Predicting emergent animal biodiversity patterns across multiple scales.

Restoring biodiversity-based resilience and ecosystem multi-functionality needs to be informed by more accurate predictions of animal biodiversity responses to environmental change. Ecological models make a substantial contribution to this understanding, especially when they encode the biological mechanisms and processes that give rise to emergent patterns (population, community, ecosystem properties and dynamics). Here, a distinction between 'mechanistic' and 'process-based' ecological models is established to review existing approaches. Mechanistic and process-based ecological models have made key advances to understanding the structure, function and dynamics of animal biodiversity, but are typically designed to account for specific levels of biological organisation and spatiotemporal scales. Cross-scale ecological models, which predict emergent co-occurring biodiversity patterns at interacting scales of space, time and biological organisation, is a critical next step in predictive ecology. A way forward is to first capitalise on existing models to systematically evaluate the ability of scale-explicit mechanisms and processes to predict emergent patterns at alternative scales. Such model intercomparisons will reveal mechanism to process transitions across fine to broad scales, overcome approach-specific barriers to model realism or tractability and identify gaps which necessitate the development of new fundamental principles. Key challenges surrounding model complexity and uncertainty would need to be addressed, and while opportunities from big data can streamline the integration of multiple scale-explicit biodiversity patterns, ambitious cross-scale field studies are also needed. Crucially, overcoming cross-scale ecological modelling challenges would unite disparate fields of ecology with the common goal of improving the evidence-base to safeguard biodiversity and ecosystems under novel environmental change.

Temperature thresholds of ecosystem respiration at a global scale.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.

Mechanistic Effect Modeling of Earthworms in the Context of Pesticide Risk Assessment: Synthesis of the FORESEE Workshop.

Earthworms are important ecosystem engineers, and assessment of the risk of plant protection products toward them is part of the European environmental risk assessment (ERA). In the current ERA scheme, exposure and effects are represented simplistically and are not well integrated, resulting in uncertainty when the results are applied to ecosystems. Modeling offers a powerful tool to integrate the effects observed in lower tier laboratory studies with the environmental conditions under which exposure is expected in the field. This paper provides a summary of the (In)Field Organism Risk modEling by coupling Soil Exposure and Effect (FORESEE) Workshop held 28-30 January 2020 in Düsseldorf, Germany. This workshop focused on toxicokinetic-toxicodynamic (TKTD) and population modeling of earthworms in the context of ERA. The goal was to bring together scientists from different stakeholder groups to discuss the current state of soil invertebrate modeling and to explore how earthworm modeling could be applied to risk assessments, in particular how the different model outputs can be used in the tiered ERA approach. In support of these goals, the workshop aimed at addressing the requirements and concerns of the different stakeholder groups to support further model development. The modeling approach included 4 submodules to cover the most relevant processes for earthworm risk assessment: environment, behavior (feeding, vertical movement), TKTD, and population. Four workgroups examined different aspects of the model with relevance for risk assessment, earthworm ecology, uptake routes, and cross-species extrapolation and model testing. Here, we present the perspectives of each workgroup and highlight how the collaborative effort of participants from multidisciplinary backgrounds helped to establish common ground. In addition, we provide a list of recommendations for how earthworm TKTD modeling could address some of the uncertainties in current risk assessments for plant protection products. Integr Environ Assess Manag 2021;17:352-363. © 2020 SETAC.

Multiple environmental controls explain global patterns in soil animal communities.

Soil animals play important roles in ecosystem functioning and stability, but the environmental controls on their communities are not fully understood. In this study, we compiled a dataset of soil animal communities for which the abundance and body mass of multiple soil animal groups were recorded. The mass-abundance scaling relationships were then used to investigate multiple environmental controls on soil animal community composition. The data reveal latitudinal shifts from high abundances of small soil animals at high latitudes to greater relative abundances of large soil animals at low latitudes. A hierarchical linear mixed effects model was applied to reveal the environmental variables shaping these latitudinal trends. The final hierarchical model identified mean annual temperature, soil pH and soil organic carbon content as key environmental controls explaining global mass-abundance scaling relationships in soil animal communities (R2c = 0.828, Ngroup = 117). Such relationships between soil biota with climate and edaphic conditions have been previously identified for soil microbial, but not soil animal, communities at a global scale. More comprehensive global soil community datasets are needed to better understand the generality of these relationships over a broader range of global ecosystems and soil animal groups.

MicroRNA Profiling in Adipose Before and After Weight Loss Highlights the Role of miR-223-3p and the NLRP3 Inflammasome.

OBJECTIVE: Adipose tissue plays a key role in obesity-related metabolic dysfunction. MicroRNA (miRNA) are gene regulatory molecules involved in intercellular and inter-organ communication. It was hypothesized that miRNA levels in adipose tissue would change after gastric bypass surgery and that this would provide insights into their role in obesity-induced metabolic dysregulation. METHODS: miRNA profiling (Affymetrix GeneChip miRNA 2.0 Array) of omental and subcutaneous adipose (n = 15 females) before and after gastric bypass surgery was performed. RESULTS: One omental and thirteen subcutaneous adipose miRNAs were significantly differentially expressed after gastric bypass, including downregulation of miR-223-3p and its antisense relative miR-223-5p in both adipose tissues. mRNA levels of miR-223-3p targets NLRP3 and GLUT4 were decreased and increased, respectively, following gastric bypass in both adipose tissues. Significantly more NLRP3 protein was observed in omental adipose after gastric bypass (P = 0.02). Significant hypomethlyation of NLRP3 and hypermethylation of miR-223 were observed in both adipose tissues after gastric bypass. In subcutaneous adipose, significant correlations were observed between both miR-223-3p and miR-223-5p and glucose and between NLRP3 mRNA and protein levels and blood lipids. CONCLUSIONS: This is the first report detailing genome-wide miRNA profiling of omental adipose before and after gastric bypass, and it further highlights the association of miR-223-3p and the NLRP3 inflammasome with obesity.

How do we know what we don't know? Exploring Deaf people's experiences of supporting their Deaf family member living with dementia.

Deaf sign language users living with dementia and their carers, some of whom are Deaf, routinely face everyday barriers in accessing information, support (both formal and informal) and services. The familial care situation is further complicated given that most Deaf people will choose a life partner who is Deaf and most Deaf couples will have hearing children. This study focussed specifically on the everyday experiences of Deaf carers and the impact of caring for a loved one with dementia. Drawing on data from a wider consultation about dementia care, three Deaf carers were directly interviewed in British Sign Language by a Deaf researcher about their everyday experiences of care, support, and services. Thematic analysis focussed on: access is more than the provision of interpreters; effective care for the carers; and unknowing risk taking. Findings demonstrate the multifaceted effects of barriers to knowledge and information when the care partner is also Deaf, the urgent need for effective support for Deaf carers and unrecognised safeguarding concerns that are a result of lack of access to forms of basic knowledge about living with someone with dementia and potential coping strategies. Nonetheless, the participants demonstrated novel solutions and resilience in the face of these multiple challenges. Implications are drawn for future targeted services to supported Deaf carers of people affected by dementia.

The influence of soil communities on the temperature sensitivity of soil respiration.

Soil respiration represents a major carbon flux between terrestrial ecosystems and the atmosphere, and is expected to accelerate under climate warming. Despite its importance in climate change forecasts, however, our understanding of the effects of temperature on soil respiration (RS) is incomplete. Using a metabolic ecology approach we link soil biota metabolism, community composition and heterotrophic activity to predict RS rates across five biomes. We find that accounting for the ecological mechanisms underpinning decomposition processes predicts climatological RS variations observed in an independent dataset (n = 312). The importance of community composition is evident because without it RS is substantially underestimated. With increasing temperature, we predict a latitudinal increase in RS temperature sensitivity, with Q10 values ranging between 2.33 ± 0.01 in tropical forests to 2.72 ± 0.03 in tundra. This global trend has been widely observed, but has not previously been linked to soil communities.

A risk assessment example for soil invertebrates using spatially explicit agent-based models.

Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier, population-level effects are assessed using semifield and field trials at a higher tier because modeling methods for extrapolating available lower-tier information to population effects have not yet been implemented. Field trials are expensive, time consuming, and cannot be applied to variable landscape scenarios. Mechanistic modeling of the toxicological effects of PPPs on individuals and their responses combined with simulation of population-level response shows great potential in fulfilling such a need, aiding ecologically informed extrapolation. Here, we introduce and demonstrate the potential of 2 population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed "overall"], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover within 1 year after pesticide application, regardless of application method. The population modeling for both soil organisms also illustrated that a lower predicted average environmental concentration in soil (PECsoil) could potentially lead to greater effects at the population level, depending on the spatial heterogeneity of the pesticide and the behavior of the soil organisms. Population-level effects of spatial-temporal variations in exposure were elucidated in the refined risk assessment, using ABMs and population-level endpoints while yielding outputs that directly address the protection goals. We recommend choosing model outputs that are closely related to specific protection goals, using available toxicity data and accepted fate models to the extent possible in parameterizing models to minimize additional data needs and testing, evaluating, and documenting models following recent guidance.