisms through which P. uviferum forests may recover following fire or become locked into alternative development pathways by comparing biophysical factors of a reburned ecotone to those of an unburned (control) ecotone. We found that, (1) the significantly higher densities of P. uviferum trees and seedlings in the forested patches at both the reburned and control sites were associated with significantly lower seasonal water tables, lower cover of Sphagnum mosses and higher cover of other mosses (i.e., not in the Sphagnum or Dicranaloma genera); (2) despite abrupt boundaries in vegetation at both sites, successive fires homogenized the environment at the reburned site; and (3) the distinct life forms and individual species that characterized the understory plant communities across the ecotones affected seedling abundance by shaping microtopography and the substrates available for establishment. Together, our results suggest that fire can push edaphically wet P. uviferum-dominated sites towards a non-forested state by reducing the diversity of microsite structure and composition, thereby placing P. uviferum seedlings in direct competition with Sphagnum mosses and potentially limiting the availability of microsites that are protected from both seasonal inundation and seasonal drought. If wildfires continue under increasingly warmer and drier conditions, the forest-peatland ecotone of western Patagonia may be susceptible to large-scale transformation towards a non-forested state.