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Journal articleMorris OF, Loewen CJG, Woodward G, et al., 2022,
Local stressors mask the effects of warming in freshwater ecosystems
, Ecology Letters, Vol: 25, Pages: 2540-2551, ISSN: 1461-023XClimate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.
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Journal articleMatthews TJ, Wayman JP, Cardoso P, et al., 2022,
Threatened and extinct island endemic birds of the world: Distribution, threats and functional diversity
, JOURNAL OF BIOGEOGRAPHY, Vol: 49, Pages: 1920-1940, ISSN: 0305-0270- Author Web Link
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- Citations: 9
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Journal articleJoshi J, Stocker B, Hofhansl F, et al., 2022,
Towards a unified theory of plant photosynthesis and hydraulics
, Nature Plants, Vol: 8, Pages: 1304-1316, ISSN: 2055-026XThe global carbon and water cycles are governed by the coupling of CO2 and water vapour exchanges through the leaves of terrestrial plants, controlled by plant adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to environments changing on multiple timescales. Tested with experimental data from 18 species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature and CO2. Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO2 on global photosynthesis and transpiration.
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Journal articleGarrood WT, Cuber P, Willis K, et al., 2022,
Driving down malaria transmission with engineered gene drives
, FRONTIERS IN GENETICS, Vol: 13, Pages: 1-17The last century has witnessed the introduction, establishment and expansion of mosquito-borne diseases into diverse new geographic ranges. Malaria is transmitted by female Anopheles mosquitoes. Despite making great strides over the past few decades in reducing the burden of malaria, transmission is now on the rise again, in part owing to the emergence of mosquito resistance to insecticides, antimalarial drug resistance and, more recently, the challenges of the COVID-19 pandemic, which resulted in the reduced implementation efficiency of various control programs. The utility of genetically engineered gene drive mosquitoes as tools to decrease the burden of malaria by controlling the disease-transmitting mosquitoes is being evaluated. To date, there has been remarkable progress in the development of CRISPR/Cas9-based homing endonuclease designs in malaria mosquitoes due to successful proof-of-principle and multigenerational experiments. In this review, we examine the lessons learnt from the development of current CRISPR/Cas9-based homing endonuclease gene drives, providing a framework for the development of gene drive systems for the targeted control of wild malaria-transmitting mosquito populations that overcome challenges such as with evolving drive-resistance. We also discuss the additional substantial works required to progress the development of gene drive systems from scientific discovery to further study and subsequent field application in endemic settings.
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Journal articleDunn N, Savolainen V, Weber S, et al., 2022,
Elasmobranch diversity across a remote coral reef atoll revealed through environmental DNA metabarcoding
, Zoological Journal of the Linnean Society, Vol: 196, Pages: 593-607, ISSN: 0024-4082As elasmobranchs are becoming increasingly threatened, efficient methods for monitoring the distribution and diversity of elasmobranch populations are required. Environmental DNA (eDNA) metabarcoding is an increasingly applied technique that enables mass identification of entire communities and is an effective method for the detection of rare and elusive species. We performed an eDNA metabarcoding survey for fish communities around a coral reef atoll in the Chagos Archipelago and assessed the diversity and distribution of elasmobranch species detected within these communities. Our eDNA survey detected 353 amplicon sequence variants (ASVs) attributed to fishes, 12 of which were elasmobranchs. There were no differences in fish communities based on the presence and absence of ASVs between sample depth (surface and 40m) or sampling habitat, but communities based on read abundance were significantly different between habitats. The dominant elasmobranch species were grey reef (Carcharhinus amblyrhynchos) and silvertip (C. albimarginatus) sharks, and elasmobranch communities were significantly different between sampling depth and habitat. Overall, we find that eDNA metabarcoding can be used to reveal the diversity of elasmobranchs within broader taxonomic assays, but further research and development of targeted metabarcoding primers may be required before it can be integrated into a toolkit for monitoring these species.
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Journal articleChik HYJ, Sparks AM, Schroeder J, et al., 2022,
A meta-analysis on the heritability of vertebrate telomere length
, JOURNAL OF EVOLUTIONARY BIOLOGY, Vol: 35, Pages: 1283-1295, ISSN: 1010-061X- Author Web Link
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- Citations: 7
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Journal articleMorris ZS, Vliet KA, Abzhanov A, et al., 2022,
Developmental origins of the crocodylian skull table and platyrostral face
, ANATOMICAL RECORD-ADVANCES IN INTEGRATIVE ANATOMY AND EVOLUTIONARY BIOLOGY, Vol: 305, Pages: 2838-2853, ISSN: 1932-8486- Author Web Link
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- Citations: 8
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Journal articleVroom RJE, van den Berg M, Pangala SR, et al., 2022,
Physiological processes affecting methane transport by wetland vegetation – A review
, Aquatic Botany, Vol: 182, Pages: 103547-103547, ISSN: 0304-3770 -
Journal articleMombrikotb SB, Van Agtmaal M, Johnstone E, et al., 2022,
The interactions and hierarchical effects of long-term agricultural stressors on soil bacterial communities
, ENVIRONMENTAL MICROBIOLOGY REPORTS, Vol: 14, Pages: 711-718, ISSN: 1758-2229- Author Web Link
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- Citations: 1
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Journal articlePearse WD, Stemkovski M, Lee BR, et al., 2022,
Consistent, linear phenological shifts across a century of observations in South Korea
<jats:title>Abstract</jats:title><jats:p>The Korea Meteorological Agency (KMA) has monitored flowering dates over the past 100 years for seven economically important woody plant species. This unique dataset is perfect for understanding whether historical patterns of phenological plasticity are breaking down in the face of recent and rapid climate change. Here we show that a scientist armed only 50 years into this study would have been able to predict the phenological shifts of the last 50 years with a high degree of accuracy. This is despite record-breaking warm temperatures and unprecedented early flowering, suggesting consistency in phenological shifts over time.</jats:p>
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Journal articleEmerson BC, Borges PAV, Cardoso P, et al., 2022,
Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands
, MOLECULAR ECOLOGY, ISSN: 0962-1083- Author Web Link
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- Citations: 4
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Journal articleNobrega R, Prentice IC, 2022,
Holistic analysis of the carbon and water cycles to quantify the human footprint in basin-wide hydrological processes in the Amazon
<jats:p>&lt;p&gt;While land-cover clearing (LCC) immediately reduces evapotranspiration (ET), its effects on other water fluxes, such as river discharge and terrestrial water storage, exhibit contrasting responses depending on location and scale. One explanation for this is that LCC triggers a series of asynchronous disruptions in the equilibrium of hydrological processes that was established upon the long-term balance with regional climatological, edaphic, and geological characteristics. Water fluxes under these circumstances are not well represented by hydrological models that have Budyko-like approaches or rely on the stationarity of the hydrological responses. The complexity of such analysis is incremented once LCC is followed by the conversion to pastures and crops established over random spatial and temporal patterns throughout river basins. Here, we propose an analysis of river discharge and root zone storage capacity (RZSC) to unveil underlying relationships between stream dynamics and water consumption by plants. We use a time-series segmentation and residual trend analysis on streamflow and precipitation of high-order tributaries of the Tapaj&amp;#243;s River in the Amazon whose catchments underwent an intense land-use change over the past decades. We estimate the RZSC using the mass-curve balance method by considering the annual land-cover changes over a &gt;30-year period. Despite the common belief that increases in river discharge are primarily caused by reduced ET when precipitation trends are not significant, we show that this might not be the main trigger of streamflow change in these major Amazon catchments. Instead, the reduction in the RZSC caused by changes in the water consumption by plants over the dry season is tightly associated with the increased baseflow contribution to rivers. Finally, we analysed gross primary productivity (GPP) and ET estimates generated by a model based on eco-evolutionary optimalit
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Journal articleMataranyika PN, Chimwamurombe PM, Venturi V, et al., 2022,
Bacterial bioinoculants adapted for sustainable plant health and soil fertility enhancement in Namibia
, Frontiers in Sustainable Food Systems, Vol: 6, ISSN: 2571-581XThe increase in dryland agriculture elicits the need to develop sustainable practices that improve crop yield and protect soil fertility. The use of biofertilisers adapted to nutrient deficient soils and arid climates would help achieve this. In this review, the use of plant growth-promoting bacteria is explored as a possible solution to the current state of dryland agriculture and climate change threats to agriculture. Plant microbe interactions form the basis of this review as evidence has shown that these interactions often exist to improve the health of plants. This is achieved by the production of important biochemicals and enzymes like indole acetic acid and amino cyclopropane-1-carboxylate deaminase while also actively protecting plants from pathogens including fungal pathogens. Research, therefore, has shown that these plant-growth promoting bacteria may be exploited and developed into biofertilisers. These biofertilisers are both economically and environmentally sustainable while improving soil quality and crop yield. The literature presented in this review is in context of the Namibian climate and soil profiles.
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Journal articleChen JM, Wang R, Liu Y, et al., 2022,
Global datasets of leaf photosynthetic capacity for ecological and earth system research
, Earth System Science Data, Vol: 14, Pages: 4077-4093, ISSN: 1866-3508The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a keyparameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecologicalresearch. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants’ optimaldistribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2)observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilationtechnique. These two independent global Vcmax products agree well (r2=0.79, RMSE=15.46 μmol m-2s-1 25 , P<0.001) andcompare well with 3672 ground-based measurements (r2=0.68, RMSE=13.55 μmol m-2s-1and P<0.001 for SIF; r2=0.55,RMSE=17.55 μmol m-2s-1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval ofVcmax from TROPOMI SIF data to produce an optimized Vcmax product using both SIF and LCC information. The globaldistributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH andleaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play amajor role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC and SIF+LCC areavailable at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2020) and the code for implementing the ecologicaloptimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R (Smith, 2020).
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Journal articleCheng S, Prentice IC, Huang Y, et al., 2022,
Data-driven surrogate model with latent data-assimilation: application to wildfire forecasting
, Journal of Computational Physics, Vol: 464, ISSN: 0021-9991The large and catastrophic wildfires have been increasing across the globe in the recent decade, highlighting the importance of simulating and forecasting fire dynamics in near real-time. This is extremely challenging due to the complexities of physical models and geographical features. Running physics-based simulations for large wildfire events in near real-time are computationally expensive, if not infeasible. In this work, we develop and test a novel data-model integration scheme for fire progression forecasting, that combines Reduced-order modelling, recurrent neural networks (Long-Short-Term Memory), data assimilation, and error covariance tuning. The Reduced-order modelling and the machine learning surrogate model ensure the efficiency of the proposed approach while the data assimilation enables the system to adjust the simulation with observations. We applied this algorithm to simulate and forecast three recent large wildfire events in California from 2017 to 2020. The deep-learning-based surrogate model runs around 1000 times faster than the Cellular Automata simulation which is used to generate training data-sets. The daily fire perimeters derived from satellite observation are used as observation data in Latent Assimilation to adjust the fire forecasting in near real-time. An error covariance tuning algorithm is also performed in the reduced space to estimate prior simulation and observation errors. The evolution of the averaged relative root mean square error (R-RMSE) shows that data assimilation and covariance tuning reduce the RMSE by about 50% and considerably improves the forecasting accuracy. As a first attempt at a reduced order wildfire spread forecasting, our exploratory work showed the potential of data-driven machine learning models to speed up fire forecasting for various applications.
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Journal articleTriantis KA, Rigal F, Whittaker RJ, et al., 2022,
Deterministic assembly and anthropogenic extinctions drive convergence of island bird communities
, GLOBAL ECOLOGY AND BIOGEOGRAPHY, Vol: 31, Pages: 1741-1755, ISSN: 1466-822X- Author Web Link
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- Citations: 4
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Journal articleArias MB, Hartle-Mougiou K, Taboada S, et al., 2022,
Unveiling biogeographical patterns in the worldwide distributed <i>Ceratitis capitata</i> (medfly) using population genomics and microbiome composition
, MOLECULAR ECOLOGY, Vol: 31, Pages: 4866-4883, ISSN: 0962-1083 -
Journal articleLiang G, Sun P, Waring BG, 2022,
Nitrogen agronomic efficiency under nitrogen fertilization does not change over time in the long term: Evidence from 477 global studies
, SOIL & TILLAGE RESEARCH, Vol: 223, ISSN: 0167-1987- Author Web Link
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- Citations: 5
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Journal articleDong N, Wright IJ, Chen JM, et al., 2022,
Rising CO2 and warming reduce global canopy deman for nitrogen
, New Phytologist, Vol: 235, Pages: 1692-1700, ISSN: 0028-646XNitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO2 and climate change. By extension, it has been suggested that declining carboxylation capacity (Vcmax) and leaf N content in enhanced-CO2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis, and estimated changes in leaf-level photosynthetic N for 1982–2016 assuming proportionality with leaf-level Vcmax at 25˚C. Whole-canopy photosynthetic N was derived using satellite-based leaf area index (LAI) data and an empirical extinction coefficient for Vcmax, and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of Vcmax shares key features with an independent reconstruction from remotely-sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27 % yr-1, while observed leaf (total) N declined by 0.2–0.25 % yr-1. Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf-level responses to rising CO2, and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.
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Journal articlePalmer J, Samuelson AE, Gill RJ, et al., 2022,
Honeybees vary communication and collective decision making across landscapes
<jats:title>Abstract</jats:title><jats:p>Honeybee (<jats:italic>Apis mellifera</jats:italic>) colony foraging decisions arise from the waggle dances of individual foragers, processed and filtered through a series of feedback loops that produce emergent collective behaviour. This process is an example of animal communication at the height of eusociality, yet a growing body of evidence suggests that its value for colony foraging success is heavily dependent on local ecology. Although colonies are thought to vary their use of the waggle dance in response to local ecological conditions, this is yet to be empirically established. Here, we quantify waggle dance use based on colony level dance-decoding and show that the impact of dance use on collective foraging is clear in some colonies but nearly negligible in others. We outline how these estimates of dance use can be combined with land-use data to explore the landscape characteristics that drive collective foraging. Our methodology provides a means to quantify the real-world importance of a celebrated example of animal communication and opens the door to the exploration of the selection pressures that may have driven the evolution of this remarkable collective behaviour.</jats:p>
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Journal articleLiu M, Prentice IC, Menviel L, et al., 2022,
Past rapid warmings as a constraint on greenhouse-gas climate feedbacks
, Communications Earth & Environment, Vol: 3, ISSN: 2662-4435There are large uncertainties in the estimation of greenhouse-gas climate feedback. Recent observations do not provide strong constraints because they are short and complicated by human interventions, while model-based estimates differ considerably. Rapid climate changes during the last glacial period (Dansgaard-Oeschger events), observed near-globally, were comparable in both rate and magnitude to current and projected 21st century climate warming and therefore provide a relevant constraint on feedback strength. Here we use these events to quantify the centennial-scale feedback strength of CO2, CH4 and N2O by relating global mean temperature changes, simulated by an appropriately forced low-resolution climate model, to the radiative forcing of these greenhouse gases derived from their concentration changes in ice-core records. We derive feedback estimates (expressed as dimensionless gain) of 0.14 ± 0.04 for CO2, 0.10 ± 0.02 for CH4, and 0.09 ± 0.03 for N2O. This indicates that much lower or higher estimates of gains, particularly some previously published values for CO2, are unrealistic.
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Journal articleKhatri BS, Burt A, 2022,
A theory of resistance to multiplexed gene drive demonstrates the significant role of weakly deleterious natural genetic variation
, Proceedings of the National Academy of Sciences of USA, Vol: 119, ISSN: 0027-8424Evolution of resistance is a major barrier to successful deployment of gene-drive systems to suppress natural populations, which could greatly reduce the burden of many vector-borne diseases. Multiplexed guide RNAs (gRNAs) that require resistance mutations in all target cut sites are a promising antiresistance strategy since, in principle, resistance would only arise in unrealistically large populations. Using stochastic simulations that accurately model evolution at very large population sizes, we explore the probability of resistance due to three important mechanisms: 1) nonhomologous end-joining mutations, 2) single-nucleotide mutants arising de novo, or 3) single-nucleotide polymorphisms preexisting as standing variation. Our results explore the relative importance of these mechanisms and highlight a complexity of the mutation–selection–drift balance between haplotypes with complete resistance and those with an incomplete number of resistant alleles. We find that this leads to a phenomenon where weakly deleterious naturally occurring variants greatly amplify the probability of multisite resistance compared to de novo mutation. This key result provides design criterion for antiresistance multiplexed systems, which, in general, will need a larger number of gRNAs compared to de novo expectations. This theory may have wider application to the evolution of resistance or evolutionary rescue when multiple changes are required before selection can act.
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Journal articleDobson B, Barry S, Maes-Prior R, et al., 2022,
Predicting catchment suitability for biodiversity at national scales
, WATER RESEARCH, Vol: 221, ISSN: 0043-1354- Author Web Link
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- Citations: 3
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Journal articleSmith T, Stemkovski M, Koontz A, et al., 2022,
AREAdata: a worldwide climate dataset averaged across spatial units at different scales through time
, Data in Brief, Vol: 43, ISSN: 2352-3409In an era of increasingly cross-discipline collaborative science, it is imperative to produce data resources which can be quickly and easily utilised by non-specialists. In particular, climate data often require heavy processing before they can be used for analyses. Here we describe AREAdata, a continually updated, free-to-use online global climate dataset, pre-processed to provide the averages of various climate variables across different administrative units (e.g., countries, states). These are daily estimates, based on the Copernicus Climate Data Store’s ERA-5 data, regularly updated to the near-present and provided as direct downloads from our website (https://pearselab.github.io/areadata/). The daily climate estimates from AREAdata are consistent with other openly available data, but at much finer-grained spatial and temporal scales than available elsewhere. AREAdata complements the existing suite of climate resources by providing these data in a form more readily usable by researchers unfamiliar with GIS data-processing methods, and we anticipate these resources being of particular use to environmental and epidemiological researchers.
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Journal articleKowal J, Arrigoni E, Jarvis S, et al., 2022,
Atmospheric pollution, soil nutrients and climate effects on Mucoromycota arbuscular mycorrhizal fungi
, Environmental Microbiology, Vol: 24, Pages: 3390-3404, ISSN: 1462-2912Fine root endophyte mycorrhizal fungi in the Endogonales (Mucoromycota arbuscular mycorrhizal fungi, M-AMF) are now recognized as at least as important globally as Glomeromycota AMF (G-AMF), yet little is known about the environmental factors which influence M-AMF diversity and colonization, partly because they typically only co-colonize plants with G-AMF. Wild populations of Lycopodiella inundata predominantly form mycorrhizas with M-AMF and therefore allow focussed study of M-AMF environmental drivers. Using microscopic examination and DNA sequencing we measured M-AMF colonization and diversity over three consecutive seasons and modelled interactions between these response variables and environmental data. Significant relationships were found between M-AMF colonization and soil S, P, C:N ratio, electrical conductivity, and the previously overlooked micronutrient Mn. Estimated N deposition was negatively related to M-AMF colonization. Thirty-nine Endogonales Operational Taxonomic Units (OTUs) were identified in L. inundata roots, a greater diversity than previously recognized in this plant. Endogonales OTU richness correlated negatively with soil C:N while community composition was mostly influenced by soil P. This study provides first evidence that M-AMF have distinct ecological preferences in response to edaphic variables also related to air pollution. Future studies require site-level atmospheric pollution monitoring to guide critical load policy for mycorrhizal fungi in heathlands and grasslands.
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Journal articleAndujar C, Arribas P, Lopez H, et al., 2022,
Community assembly and metaphylogeography of soil biodiversity: insights from haplotype-level community DNA metabarcoding within an oceanic island
, Molecular Ecology, Vol: 31, Pages: 4078-4094, ISSN: 0962-1083Most of our understanding of island diversity comes from the study of aboveground systems, while the patterns and processes of diversification and community assembly for belowground biotas remain poorly understood. Here, we take advantage of a relatively young and dynamic oceanic island to advance our understanding of ecoevolutionary processes driving community assembly within soil mesofauna. Using whole organism community DNA (wocDNA) metabarcoding and the recently developed metaMATE pipeline, we have generated spatially explicit and reliable haplotype-level DNA sequence data for soil mesofaunal assemblages sampled across the four main habitats within the island of Tenerife. Community ecological and metaphylogeographic analyses have been performed at multiple levels of genetic similarity, from haplotypes to species and supraspecific groupings. Broadly consistent patterns of local-scale species richness across different insular habitats have been found, whereas local insular richness is lower than in continental settings. Our results reveal an important role for niche conservatism as a driver of insular community assembly of soil mesofauna, with only limited evidence for habitat shifts promoting diversification. Furthermore, support is found for a fundamental role of habitat in the assembly of soil mesofauna, where habitat specialism is mainly due to colonization and the establishment of preadapted species. Hierarchical patterns of distance decay at the community level and metaphylogeographical analyses support a pattern of geographic structuring over limited spatial scales, from the level of haplotypes through to species and lineages, as expected for taxa with strong dispersal limitations. Our results demonstrate the potential for wocDNA metabarcoding to advance our understanding of biodiversity.
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Journal articleSteyaert M, Mogg A, Dunn N, et al., 2022,
Observations of coral and cryptobenthic sponge fluorescence and recruitment on autonomous reef monitoring structures (ARMS)
, CORAL REEFS, Vol: 41, Pages: 877-883, ISSN: 0722-4028- Author Web Link
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- Citations: 1
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Journal articleTerlau J, Brose U, Antunes AC, et al., 2022,
Integrating trait-based movement into mechanistic predictions of thermal performance
<jats:title>Abstract</jats:title> <jats:p>Despite the diversity and functional importance of invertebrates, predicting their response to global warming remains challenging as it requires extensive measurements of physiological performance or rarely available high-resolution distribution data. Mechanistic models can help overcome these limitations by generalizing fundamental physiological processes. However, their predictions typically omit the effects of species interactions. Movement is a key process of species interactions underpinning animal performance in the real world. Here, we developed an empirically-grounded mechanistic model that incorporates allometric and thermodynamic constraints on movement and predator-prey interactions. We illustrate how it can be used to quantify the thermal performance of invertebrates under current and future climatic conditions. This trait-based approach (1) contributes to our understanding of the mechanisms underlying thermal fitness, (2) allows generalized predictions of thermal performance across invertebrate species worldwide and (3) can be used to inform species distribution models and thereby help infer species range limits under climate change.</jats:p>
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Journal articleRosindell J, Manson K, Gumbs R, et al., 2022,
Phylogenetic Biodiversity Metrics Should Account for Both Accumulation and Attrition of Evolutionary Heritage
<jats:title>A<jats:sc>bstract</jats:sc></jats:title><jats:p>Phylogenetic metrics are essential tools used in the study of ecology, evolution and conservation. Phylogenetic diversity (PD) in particular is one of the most prominent measures of biodiversity, and is based on the idea that biological features accumulate along the edges of phylogenetic trees that are summed. We argue that PD and many other phylogenetic biodiversity metrics fail to capture an essential process that we term attrition. Attrition is the gradual loss of features through causes other than extinction. Here we introduce ‘EvoHeritage’, a generalisation of PD that is founded on the joint processes of accumulation and attrition of features. We argue that whilst PD measures evolutionary history, EvoHeritage is required to capture a more pertinent subset of evolutionary history including only components that have survived attrition. We show that EvoHeritage is not the same as PD on a tree with scaled edges; instead, accumulation and attrition interact in a more complex non-monophyletic way that cannot be captured by edge lengths alone. This leads us to speculate that the one dimensional edge lengths of classic trees may be insufficiently flexible to capture the nuances of evolutionary processes. We derive a measure of EvoHeritage and show that it elegantly reproduces species richness and PD at opposite ends of a continuum based on the intensity of attrition. We demonstrate the utility of EvoHeritage in ecology as a predictor of community productivity compared with species richness and PD. We also show how EvoHeritage can quantify living fossils and resolve their associated controversy. We suggest how the existing calculus of PD-based metrics and other phylogenetic biodiversity metrics can and should be recast in terms of EvoHeritage accumulation and attrition.</jats:p><jats:sec><jats:title>Candidate cover image</jats:title><jats:fig
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Journal articleWaring B, Gee A, Liang G, et al., 2022,
A quantitative analysis of microbial community structure-function relationships in plant litter decay
, iScience, Vol: 25, Pages: 1-13, ISSN: 2589-0042Soil microbes play a central role in ecosystem element cycling. Yet a central question in microbial ecology remains unanswered: to what extent does the taxonomic composition of soil microbial communities mediate biogeochemical process rates? In this quantitative review, we explore the mechanisms that lead to variation in the strength of microbial community structure-function relationships over space and time. To evaluate these mechanisms, we conduct a meta-analysis of studies that have monitored the decomposition of sterilized plant litter inoculated with different microbial assemblages. We find that the influence of microbial community composition on litter decay is pervasive and strong, rivalling in magnitude the influence of litter chemistry on decomposition. However, no single environmental or experimental attribute was correlated with variation in the inoculum effect. These results emphasize the need to better understand ecological dynamics within microbial communities, particularly emergent features such as cross-feeding networks, to improve predictions of soil biogeochemical function.
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