Insights into the tussock growth form with model-data fusion

Some rhizomatous grass and sedge species form tussocks that impact ecosystem structure and function. Despite their importance, tussock development and size controls are poorly understood due to the decadal to centennial timescales over which tussocks form. We explored mechanisms regulating tussock development and size in a ubiquitous arctic tussock sedge (Eriophorum vaginatum) using field observations and a mass balance model coupled with a tiller population model. Model-data fusion was used to quantify parameter and prediction uncertainty, determine model sensitivity, and test hypotheses on the factors regulating tussock size. The model accurately captured the dynamics of tussock development, characteristics, and size observed in the field. Tussock growth approached maximal size within several decades, which was determined by feedbacks between the mass balance of tussock root necromass and density-dependent tillering. The model also predicted that maximal tussock size was primarily regulated by tiller root productivity and necromass bulk density and less so by tiller demography. These predictions were corroborated by field observations of tussock biomass and root characteristics. The study highlights the importance of belowground processes in regulating tussock development and size and enhances our understanding of the influence of tussocks on arctic ecosystem structure and function.

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

An Open-Source, Durable, and Low-Cost Alternative to Commercially Available Soil Temperature Data Loggers

Soil temperatures play an important role in determining the distribution and function of organisms. However, soil temperature is decoupled from air temperature and varies widely in space. Characterizing and predicting soil temperature requires large and expensive networks of data loggers. We developed an open-source soil temperature data logger and created online resources to ensure our design was accessible. We tested data loggers constructed by students, with little prior electronics experience, in the lab, and in the field in Alaska. The do-it-yourself (DIY) data logger was comparably accurate to a commercial system with a mean absolute error of 2% from -20-0 °C and 1% from 0-20 °C. They captured accurate soil temperature data and performed reliably in the field with less than 10% failing in the first year of deployment. The DIY loggers were ~1.7-7 times less expensive than commercial systems. This work has the potential to increase the spatial resolution of soil temperature monitoring and serve as a powerful educational tool. The DIY soil temperature data logger will reduce data collection costs and improve our understanding of species distributions and ecological processes. It also provides an educational resource to enhance STEM, accessibility, inclusivity, and engagement.

Integrated Biological Risk and Cost Model Analysis Supports a Geopolitical Shift in Ballast Water Management

This work evaluates efficacies of plausible ballast water management strategies and standards by integrating a global species spread risk assessment with a policy cost-effectiveness analysis. Specifically, we consider species spread risks and costs of port- and vessel-based strategies under both current organism concentration standards and stricter standards proposed by California. For each scenario, we estimate species spread risks and patterns using a higher-order analysis of a global ship-borne species spread model and estimate fleet costs for vessel- and barge-based ballast water treatment systems for each standard. We find that stricter standards may reduce species spread risk by a factor of 17 globally and would greatly simplify the complex network of ship-borne species spread. The current policy of IMO standards is most cost-effectively achieved through ship-based treatment, and that any additional risk reduction will be most cost-effectively achieved by port-based (or barge-based) technologies, particularly if these are strategically implemented at the top ports within the largest clusters. Barge-based ballast water management would require a shift in governance, and we suggest that this next level of policymaking could be feasible for special areas designated by the IMO, by State or multistate authorities, or by voluntary port applications.

Network analysis of ballast-mediated species transfer reveals important introduction and dispersal patterns in the Arctic

Rapid climate change has wide-ranging implications for the Arctic region, including sea ice loss, increased geopolitical attention, and expanding economic activity resulting in a dramatic increase in shipping activity. As a result, the risk of harmful non-native marine species being introduced into this critical region will increase unless policy and management steps are implemented in response. Using data about shipping, ecoregions, and environmental conditions, we leverage network analysis and data mining techniques to assess, visualize, and project ballast water-mediated species introductions into the Arctic and dispersal of non-native species within the Arctic. We first identify high-risk connections between the Arctic and non-Arctic ports that could be sources of non-native species over 15 years (1997-2012) and observe the emergence of shipping hubs in the Arctic where the cumulative risk of non-native species introduction is increasing. We then consider how environmental conditions can constrain this Arctic introduction network for species with different physiological limits, thus providing a tool that will allow decision-makers to evaluate the relative risk of different shipping routes. Next, we focus on within-Arctic ballast-mediated species dispersal where we use higher-order network analysis to identify critical shipping routes that may facilitate species dispersal within the Arctic. The risk assessment and projection framework we propose could inform risk-based assessment and management of ship-borne invasive species in the Arctic.

SoilTemp: A global database of near-surface temperature

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Differential responses of ecotypes to climate in a ubiquitous Arctic sedge: implications for future ecosystem C cycling

The response of vegetation to climate change has implications for the carbon cycle and global climate. It is frequently assumed that a species responds uniformly across its range to climate change. However, ecotypes - locally adapted populations within a species - display differences in traits that may affect their gross primary productivity (GPP) and response to climate change. To determine if ecotypes are important for understanding the response of ecosystem productivity to climate we measured and modeled growing season GPP in reciprocally transplanted and experimentally warmed ecotypes of the abundant Arctic sedge Eriophorum vaginatum. Transplanted northern ecotypes displayed home-site advantage in GPP that was associated with differences in leaf area index. Southern ecotypes exhibited a greater response in GPP when transplanted. The results demonstrate that ecotypic differentiation can impact the morphology and function of vegetation with implications for carbon cycling. Moreover they suggest that ecotypic control of GPP may limit the response of ecosystem productivity to climate change. This investigation shows that ecotypes play a substantial role in determining GPP and its response to climate. These results have implications for understanding annual to decadal carbon cycling where ecotypes could influence ecosystem function and vegetation feedbacks to climate change.