Harnessing ecological theory to enhance ecosystem restoration.

Ecosystem restoration can increase the health and resilience of nature and humanity. As a result, the international community is championing habitat restoration as a primary solution to address the dual climate and biodiversity crises. Yet most ecosystem restoration efforts to date have underperformed, failed, or been burdened by high costs that prevent upscaling. To become a primary, scalable conservation strategy, restoration efficiency and success must increase dramatically. Here, we outline how integrating ten foundational ecological theories that have not previously received much attention - from hierarchical facilitation to macroecology - into ecosystem restoration planning and management can markedly enhance restoration success. We propose a simple, systematic approach to determining which theories best align with restoration goals and are most likely to bolster their success. Armed with a century of advances in ecological theory, restoration practitioners will be better positioned to more cost-efficiently and effectively rebuild the world's ecosystems and support the resilience of our natural resources.

Variation in genomic vulnerability to climate change across temperate populations of eelgrass (Zostera marina).

A global decline in seagrass populations has led to renewed calls for their conservation as important providers of biogenic and foraging habitat, shoreline stabilization and carbon storage. Eelgrass (Zostera marina) occupies the largest geographic range among seagrass species spanning a commensurately broad spectrum of environmental conditions. In Canada, eelgrass is managed as a single phylogroup despite occurring across three oceans and a range of ocean temperatures and salinity gradients. Previous research has focused on applying relatively few markers to reveal population structure of eelgrass, whereas a whole-genome approach is warranted to investigate cryptic structure among populations inhabiting different ocean basins and localized environmental conditions. We used a pooled whole-genome re-sequencing approach to characterize population structure, gene flow and environmental associations of 23 eelgrass populations ranging from the Northeast United States to Atlantic, subarctic and Pacific Canada. We identified over 500,000 SNPs, which when mapped to a chromosome-level genome assembly revealed six broad clades of eelgrass across the study area, with pairwise F ST ranging from 0 among neighbouring populations to 0.54 between Pacific and Atlantic coasts. Genetic diversity was highest in the Pacific and lowest in the subarctic, consistent with colonization of the Arctic and Atlantic oceans from the Pacific less than 300 kya. Using redundancy analyses and two climate change projection scenarios, we found that subarctic populations are predicted to be potentially more vulnerable to climate change through genomic offset predictions. Conservation planning in Canada should thus ensure that representative populations from each identified clade are included within a national network so that latent genetic diversity is protected, and gene flow is maintained. Northern populations, in particular, may require additional mitigation measures given their potential susceptibility to a rapidly changing climate.

Temperature dependence of competitive ability is cold-shifted compared to that of growth rate in marine phytoplankton.

The effect of climate warming on community composition is expected to be contingent on competitive outcomes, yet approaches to projecting ecological outcomes often rely on measures of density-independent performance across temperatures. Recent theory suggests that the temperature response of competitive ability differs in shape from that of population growth rate. Here, we test this hypothesis empirically and find thermal performance curves of competitive ability in aquatic microorganisms to be systematically left-shifted and flatter compared to those of exponential growth rate. The minimum resource requirement for growth, R*-an inverse indicator of competitive ability-changes with temperature following a U-shaped pattern in all four species tested, contrasting from their left-skewed density-independent growth rate thermal performance curves. Our results provide new evidence that exploitative competitive success is highest at temperatures that are sub-optimal for growth, suggesting performance estimates of density-independent variables might underpredict performance in cooler competitive environments.

Patient specific implants versus conventional implants in primary total knee arthroplasty: No significant difference in patient reported outcomes at 5 years.

Background: Patient specific implants (PSI) represent a novel innovation aimed to improve patient satisfaction and function after total knee arthroplasty (TKA); however, longitudinal patient reported outcome measures (PROMs) for PSI are not well described. We sought to primarily evaluate PROMs of patients undergoing TKA with either PSI or off-the-shelf (OTS) implants at mid-term follow-up. Methods: A retrospective review was performed on a prospectively collected cohort of 43 primary, cruciate-retaining TKAs performed with PSI (n = 23) and OTS implants (n = 20) by a single surgeon. Patient demographics, operative characteristics, range of motion (ROM) return, reoperations, and outcomes [Patient-Reported Outcomes Measurement Information System (PROMIS) T-score, Knee Injury and Osteoarthritis outcome score (KOOS), and Knee Society Score-Function (KSS-F)] were compared. Mean follow-up was 5 years. Results: TKA performed with either PSI and OTS implants demonstrated no difference in obtaining ROM by 3 months (extension 3° short of full extension vs. 0°, p = 0.16) or flexion (114° vs. 115°, p = 0.99) and final ROM was identical [0° extension to 120° flexion (p = 1)]. Although not significant (p = 0.42), 5 (22%) PSI TKA and 2 (10%) OTS implant patients required manipulation under anesthesia. KSS-F and PROMIS T-scores were higher in the PSI versus OTS TKA patients, respectively (90 vs. 73, p = 0.002; 51.6 vs. 44.5, p = 0.01). However, after multivariable analysis, none of these continuous outcome measures were significantly different (p = 0.28 for KSS and p = 0.45 for PROMIS T-score) between the groups. Conclusion: In a series of TKAs performed with PSI, no difference existed in postoperative ROM, reoperations, or patient-reported outcomes compared to OTS implants at 5 years. Surgeons may utilize the equivocal midterm results during TKA preoperative patient discussion of implant technologies.

Telemedical Interdisciplinary Care Team Evaluation and Treatment of People With Low Back Pain: A Retrospective Observational Study.

Objective: To evaluate the effects of an interdisciplinary care team (ICT) model delivered by telemedicine on patients with low back pain (LBP). Design: Retrospective analysis of deidentified pre-existing data. Setting: Retrospective observational study of patients presenting with LBP to a nationwide telemedicine practice using an ICT model. Participants: Over a 9-month period all patients with a diagnosis related to LBP and who had an ICT evaluation (medical doctor, advanced practice provider, health coach, and physical therapist) were included in the study (n=36). A minimum of 2 follow-up physical therapy visits were required for inclusion. Interventions: Patients were evaluated for LBP, received a diagnosis, and were offered a multidisciplinary treatment plan. Additional real-time audio visual medical, health coaching, registered dietician, and physical therapy services were received as deemed clinically appropriate. Main Outcome Measures: Baseline, 30 day, and final pain (mean 81 day) measurements via numerical pain rating scale (NPRS). Baseline and final Patient-Reported Outcomes Measurement Information System (PROMIS)-10 Global Mental/Physical domains. Secondary Outcome Measures: Use of prescription medication, referral for imaging, need for injections, or surgery. Results: 36 patients met criteria. Pain levels included mild (n=6, 16.7%), moderate (n=19, 52.8%), and severe (n=11, 30.6%). Clinically significant pain improvements were noted in 83.3% (n=25) of those with moderate or severe pain. PROMIS Mental and Physical Health categorization from Fair/Poor to Good/Excellent significantly improved over time. The initial 20% (n=7) in Fair/Poor Mental Health improved to 6.3% (n=2) at finish, while the 80% (n=28) in Good/Excellent Mental Health at start improved to 93.8% (n=30) at finish. Regarding Physical Health, 51.4% (n=18) rated Fair/Poor at start and 31.3% (n=10) at finish, while the 48.6% (n=17) rated Good/Excellent at start improved to 68.8% (n=22) at finish. The need for prescription medication was low (n=6, 16.7%) and spinal imaging orders were negligible (n=1, 2.8%). Injections were warranted in 11.4% (n=4) of patients and surgical referral with operative treatment in 2.8% (n=1). Conclusion: Interdisciplinary care delivered through telemedicine can significantly improve pain and support improved health-related quality of life in patients with LBP, with low rates of imaging, prescription, and interventional use.

The International Initiative to Measure Perceived Risk in Arthroplasty: The Results From a Multinational Survey.

BACKGROUND: There is an inherent moral imperative to avoid complications from arthroplasty. Doing so at ideal cost is also associated with surgeon reputation, and, increasingly in health care delivery systems that measure and competitively score outcomes, reimbursement to the surgeons and their hospitals. As a result, patients who are perceived to be in higher risk comorbidity groups, such as the obese and diabetics, as well as those challenged by socioeconomic factors may face barriers to access elective arthroplasty. METHODS: In this initiative, surveys were sent to surgeons in 8 different countries, each adapted for their own unique payment, remuneration, and punitive models. The questions in the surveys pertained to surgeons' perception of risk regarding medical and socioeconomic factors in patients indicated for total hip or knee arthroplasty. This paper primarily reports on the results from Canada, Ireland, and the United Kingdom. RESULTS: The health care systems varied between a universal/state funded health care system (Canada) to those that were almost exclusively private (India). Some health care systems have "bundled" payment with retention of fees for postoperative complications requiring readmission/reoperation and including some with public publication of outcome data (United States and the United Kingdom), whereas others had none (Canada). There were some major discrepancies across different countries regarding the perceived risk of diabetic patients, who have variable Hemoglobin A1c cut-offs, if any used. However, overall the perception of risk for age, body mass index, age, sex, socioeconomic, and social situations remained surprisingly consistent throughout the health care systems. Any limitations set were primarily driven by surgeon decision making and not external demands. CONCLUSION: Surgeons will understandably try and optimize the health status of patients who have reversible risks as shown by best available evidence. The evidence is of variable quality, and, especially for irreversible social risk factors, limited due to concerns over cost and quality outcomes that can be influenced by experience-driven perceptions of risk. The results show that perceptions of risk do have such influence on access across many health care delivery environments. The authors recommend better risk-adjustment models for medical and socioeconomic risk factors with possible stratification/exclusions regarding reimbursement adjustments and reporting to help reverse disparities of access to arthroplasty.

Theory and application of an improved species richness estimator.

Species richness is an essential biodiversity variable indicative of ecosystem states and rates of invasion, speciation and extinction both contemporarily and in fossil records. However, limited sampling effort and spatial aggregation of organisms mean that biodiversity surveys rarely observe every species in the survey area. Here we present a non-parametric, asymptotic and bias-minimized richness estimator, Ω by modelling how spatial abundance characteristics affect observation of species richness. Improved asymptotic estimators are critical when both absolute richness and difference detection are important. We conduct simulation tests and applied Ω to a tree census and a seaweed survey. Ω consistently outperforms other estimators in balancing bias, precision and difference detection accuracy. However, small difference detection is poor with any asymptotic estimator. An R-package, Richness, performs the proposed richness estimations along with other asymptotic estimators and bootstrapped precisions. Our results explain how natural and observer-induced variations affect species observation, how these factors can be used to correct observed richness using the estimator Ω on a variety of data, and why further improvements are critical for biodiversity assessments. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

A framework for the detection and attribution of biodiversity change.

The causes of biodiversity change are of great scientific interest and central to policy efforts aimed at meeting biodiversity targets. Changes in species diversity and high rates of compositional turnover have been reported worldwide. In many cases, trends in biodiversity are detected, but these trends are rarely causally attributed to possible drivers. A formal framework and guidelines for the detection and attribution of biodiversity change is needed. We propose an inferential framework to guide detection and attribution analyses, which identifies five steps-causal modelling, observation, estimation, detection and attribution-for robust attribution. This workflow provides evidence of biodiversity change in relation to hypothesized impacts of multiple potential drivers and can eliminate putative drivers from contention. The framework encourages a formal and reproducible statement of confidence about the role of drivers after robust methods for trend detection and attribution have been deployed. Confidence in trend attribution requires that data and analyses used in all steps of the framework follow best practices reducing uncertainty at each step. We illustrate these steps with examples. This framework could strengthen the bridge between biodiversity science and policy and support effective actions to halt biodiversity loss and the impacts this has on ecosystems. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

The sizes of life.

Recent research has revealed the diversity and biomass of life across ecosystems, but how that biomass is distributed across body sizes of all living things remains unclear. We compile the present-day global body size-biomass spectra for the terrestrial, marine, and subterranean realms. To achieve this compilation, we pair existing and updated biomass estimates with previously uncatalogued body size ranges across all free-living biological groups. These data show that many biological groups share similar ranges of body sizes, and no single group dominates size ranges where cumulative biomass is highest. We then propagate biomass and size uncertainties and provide statistical descriptions of body size-biomass spectra across and within major habitat realms. Power laws show exponentially decreasing abundance (exponent -0.9±0.02 S.D., R2 = 0.97) and nearly equal biomass (exponent 0.09±0.01, R2 = 0.56) across log size bins, which resemble previous aquatic size spectra results but with greater organismal inclusivity and global coverage. In contrast, a bimodal Gaussian mixture model describes the biomass pattern better (R2 = 0.86) and suggests small (~10-15 g) and large (~107 g) organisms outweigh other sizes by one order magnitude (15 and 65 Gt versus ~1 Gt per log size). The results suggest that the global body size-biomass relationships is bimodal, but substantial one-to-two orders-of-magnitude uncertainty mean that additional data will be needed to clarify whether global-scale universal constraints or local forces shape these patterns.

The fitness value of ecological information in a variable world.

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for 'fitness value of information' (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Effects of thermal fluctuations on biological processes: a meta-analysis of experiments manipulating thermal variability.

Thermal variability is a key driver of ecological processes, affecting organisms and populations across multiple temporal scales. Despite the ubiquity of variation, biologists lack a quantitative synthesis of the observed ecological consequences of thermal variability across a wide range of taxa, phenotypic traits and experimental designs. Here, we conduct a meta-analysis to investigate how properties of organisms, their experienced thermal regime and whether thermal variability is experienced in either the past (prior to an assay) or present (during the assay) affect performance relative to the performance of organisms experiencing constant thermal environments. Our results-which draw upon 1712 effect sizes from 75 studies-indicate that the effects of thermal variability are not unidirectional and become more negative as mean temperature and fluctuation range increase. Exposure to variation in the past decreases performance to a greater extent than variation experienced in the present and increases the costs to performance more than diminishing benefits across a broad set of empirical studies. Further, we identify life-history attributes that predictably modify the ecological response to variation. Our findings demonstrate that effects of thermal variability on performance are context-dependent, yet negative outcomes may be heightened in warmer, more variable climates.