Changes in Biomass and Diversity of Soil Macrofauna along a Climatic Gradient in European Boreal Forests

Latitudinal gradients allow insights into the factors that shape ecosystem structure and delimit ecosystem processes, particularly climate. We asked whether the biomass and diversity of soil macrofauna in boreal forests change systematically along a latitudinal gradient spanning from 60° N to 69° N. Invertebrates (3697 individuals) were extracted from 400 soil samples (20 × 20 cm, 30 cm depth) collected at ten sites in 2015–2016 and then weighed and identified. We discovered 265 species living in soil and on the soil surface; their average density was 0.486 g d·w·m−2. The species-level diversity decreased from low to high latitudes. The biomass of soil macrofauna showed no latitudinal changes in early summer but decreased towards the north in late summer. This variation among study sites was associated with the decrease in mean annual temperature by ca 5 °C and with variation in fine root biomass. The biomass of herbivores and fungivores decreased towards the north, whereas the biomass of detritivores and predators showed no significant latitudinal changes. This variation in latitudinal biomass patterns among the soil macrofauna feeding guilds suggests that these guilds may respond differently to climate change, with poorly understood consequences for ecosystem structure and functions.

A Structural Equation Modeling Approach to Disentangling Regional-Scale Landscape Dynamics in Ghana

Land cover (LC) change is an integrative indicator of changes in ecosystems due to anthropogenic or natural forcings. There is a significant interest in the investigation of spatio-temporal patterns of LC transitions, and the causes and consequences thereof. While the advent of satellite remote sensing techniques have enhanced our ability to track and measure LC changes across the globe, significant gaps remain in disentangling specific factors that influence, or in certain cases, are influenced by, LC change. This study aims to investigate the relative influence of regional-scale bioclimatology and local-scale anthropogenic factors in driving LC and environmental change in Ghana. This analysis builds upon previous research in the region that has highlighted multiple drivers of LC change in the region, especially via drivers such as deforestation, urbanization, and agricultural expansion. It used regional-scale remotely sensed, demographic, and environmental data for Ghana across 20 years and developed path models on causal factors influencing LC transitions in Ghana. A two-step process is utilized wherein causal linkages from an exploratory factor analysis (EFA) are constrained with literature-based theoretical constructs to implement a regional-scale partial least squares path model (PLSPM). The PLSPM reveals complex interrelationships among drivers of LC change that vary across the geography of Ghana. The model suggests strong effects of local urban expansion on deforestation and vegetation losses in urban and peri-urban areas. Losses of vegetation are in turn related to increases in local heating patterns indicative of urban heat island effects. Direct effects of heat islands are however masked by strong latitudinal gradients in climatological factors. The models confirm that decreases in vegetation cover results in increased land surface albedo that is indirectly related to urban and population expansion. These empirically-estimated causal linkages provide insights into complex spatio-temporal variations in potential drivers of LC change. We expect these models and spatial data products to form the basis for detailed investigations into the mechanistic underpinnings of land cover dynamics across Ghana. These analyses are aimed at building a template for methods that can be utilized to holistically design spatially-disaggregated strategies for sustainable development across Ghana.

Globally invariant metabolism but density-diversity mismatch in springtails

Soil life supports the functioning and biodiversity of terrestrial ecosystems1,2. Springtails (Collembola) are among the most abundant soil animals regulating soil fertility and flow of energy through above- and belowground food webs3-5. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset collected from 2,470 sites, we estimate total soil springtail biomass at 29 Mt carbon (threefold higher than wild terrestrial vertebrates6) and record peak densities up to 2 million individuals per m2 in the Arctic. Despite a 20-fold biomass difference between tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the increase in temperature. Neither springtail density nor community metabolism were predicted by local species richness, which was highest in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation7,8, and resource limitation7,9,10 in soil communities. Contrasting temperature responses of biomass, diversity and activity of springtail communities suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting major soil functions.

Beyond the Tree-Line: The C3-C4 “Grass-Line” Can Track Global Change in the World’s Grassy Mountain Systems

von Humboldt’s tree-line concept has dominated mountain ecology for almost two hundred years, and is considered a key indicator for monitoring change in biome boundaries and biodiversity shifts under climate change. Even though the concept of life zones and elevation gradients are a globally observed phenomenon, they have not been thoroughly explored for many contexts. One such example is the tree-line ecotone, a widely used conceptual tool to track climate change in many regions, which has limited application in the widespread tree-sparse, grassy systems that comprise a third of the world’s mountain systems. Among grasses (Poaceae), temperature is linked to variation in photosynthetic performance and community dominance for C3 and C4 metabolic groups, due to its role in limiting photorespiration in the C3 photosynthesis process. Here, we investigate this community shift in grassland-dominated mountains to demonstrate the role of climate in driving this transition and discuss the potential applications of this tool to mountain ecosystem conservation worldwide. For identifying grass-dominated mountains worldwide, we measured the grass-cover using satellite data. We then compiled Poaceae distribution data for ten grass-dominated mountains spanning from 42°S to 41°N and determined the temperature intervals and elevation ranges at which each genus was found, testing for effects of temperature, precipitation, and latitudinal gradients on the dominance of C3-C4 grasses. Temperature was the main driver of C3 dominance, with the richness of C3 genera tending to surpass the taxonomic dominance of C4 plants along mountain temperature gradients where the annual mean temperature was colder than ca. 14.6°C. Similar patterns were observed in eight out of ten mountains, suggesting that this may constitute an isotherm-driven ecotone. Consequently, this C3-C4 transition offers a promising tool for monitoring climate change impacts in grassy mountains. C3-C4 grass community shifts in response to environmental change will likely have major implications for fire frequency and severity, rangeland productivity and livelihoods, food security, and water budgets in mountain systems. Given the severity of the implications of global change on these social-ecological systems, we propose that a “grass-line” monitoring protocol be developed for global application.

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.

Mito-nuclear selection induces a trade-off between species ecological dominance and evolutionary lifespan

Micro-evolutionary processes acting in populations and communities ultimately produce macro-evolutionary patterns. However, current models of species life histories -- including processes of speciation, persistence, hybridization, and eventual extinction -- rarely connect these two time scales. This leaves us with a limited theoretical understanding of the subtleties of diversification, such as the relationship between species abundance in an ecological community and species longevity over evolutionary time, or the impact of selection on patterns of speciation and extinction when structuring an ecological community. Here we present a model for evolution in spatially extended populations with a focus on selection for mito-nuclear compatibility. We find that mito-nuclear selection acting at the individual level decreases genetic variability among species in a radiation, reducing the total number of species and skewing species abundances distributions towards mono-dominance. Also, intraspecific diversity increases as species become more abundant, leading to frequent evolutionary branching that reduces species lifetimes. The equilibrium of such communities is characterized by high rates of speciation, extinction, and hybridization, i.e., high turnover rate. These theoretical results are in concordance with empirical patterns of diversity across latitudinal gradients. Model predictions in the absence of mito-nuclear selection resemble the tropics, with high biodiversity, old species, and low speciation and extinction rates. Whereas model predictions under strong selection, which we expect in the harsh environments of temperate zones, produce fewer species and elevated recent speciation rates.

Environmental optima for an ecosystem engineer: a multidisciplinary trait-based approach

A complex interplay of biotic and abiotic factors underpins the distribution of species and operates across different levels of biological organization and life history stages. Understanding ecosystem engineer reproductive traits is critical for comprehending and managing the biodiversity-rich habitats they create. Little is known about how the reproduction of the reef-forming worm, Sabellaria alveolata, varies across environmental gradients. By integrating broad-scale environmental data with in-situ physiological data in the form of biochemical traits, we identified and ranked the drivers of intraspecific reproductive trait variability (ITV). ITV was highest in locations with variable environmental conditions, subjected to fluctuating temperature and hydrodynamic conditions. Our trait selection pointed to poleward sites being the most physiologically stressful, with low numbers of irregularly shaped eggs suggesting potentially reduced reproductive success. Centre-range individuals allocated the most energy to reproduction, with the highest number of intermediate-sized eggs, whilst equatorward sites were the least physiologically stressful, thus confirming the warm-adapted nature of our model organism. Variation in total egg diameter and relative fecundity were influenced by a combination of environmental conditions, which changed depending on the trait and sampling period. An integrated approach involving biochemical and reproductive traits is essential for understanding macro-scale patterns in the face of anthropogenic-induced climate change across environmental and latitudinal gradients.

Carbon response of tundra ecosystems to advancing greenup and snowmelt in Alaska

The ongoing disproportionate increases in temperature and precipitation over the Arctic region may greatly alter the latitudinal gradients in greenup and snowmelt timings as well as associated carbon dynamics of tundra ecosystems. Here we use remotely-sensed and ground-based datasets and model results embedding snowmelt timing in phenology at seven tundra flux tower sites in Alaska during 2001–2018, showing that the carbon response to early greenup or delayed snowmelt varies greatly depending upon local climatic limits. Increases in net ecosystem productivity (NEP) due to early greenup were amplified at the higher latitudes where temperature and water strongly colimit vegetation growth, while NEP decreases due to delayed snowmelt were alleviated by a relief of water stress. Given the high likelihood of more frequent delayed snowmelt at higher latitudes, this study highlights the importance of understanding the role of snowmelt timing in vegetation growth and terrestrial carbon cycles across warming Arctic ecosystems.