An assessment of statistical methods for nonindependent data in ecological meta‐analyses

A global meta-analysis on the effects of organic and inorganic fertilization on grasslands and croplands

A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss.

Biochar improves the nutrient cycle in sandy-textured soils and increases crop yield: a systematic review

BACKGROUND

Biochar is a relatively new development in sustainable agricultural management that can be applied to ameliorate degraded and less fertile soils, especially sandy-textured ones, to improve their productivity with respect to crop production through improved nutrient availability. However, as the literature has shown, the response of sandy-textured soils to biochar varies in terms of effect size and direction. Therefore, the present study systematically reviewed the available evidence to synthesize the impact of biochar amendments on aspects of the nutrient cycle of sandy-textured soils.

METHODS

Both peer-reviewed and gray literature were searched in English in bibliographic databases, organizational web pages, and Internet search engines. Articles underwent a two-stage screening (title and abstract, and full-text) based on predefined criteria, with consistency checks. Validity assessments were conducted, utilizing specifically designed tools for study validity. Data extraction involved categorizing the various properties of the nutrient cycle into nine main Soil and Plant Properties (SPPs), each of which was studied independently. Nine meta-analyses were performed using a total of 1609 observations derived from 92 articles. Comparing meta-averages with and without correction for publication bias suggests that publication bias plays a minor role in the literature, while some indication for publication bias is found when accounting for heterogeneity by means of meta-regressions.

REVIEW FINDINGS

According to the results, soil total and available nitrogen [N], phosphorous [P] and potassium [K], plant nutrient level, and potential cation exchange capacity (CEC) increased by 36% (CI [23%, 50%]), 34% (CI [15%, 57%]), 15% (CI [1%, 31%]), and 18% (CI [3%, 36%), respectively, and N2O emission and mineral nutrient leaching decreased by 29% (CI [- 48%, - 3%]) and 38% (CI [- 56%, - 13%). On average, however, biochar had no effect on soil mineral nitrogen and nutrient use efficiency. Publication bias was identified in the response of effective CEC. After corrections for publication bias, the response shifted from 36% to a negative value of - 34% (CI [- 50%, - 14%]). Meta-regression found that the effect modifiers experimental continent, biochar application rate, and soil pH, explain result heterogeneity. Stronger responses came from the continent of South America, higher application rates, and higher pH soils. Overall, biochar is found useful for many SPPs of nutrient cycling of sandy-textured soils, thereby contributing to increased crop yields in such soils.

Biodiversity survey and estimation for line-transect sampling

Conducting biodiversity surveys using a fully randomised design can be difficult due to budgetary constraints (e.g., the cost of labour), site accessibility, and other constraints. To this end, ecologists usually select representative line transects or quadrats from a studied area to collect individuals of a given species and use this information to estimate the levels of biodiversity over an entire region. However, commonly used biodiversity estimators such as Rao's quadratic diversity index (and especially the Gini-Simpson index) were developed based on the assumption of independent sampling of individuals. Therefore, their performance can be compromised or even misleading when applied to species abundance datasets that are collected from non-independent sampling. In this study, we utilise a Markov chain model and derive an associated parameter estimator to account for non-independence in sequential sampling. Empirical tests on two forest plots in tropical (Barro Colorado, Island of Panama) and subtropical (Heishiding Nature Reserve of Guangdong, China) regions and the continental-scale spatial distribution of Acacia species in Australia showed that our estimators performed reasonably well. The estimated parameter measuring the degree of non-independence of subsequent sampling showed that a non-independent effect is very likely to occur when using line transects to sample organisms in subtropical regions at both local and regional spatial scales. In summary, based on a first-order Markov sampling model and using Rao's quadratic diversity index as an example, our study provides an improvement in diversity estimation while simultaneously accounting for the non-independence of sampling in field biodiversity surveys. Our study presents one possible solution for addressing the non-independent sampling of individuals in biodiversity surveys.

A meta-evaluation of the quality of reporting and execution in ecological meta-analyses

Quantitatively summarizing results from a collection of primary studies with meta-analysis can help answer ecological questions and identify knowledge gaps. The accuracy of the answers depends on the quality of the meta-analysis. We reviewed the literature assessing the quality of ecological meta-analyses to evaluate current practices and highlight areas that need improvement. From each of the 18 review papers that evaluated the quality of meta-analyses, we calculated the percentage of meta-analyses that met criteria related to specific steps taken in the meta-analysis process (i.e., execution) and the clarity with which those steps were articulated (i.e., reporting). We also re-evaluated all the meta-analyses available from Pappalardo et al. [1] to extract new information on ten additional criteria and to assess how the meta-analyses recognized and addressed non-independence. In general, we observed better performance for criteria related to reporting than for criteria related to execution; however, there was a wide variation among criteria and meta-analyses. Meta-analyses had low compliance with regard to correcting for phylogenetic non-independence, exploring temporal trends in effect sizes, and conducting a multifactorial analysis of moderators (i.e., explanatory variables). In addition, although most meta-analyses included multiple effect sizes per study, only 66% acknowledged some type of non-independence. The types of non-independence reported were most often related to the design of the original experiment (e.g., the use of a shared control) than to other sources (e.g., phylogeny). We suggest that providing specific training and encouraging authors to follow the PRISMA EcoEvo checklist recently developed by O'Dea et al. [2] can improve the quality of ecological meta-analyses.

Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations

Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.

Meta-analysis of ecosystem services associated with oyster restoration

Restoration of foundation species promises to reverse environmental degradation and return lost ecosystem services, but a lack of standardized evaluation across projects limits understanding of recovery, especially in marine systems. Oyster reefs are restored to reverse massive global declines and reclaim valuable ecosystem services, but the success of these projects has not been systematically and comprehensively quantified. We synthesized data on ecosystem services associated with oyster restoration from 245 pairs of restored and degraded reefs and 136 pairs of restored and reference reefs across 3500 km of U.S. Gulf of Mexico and Atlantic coastlines. On average, restoration was associated with a 21-fold increase in oyster production (mean log response ratio = 3.08 [95% confidence interval: 2.58-3.58]), 34-97% enhancement of habitat provisioning (mean community abundance = 0.51 [0.41-0.61], mean richness = 0.29 [0.19-0.39], and mean biomass = 0.69 [0.39-0.99]), 54% more nitrogen removal (mean = 0.43 [0.13-0.73]), and 89-95% greater sediment nutrients (mean = 0.67 [0.27-1.07]) and organic matter (mean = 0.64 [0.44-0.84]) relative to degraded habitats. Moreover, restored reefs matched reference reefs for these ecosystem services. Our results support the continued and expanded use of oyster restoration to enhance ecosystem services of degraded coastal systems and match many functions provided by reference reefs.

Decline of insects and arachnids driven by nutrient enrichment: A meta-analysis

Recent studies have documented global declines in insects and their relatives, but the exact mechanisms explaining these patterns are not fully understood. A potential driver underlying arthropod population declines is increases in anthropogenic inputs of nitrogen (N) and phosphorus (P). Here, we synthesize the effects of N, P, and combined N + P enrichment on the abundance of hexapods (insects and collembola) and arachnids from 901 experiments reported in 84 studies. We found that N and combined N + P enrichment caused significant decreases in the abundance of these groups overall. While arthropod responses to nutrient enrichment across aquatic and terrestrial habitats and in temperate as well as tropical climatic zones differed in magnitude, our results suggest that arthropods are decreasing similarly in response to nitrogen and phosphorus enrichment. Further, despite previously shown differences in the nutrient demands of different insect metamorphosis groups, we found consistent negative effects of N + P enrichment on all groups. Our results also showed that the negative effects of nutrient additions are stronger for aquatic insects that are considered more sensitive to changes in physical-chemical parameters in their environments, Ephemeroptera, Plecoptera, and Trichoptera (EPT), compared with other aquatic insects. In addition, N + P enrichment reduced the abundance of above-ground and below-ground arthropods, suggesting that a similar mechanism driving arthropod community change is acting on both groups. These findings suggest that changes in elemental cycles are a potential cause of the ongoing global decline of arthropods and underscore the serious effects of nutrient enrichment on ecological systems.

Acoustic indices as proxies for biodiversity: a meta-analysis

As biodiversity decreases worldwide, the development of effective techniques to track changes in ecological communities becomes an urgent challenge. Together with other emerging methods in ecology, acoustic indices are increasingly being used as novel tools for rapid biodiversity assessment. These indices are based on mathematical formulae that summarise the acoustic features of audio samples, with the aim of extracting meaningful ecological information from soundscapes. However, the application of this automated method has revealed conflicting results across the literature, with conceptual and empirical controversies regarding its primary assumption: a correlation between acoustic and biological diversity. After more than a decade of research, we still lack a statistically informed synthesis of the power of acoustic indices that elucidates whether they effectively function as proxies for biological diversity. Here, we reviewed studies testing the relationship between diversity metrics (species abundance, species richness, species diversity, abundance of sounds, and diversity of sounds) and the 11 most commonly used acoustic indices. From 34 studies, we extracted 364 effect sizes that quantified the magnitude of the direct link between acoustic and biological estimates and conducted a meta-analysis. Overall, acoustic indices had a moderate positive relationship with the diversity metrics (r = 0.33, CI [0.23, 0.43]), and showed an inconsistent performance, with highly variable effect sizes both within and among studies. Over time, studies have been increasingly disregarding the validation of the acoustic estimates and those examining this link have been progressively reporting smaller effect sizes. Some of the studied indices [acoustic entropy index (H), normalised difference soundscape index (NDSI), and acoustic complexity index (ACI)] performed better in retrieving biological information, with abundance of sounds (number of sounds from identified or unidentified species) being the best estimated diversity facet of local communities. We found no effect of the type of monitored environment (terrestrial versus aquatic) and the procedure for extracting biological information (acoustic versus non-acoustic) on the performance of acoustic indices, suggesting certain potential to generalise their application across research contexts. We also identified common statistical issues and knowledge gaps that remain to be addressed in future research, such as a high rate of pseudoreplication and multiple unexplored combinations of metrics, taxa, and regions. Our findings confirm the limitations of acoustic indices to efficiently quantify alpha biodiversity and highlight that caution is necessary when using them as surrogates of diversity metrics, especially if employed as single predictors. Although these tools are able partially to capture changes in diversity metrics, endorsing to some extent the rationale behind acoustic indices and suggesting them as promising bases for future developments, they are far from being direct proxies for biodiversity. To guide more efficient use and future research, we review their principal theoretical and practical shortcomings, as well as prospects and challenges of acoustic indices in biodiversity assessment. Altogether, we provide the first comprehensive and statistically based overview on the relation between acoustic indices and biodiversity and pave the way for a more standardised and informed application for biodiversity monitoring.

Crop diversification and parasitic weed abundance: a global meta-analysis

Parasitic weeds cause huge annual losses to food production globally. A small number of species from the genera Cuscuta, Orobanche, Phelipanche and Striga have proliferated across many agroecological zones. Their control is compromised due to the lack of efficacy of conventional herbicides and their rapid adaptation to new resistant crop cultivars. A broad range of studies suggest consistent reductions in parasitic weed densities owing to increased spatial (intercropping) and temporal diversity (crop rotation). However, to date, no synthesis of this body of research has been published. Here we report the results of a meta-analysis using 1525 paired observations from 67 studies across 24 countries, comparing parasitic weed density and crop yields from monocrop and more diverse cropping systems. We found both spatial and temporal crop diversification had a significant effect on parasitic weed density reduction. Furthermore, our results show effects of spatial diversification are stronger in suppressing parasitic weeds than temporal effects. Furthermore, the analysis indicates intercrops which alter both microclimate and soil chemistry (e.g. Crotalaria, Stylosanthes, Berseem clover and Desmodium) are most effective in parasitic weed management. This analysis serves to underline the viability of crop diversification as a tool to enhance food security globally.

Eco-evolutionary causes and consequences of rarity in plants: a meta-analysis

Species differ dramatically in their prevalence in the natural world, with many species characterized as rare due to restricted geographic distribution, low local abundance and/or habitat specialization. We investigated the ecoevolutionary causes and consequences of rarity with phylogenetically controlled metaanalyses of population genetic diversity, fitness and functional traits in rare and common congeneric plant species. Our syntheses included 252 rare species and 267 common congeners reported in 153 peer-reviewed articles published from 1978 to 2020 and one manuscript in press. Rare species have reduced population genetic diversity, depressed fitness and smaller reproductive structures than common congeners. Rare species also could suffer from inbreeding depression and reduced fertilization efficiency. By limiting their capacity to adapt and migrate, these characteristics could influence contemporary patterns of rarity and increase the susceptibility of rare species to rapid environmental change. We recommend that future studies present more nuanced data on the extent of rarity in focal species, expose rare and common species to ecologically relevant treatments, including reciprocal transplants, and conduct quantitative genetic and population genomic analyses across a greater array of systems. This research could elucidate the processes that contribute to rarity and generate robust predictions of extinction risks under global change.

Decline effects are rare in ecology

The scientific evidence base on any given topic changes over time as more studies are published. Currently, there is widespread concern about non-random, directional changes over time in the scientific evidence base associated with many topics. In particular, if studies finding large effects (e.g., large differences between treatment and control means) tend to get published quickly, while small effects tend to get published slowly, the net result will be a decrease over time in the estimated magnitude of the mean effect size, known as a "decline effect". If decline effects are common, then the published scientific literature will provide a biased and misleading guide to management decisions, and to the allocation of future research effort. We compiled data from 466 meta-analyses in ecology to look for evidence of decline effects. We found that decline effects are rare. Only ~5% of ecological meta-analyses truly exhibit a directional change in mean effect size over time arising for some reason other than random chance, usually but not always in the direction of decline. Most apparent directional changes in mean effect size over time are attributable to regression to the mean, consistent with primary studies being published in random order with respect to the effect sizes they report. Our results are good news: decline effects are the exception to the rule in ecology. Identifying and rectifying rare cases of true decline effects remains an important task, but ecologists should not overgeneralize from anecdotal reports of decline effects.

A categorical assessment of dose-response dynamics for managing suspended sediment effects on salmonids

Many studies have investigated the consequences of exposure to fine-grained suspended sediments (SS) on aquatic organisms. Exposure has two components-concentration and duration-and can be expressed as dose, where we define suspended sediment dose (SSD: mg·h·L^-1) as the product of suspended sediment concentration (SSC: mg·L^-1) and duration of exposure (DoE: h). We evaluated these three measurement endpoints for managing SS effects on salmonids by assembling and analyzing all published SS dose-response observations. Despite a prevalence in SS management guidelines for using SSC as a primary endpoint to manage SS effects on salmonids, SSC was found to be less effective than SSD or DoE as a predictor variable for the available dose-response observations. We used data visualization to identify trends and distinct response categories that were then evaluated using a logistic regression model that accounts for nested observations by study. The model estimates the probability of moving from behavioural to major physiological and lethal responses in the available literature, as explained by one or more predictor variables, including ln(SSC), ln(DoE), ln(SSD), and life stage (adult versus juvenile). Akaike Information Criterion (AIC) and receiver operating characteristic (ROC) were used to compare model fit and classification performance, respectively, among alternative models. The best performing model as judged by AIC and ROC incorporated ln(SSD) as the predictor variable.

Arbuscular mycorrhizal fungi increase crop yields by improving biomass under rainfed condition: a meta-analysis

BACKGROUND

Rainfed agriculture plays key role in ensuring food security and maintain ecological balance. Especially in developing areas, most grain food are produced rainfed agricultural ecosystem. Therefore, the increase of crop yields in rainfed agricultural ecosystem becomes vital as well as ensuring global food security.

METHODS

The potential roles of arbuscular mycorrhizal fungi (AMF) in improving crop yields under rainfed condition were explored based on 546 pairs of observations published from 1950 to 2021.

RESULTS

AMF inoculation increased 23.0% crop yields based on 13 popular crops under rainfed condition. Not only was crop biomass of shoot and root increased 24.2% and 29.6% by AMF inocula, respectively but also seed number and pod/fruit number per plant were enhanced markedly. Further, the effect of AMF on crop yields depended on different crop groups. AMF improved more yield of N-fixing crops than non-N-fixing crops. The effect of AMF changed between grain and non-grain crops with the effect size of 0.216 and 0.352, respectively. AMF inoculation enhances stress resistance and photosynthesis of host crop in rainfed agriculture.

CONCLUSION

AMF increased crop yields by enhancing shoot biomass due to the improvement of plant nutrition, photosynthesis, and stress resistance in rainfed field. Our findings provide a new view for understanding the sustainable productivity in rainfed agroecosystem, which enriched the theory of AMF functional diversity. This study provided a theoretical and technical way for sustainable production under rainfed agriculture.

An assessment of statistical methods for non-independent data in ecological meta-analyses: Comment

Recently, Song et al. (2020) conducted a simulation study using different methods to deal with non-independence resulting from effect sizes originating from the same paper - a common occurrence in ecological meta-analyses. The main methods that were of interest in their simulations were: 1) a standard random-effects model used in combination with a weighted average effect size for each paper (i.e., a two-step method), 2) a standard random-effects model after randomly choosing one effect size per paper, 3) a multilevel (hierarchical) meta-analysis model, modelling paper identity as a random factor, and 4) a meta-analysis making use of a robust variance estimation method. Based on their simulation results, they recommend that meta-analysts should either use the two-step method, which involves taking a weighted paper mean followed by analysis with a random-effects model, or the robust variance estimation method.

Nitrogen and phosphorus enrichment cause declines in invertebrate populations: a global meta-analysis

Human-driven changes in nitrogen (N) and phosphorus (P) inputs are modifying biogeochemical cycles and the trophic state of many habitats worldwide. These alterations are predicted to continue to increase, with the potential for a wide range of impacts on invertebrates, key players in ecosystem-level processes. Here, we present a meta-analysis of 1679 cases from 207 studies reporting the effects of N, P, and combined N + P enrichment on the abundance, biomass, and richness of aquatic and terrestrial invertebrates. Nitrogen and phosphorus additions decreased invertebrate abundance in terrestrial and aquatic ecosystems, with stronger impacts under combined N + P additions. Likewise, N and N + P additions had stronger negative impacts on the abundance of tropical than temperate invertebrates. Overall, the effects of nutrient enrichment did not differ significantly among major invertebrate taxonomic groups, suggesting that changes in biogeochemical cycles are a pervasive threat to invertebrate populations across ecosystems. The effects of N and P additions differed significantly among invertebrate trophic groups but N + P addition had a consistent negative effect on invertebrates. Nutrient additions had weaker or inconclusive impacts on invertebrate biomass and richness, possibly due to the low number of case studies for these community responses. Our findings suggest that N and P enrichment affect invertebrate community structure mainly by decreasing invertebrate abundance, and these effects are dependent on the habitat and trophic identity of the invertebrates. These results highlight the important effects of human-driven nutrient enrichment on ecological systems and suggest a potential driver for the global invertebrate decline documented in recent years.

Nitrogen addition stimulates soil aggregation and enhances carbon storage in terrestrial ecosystems of China: A meta-analysis

China is experiencing a high level of atmospheric nitrogen (N) deposition, which greatly affects the soil carbon (C) dynamics in terrestrial ecosystems. Soil aggregation contributes to the stability of soil structure and to soil C sequestration. Although many studies have reported the effects of N enrichment on bulk soil C dynamics, the underlying mechanisms explaining how soil aggregates respond to N enrichment remain unclear. Here, we used a meta-analysis of data from 76N manipulation experiments in terrestrial ecosystems in China to assess the effects of N enrichment on soil aggregation and its sequestration of C. On average, N enrichment significantly increased the mean weight diameter of soil aggregates by 10%. The proportion of macroaggregates and silt-clay fraction were significantly increased (6%) and decreased (9%) by N enrichment, respectively. A greater response of macroaggregate C (+15%) than of bulk soil C (+5%) to N enrichment was detected across all ecosystems. However, N enrichment had minor effects on microaggregate C and silt-clay C. The magnitude of N enrichment effect on soil aggregation varied with ecosystem type and fertilization regime. Additionally, soil pH declined consistently and was correlated with soil aggregate C. Overall, our meta-analysis suggests that N enrichment promotes particulate organic C accumulation via increasing macroaggregate C and acidifying soils. In contrast, increases in soil aggregation could inhibit microbially mediated breakdown of soil organic matter, causing minimal change in mineral-associated organic C. Our findings highlight that atmospheric N deposition may enhance the formation of soil aggregates and their sequestration of C in terrestrial ecosystems in China.