Cell size correlates with most traits among phytoplankton species. Theory predicts that larger cells should show poorer photosynthetic performance, perhaps due to reduced intracellular self-shading (i.e. package effect). Yet current theory relies heavily on interspecific correlational approaches and causal relationships between size and photosynthetic machinery have remained untested. As a more direct test, we applied 250 generations of artificial selection (c. 20 months) to evolve the green microalga Dunaliella teriolecta (Chlorophyta) toward different mean cell sizes, while monitoring all major photosynthetic parameters. Evolving larger sizes (> 1500% difference in volume) resulted in reduced oxygen production per chlorophyll molecule - as predicted by the package effect. However, large-evolved cells showed substantially higher rates of oxygen production - a finding unanticipated by current theory. In addition, volume-specific photosynthetic pigments increased with size (Chla+b), while photo-protectant pigments decreased (β-carotene). Finally, larger cells displayed higher growth performances and F /F , steeper slopes of rapid light curves (α) and smaller light-harvesting antennae (σ ) with higher connectivity (ρ). Overall, evolving a common ancestor into different sizes showed that the photosynthetic characteristics of a species coevolves with cell volume. Moreover, our experiment revealed a trade-off between chlorophyll-specific (decreasing with size) and volume-specific (increasing with size) oxygen production in a cell.

Many studies examine how body size mediates energy use, but few investigate how size simultaneously regulates energy acquisition. Furthermore, rarely energy fluxes are examined while accounting for the role of biotic and abiotic factors in which they are nested. These limitations contribute to an incomplete understanding of how size affects the transfer of energy through individuals, populations, and communities. Here we characterized photosynthesis-irradiance (P-I) curves and per-cell net-energy use for 21 phytoplankton species spanning across four orders of magnitude of size and seven phyla, each measured across six light intensities and four population densities. We then used phylogenetic mixed models to quantify how body size influences the energy turnover rates of a species, and how this changes across environments. Rate-parameters for the P-I curve and net-energy budgets were mostly highly correlated and consistent with an allometric size-scaling exponent of <1. The energy flux of a cell decreased with population density and increased with light intensity, but the effect of body size remained constant across all combinations of treatment levels (i.e. no size×populationdensity interaction). The negative effect of population density on photosynthesis and respiration is mostly consistent with an active downregulation of metabolic rates following a decrease in per-cell resource availability, possibly as an adaptive strategy to reduce the minimum requirements of a cell and improve its competitive ability. Also, because an increase in body size corresponds to a less-than-proportional increase in net-energy (i.e. exponent<1), we propose that volume-specific net-energy flux can represent an important cost of evolving larger body sizes in autotrophic single-cell organisms.

Size imposes physiological and ecological constraints upon all organisms. Theory abounds on how energy flux covaries with body size, yet causal links are often elusive. As a more direct way to assess the role of size, we used artificial selection to evolve the phytoplankton species Dunaliella tertiolecta towards smaller and larger body sizes. Within 100 generations (c. 1 year), we generated a fourfold difference in cell volume among selected lineages. Large-selected populations produced four times the energy than small-selected populations of equivalent total biovolume, but at the cost of much higher volume-specific respiration. These differences in energy utilisation between large (more productive) and small (more energy-efficient) individuals were used to successfully predict ecological performance (r and K) across novel resource regimes. We show that body size determines the performance of a species by mediating its net energy flux, with worrying implications for current trends in size reduction and for global carbon cycles.

Farm dams are a ubiquitous limnological feature of agricultural landscapes worldwide. While their primary function is to capture and store water, they also have disproportionally large effects on biodiversity and biogeochemical cycling, with important relevance to several Sustainable Development Goals (SDGs). However, the abundance and distribution of farm dams is unknown in most parts of the world. Therefore, we used artificial intelligence and remote sensing data to address this critical global information gap. Specifically, we trained a deep learning convolutional neural network (CNN) on high-definition satellite images to detect farm dams and carry out the first continental-scale assessment on density, distribution and historical trends. We found that in Australia there are 1.765 million farm dams that occupy an area larger than Rhode Island (4678 km2) and store over 20 times more water than Sydney Harbour (10,990 GL). The State of New South Wales recorded the highest number of farm dams (654,983; 37% of the total) and Victoria the highest overall density (1.73 dams km−2). We also estimated that 202,119 farm dams (11.5%) remain omitted from any maps, especially in South Australia, Western Australia and the Northern Territory. Three decades of historical records revealed an ongoing decrease in the construction rate of farm dams, from >3% per annum before 2000, to ~1% after 2000, to <0.05% after 2010—except in the Australian Capital Territory where rates have remained relatively high. We also found systematic trends in construction design: farm dams built in 2015 are on average 50% larger in surface area and contain 66% more water than those built in 1989. To facilitate sharing information on sustainable farm dam management with authorities, scientists, managers and local communities, we developed AusDams.org—a free interactive portal to visualise and generate statistics on the physical, environmental and ecological impacts of farm dams.

Across a wide range of taxa, larger mothers produce larger offspring. Theory assumes that larger, more fecund mothers create higher local densities of siblings, and so larger mothers produce larger offspring to offset sibling competition. This assumption has been debated for over 30 yr, but direct empirical tests are surprisingly rare. Here, we test two key assumptions of classic theories that predict sibling competition drives maternal-size-offspring-size (MSOS) correlations: (1) independent effects of offspring size and sibling density on offspring performance or (2) as a product of an interaction between these two factors. To simultaneously test these alternative assumptions, we manipulate offspring size and sibling density in the marine invertebrate, Bugula neritina, and monitor offspring performance in the field. We found that, depending on the fitness metric being considered, offspring size and sibling density can either independently or interactively affect offspring performance. Yet sibling density did not affect offspring performance in the ways that classic theories assume. Given our results, it is unlikely that sibling competition drives the positive MSOS correlation observed in this species. Empirical support for these classic theories remains lacking, suggesting alternative explanations are necessary.