scispace - formally typeset
Search or ask a question
Author

Callum D. Martin

Other affiliations: Imperial College London
Bio: Callum D. Martin is an academic researcher from Royal Holloway, University of London. The author has contributed to research in topics: Bumblebee & Bombus terrestris. The author has an hindex of 6, co-authored 12 publications receiving 2093 citations. Previous affiliations of Callum D. Martin include Imperial College London.

Papers
More filters
Journal ArticleDOI
02 Apr 2015-Nature
TL;DR: A terrestrial assemblage database of unprecedented geographic and taxonomic coverage is analysed to quantify local biodiversity responses to land use and related changes and shows that in the worst-affected habitats, pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%.
Abstract: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

2,532 citations

Journal ArticleDOI
Lawrence N. Hudson1, Tim Newbold2, Tim Newbold3, Sara Contu1  +270 moreInstitutions (167)
TL;DR: A new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world is described and assessed.
Abstract: Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species Existing global databases of species’ threat status or population time series are dominated by charismatic species The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines We describe and assess a new database of more than 16 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – wwwpredictsorguk) We make site-level summary data available alongside this article The full database will be publicly available in 2015

196 citations

Journal ArticleDOI
Lawrence N. Hudson1, Tim Newbold2, Tim Newbold3, Sara Contu1  +570 moreInstitutions (291)
TL;DR: The PREDICTS project as discussed by the authors provides a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use.
Abstract: The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

162 citations

Journal ArticleDOI
04 Aug 2021-Nature
TL;DR: This paper conducted a meta-analysis of 356 interaction effect sizes from 90 studies in which bees were exposed to combinations of agrochemicals, nutritional stressors and/or parasites, and found an overall synergistic effect between multiple stressors on bee mortality.
Abstract: Global concern over widely documented declines in pollinators1–3 has led to the identification of anthropogenic stressors that, individually, are detrimental to bee populations4–7. Synergistic interactions between these stressors could substantially amplify the environmental effect of these stressors and could therefore have important implications for policy decisions that aim to improve the health of pollinators3,8,9. Here, to quantitatively assess the scale of this threat, we conducted a meta-analysis of 356 interaction effect sizes from 90 studies in which bees were exposed to combinations of agrochemicals, nutritional stressors and/or parasites. We found an overall synergistic effect between multiple stressors on bee mortality. Subgroup analysis of bee mortality revealed strong evidence for synergy when bees were exposed to multiple agrochemicals at field-realistic levels, but interactions were not greater than additive expectations when bees were exposed to parasites and/or nutritional stressors. All interactive effects on proxies of fitness, behaviour, parasite load and immune responses were either additive or antagonistic; therefore, the potential mechanisms that drive the observed synergistic interactions for bee mortality remain unclear. Environmental risk assessment schemes that assume additive effects of the risk of agrochemical exposure may underestimate the interactive effect of anthropogenic stressors on bee mortality and will fail to protect the pollinators that provide a key ecosystem service that underpins sustainable agriculture. A meta-analysis of studies in which bees were exposed to combinations of agrochemicals, nutritional stressors and/or parasites revealed evidence for synergistic effects on mortality when bees were exposed to multiple agrochemicals at field-realistic levels.

107 citations

Journal ArticleDOI
TL;DR: Commercial bumblebees can be very effective when used in the right circumstance and increase high grade fruit by 25% in an early-flowering variety and in two other varieties commercial bees had no effect on fruit quality.

20 citations


Cited by
More filters
Journal ArticleDOI
02 Apr 2015-Nature
TL;DR: A terrestrial assemblage database of unprecedented geographic and taxonomic coverage is analysed to quantify local biodiversity responses to land use and related changes and shows that in the worst-affected habitats, pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%.
Abstract: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

2,532 citations

Journal ArticleDOI
TL;DR: The overall biomass composition of the biosphere is assembled, establishing a census of the ≈550 gigatons of carbon (Gt C) of biomass distributed among all of the kingdoms of life and shows that terrestrial biomass is about two orders of magnitude higher than marine biomass and estimate a total of ≈6 Gt C of marine biota, doubling the previous estimated quantity.
Abstract: A census of the biomass on Earth is key for understanding the structure and dynamics of the biosphere. However, a global, quantitative view of how the biomass of different taxa compare with one another is still lacking. Here, we assemble the overall biomass composition of the biosphere, establishing a census of the ≈550 gigatons of carbon (Gt C) of biomass distributed among all of the kingdoms of life. We find that the kingdoms of life concentrate at different locations on the planet; plants (≈450 Gt C, the dominant kingdom) are primarily terrestrial, whereas animals (≈2 Gt C) are mainly marine, and bacteria (≈70 Gt C) and archaea (≈7 Gt C) are predominantly located in deep subsurface environments. We show that terrestrial biomass is about two orders of magnitude higher than marine biomass and estimate a total of ≈6 Gt C of marine biota, doubling the previous estimated quantity. Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus increasing the scope of previous observations on inverse food pyramids. Finally, we highlight that the mass of humans is an order of magnitude higher than that of all wild mammals combined and report the historical impact of humanity on the global biomass of prominent taxa, including mammals, fish, and plants.

1,714 citations

Journal ArticleDOI
10 Oct 2018-Nature
TL;DR: A global model finds that the environmental impacts of the food system could increase by 60–90% by 2050, and that dietary changes, improvements in technologies and management, and reductions in food loss and waste will all be needed to mitigate these impacts.
Abstract: The food system is a major driver of climate change, changes in land use, depletion of freshwater resources, and pollution of aquatic and terrestrial ecosystems through excessive nitrogen and phosphorus inputs. Here we show that between 2010 and 2050, as a result of expected changes in population and income levels, the environmental effects of the food system could increase by 50–90% in the absence of technological changes and dedicated mitigation measures, reaching levels that are beyond the planetary boundaries that define a safe operating space for humanity. We analyse several options for reducing the environmental effects of the food system, including dietary changes towards healthier, more plant-based diets, improvements in technologies and management, and reductions in food loss and waste. We find that no single measure is enough to keep these effects within all planetary boundaries simultaneously, and that a synergistic combination of measures will be needed to sufficiently mitigate the projected increase in environmental pressures.

1,521 citations

Journal ArticleDOI
TL;DR: This work uses recently available data on infrastructure, land cover and human access into natural areas to construct a globally standardized measure of the cumulative human footprint on the terrestrial environment at 1 km2 resolution from 1993 to 2009.
Abstract: Human pressures on the environment are changing spatially and temporally, with profound implications for the planet’s biodiversity and human economies. Here we use recently available data on infrastructure, land cover and human access into natural areas to construct a globally standardized measure of the cumulative human footprint on the terrestrial environment at 1 km2 resolution from 1993 to 2009. We note that while the human population has increased by 23% and the world economy has grown 153%, the human footprint has increased by just 9%. Still, 75% the planet’s land surface is experiencing measurable human pressures. Moreover, pressures are perversely intense, widespread and rapidly intensifying in places with high biodiversity. Encouragingly, we discover decreases in environmental pressures in the wealthiest countries and those with strong control of corruption. Clearly the human footprint on Earth is changing, yet there are still opportunities for conservation gains. Habitat loss and urbanization are primary components of human impact on the environment. Here, Venter et al.use global data on infrastructure, agriculture, and urbanization to show that the human footprint is growing slower than the human population, but footprints are increasing in biodiverse regions.

1,027 citations

Journal ArticleDOI
TL;DR: It is recommended that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations.
Abstract: Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also provides ample opportunity for overfitting with non-causal predictors. This problem can persist even if remedies such as autoregressive models, generalized least squares, or mixed models are used. Block cross-validation, where data are split strategically rather than randomly, can address these issues. However, the blocking strategy must be carefully considered. Blocking in space, time, random effects or phylogenetic distance, while accounting for dependencies in the data, may also unwittingly induce extrapolations by restricting the ranges or combinations of predictor variables available for model training, thus overestimating interpolation errors. On the other hand, deliberate blocking in predictor space may also improve error estimates when extrapolation is the modelling goal. Here, we review the ecological literature on non-random and blocked cross-validation approaches. We also provide a series of simulations and case studies, in which we show that, for all instances tested, block cross-validation is nearly universally more appropriate than random cross-validation if the goal is predicting to new data or predictor space, or for selecting causal predictors. We recommend that block cross-validation be used wherever dependence structures exist in a dataset, even if no correlation structure is visible in the fitted model residuals, or if the fitted models account for such correlations.

998 citations