A framework for modelling soil structure dynamics induced by biological activity

Soil degradation is a worsening global phenomenon driven by socio‐economic pressures, poor land management practices and climate change. A deterioration of soil structure at timescales ranging from seconds to centuries is implicated in most forms of soil degradation including the depletion of nutrients and organic matter, erosion and compaction. New soil–crop models that could account for soil structure dynamics at decadal to centennial timescales would provide insights into the relative importance of the various underlying physical (e.g. tillage, traffic compaction, swell/shrink and freeze/thaw) and biological (e.g. plant root growth, soil microbial and faunal activity) mechanisms, their impacts on soil hydrological processes and plant growth, as well as the relevant timescales of soil degradation and recovery. However, the development of such a model remains a challenge due to the enormous complexity of the interactions in the soil–plant system. In this paper, we focus on the impacts of biological processes on soil structure dynamics, especially the growth of plant roots and the activity of soil fauna and microorganisms. We first define what we mean by soil structure and then review current understanding of how these biological agents impact soil structure. We then develop a new framework for modelling soil structure dynamics, which is designed to be compatible with soil–crop models that operate at the soil profile scale and for long temporal scales (i.e. decades, centuries). We illustrate the modelling concept with a case study on the role of root growth and earthworm bioturbation in restoring the structure of a severely compacted soil.     

Climate change undermines the global functioning of marine food webs

Sea water temperature affects all biological and ecological processes that ultimately impact ecosystem functioning. In this study, we examine the influence of temperature on global biomass transfers from marine secondary production to fish stocks. By combining fisheries catches in all coastal ocean areas and life‐history traits of exploited marine species, we provide global estimates of two trophic transfer parameters which determine biomass flows in coastal marine food web: the trophic transfer efficiency (TTE) and the biomass residence time (BRT) in the food web. We find that biomass transfers in tropical ecosystems are less efficient and faster than in areas with cooler waters. In contrast, biomass transfers through the food web became faster and more efficient between 1950 and 2010. Using simulated changes in sea water temperature from three Earth system models, we project that the mean TTE in coastal waters would decrease from 7.7% to 7.2% between 2010 and 2100 under the ‘no effective mitigation’ representative concentration pathway (RCP8.5), while BRT between trophic levels 2 and 4 is projected to decrease from 2.7 to 2.3 years on average. Beyond the global trends, we show that the TTEs and BRTs may vary substantially among ecosystem types and that the polar ecosystems may be the most impacted ecosystems. The detected and projected changes in mean TTE and BRT will undermine food web functioning. Our study provides quantitative understanding of temperature effects on trophodynamic of marine ecosystems under climate change.     

Nonlinearity in interspecific interactions in response to climate change: Cod and haddock as an example

Climate change has profound ecological effects, yet our understanding of how trophic interactions among species are affected by climate change is still patchy. The sympatric Atlantic haddock and cod are co‐occurring across the North Atlantic. They compete for food at younger stages and thereafter the former is preyed by the latter. Climate change might affect the interaction and coexistence of these two species. Particularly, the increase in sea temperature (ST) has been shown to affect distribution, population growth and trophic interactions in marine systems. We used 33‐year long time series of haddock and cod abundances estimates from two data sources (acoustic and trawl survey) to analyse the dynamic effect of climate on the coexistence of these two sympatric species in the Arcto‐Boreal Barents Sea. Using a Bayesian state‐space threshold model, we demonstrated that long‐term climate variation, as expressed by changes of ST, affected species demography through different influences on density‐independent processes. The interaction between cod and haddock has shifted in the last two decades due to an increase in ST, altering the equilibrium abundances and the dynamics of the system. During warm years (ST over ca. 4°C), the increase in the cod abundance negatively affected haddock abundance while it did not during cold years. This change in interactions therefore changed the equilibrium population size with a higher population size during warm years. Our analyses show that long‐term climate change in the Arcto‐Boreal system can generate differences in the equilibrium conditions of species assemblages.     

Evidence of non‐stationary relationships between climate and forest responses: Increased sensitivity to climate change in Iberian forests

Climate and forest structure are considered major drivers of forest demography and productivity. However, recent evidence suggests that the relationships between climate and tree growth are generally non‐stationary (i.e. non‐time stable), and it remains uncertain whether the relationships between climate, forest structure, demography and productivity are stationary or are being altered by recent climatic and structural changes. Here we analysed three surveys from the Spanish Forest Inventory covering c. 30 years of information and we applied mixed and structural equation models to assess temporal trends in forest structure (stand density, basal area, tree size and tree size inequality), forest demography (ingrowth, growth and mortality) and above‐ground forest productivity. We also quantified whether the interactive effects of climate and forest structure on forest demography and above‐ground forest productivity were stationary over two consecutive time periods. Since the 1980s, density, basal area and tree size increased in Iberian forests, and tree size inequality decreased. In addition, we observed reductions in ingrowth and growth, and increases in mortality. Initial forest structure and water availability mainly modulated the temporal trends in forest structure and demography. The magnitude and direction of the interactive effects of climate and forest structure on forest demography changed over the two time periods analysed indicating non‐stationary relationships between climate, forest structure and demography. Above‐ground forest productivity increased due to a positive balance between ingrowth, growth and mortality. Despite increasing productivity over time, we observed an aggravation of the negative effects of climate change and increased competition on forest demography, reducing ingrowth and growth, and increasing mortality. Interestingly, our results suggest that the negative effects of climate change on forest demography could be ameliorated through forest management, which has profound implications for forest adaptation to climate change.     

Assessing influence in biofuel production and ecosystem services when environmental changes affect plant–pest relationships

Climate change is currently affecting both biodiversity and human activities; land use change and greenhouse gas emissions are the main drivers. Many agricultural services are affected by the change, which in turn reflects on the basic provisioning services, which supply food, fibre and biofuels. Biofuels are getting increasing interest because of their sustainability potential. Jatropha curcas gained popularity as a biodiesel crop, due to its ease of cultivation even in harsh environmental conditions. Notwithstanding its high economic importance, few studies are available about its co‐occurrence with pests of the genus Aphthona in sub‐Saharan Africa, where these insects feed on J. curcas, leading to relevant economic losses. Using ecological niche modelling and GIS post‐modelling analyses, we infer the current and future suitable territories for both these taxa, delineating areas where J. curcas cultivations may occur without suffering the presence of Aphthona, in the context of future climate and land use changing. We introduce an area‐normalized index, the ‘Potential‐Actual Cultivation Index’, to better depict the ratio between the suitable areas shared both by the crop and its pest, and the number of actual cultivations, in a target country. Moreover, we find high economic losses (~?50%) both in terms of carbon sequestration and in biodiesel production when J. curcas co‐occur with the Aphthona cookei species group.     

Sustainable intensification of crop residue exploitation for bioenergy: Opportunities and challenges

Crop residue exploitation for bioenergy can play an important role in climate change mitigation without jeopardizing food security, but it may be constrained by impacts on soil organic carbon (SOC) stocks, and market, logistic and conversion challenges. We explore opportunities to increase bioenergy potentials from residues while reducing environmental impacts, in line with sustainable intensification. Using the case study of North Rhine‐Westphalia in Germany, we employ a spatiotemporally explicit approach combined with stakeholder interviews. First, the interviews identify agronomic and environmental impacts due to the potential reduction in SOC as the most critical challenge associated with enhanced crop residue exploitation. Market and technological challenges and competition with other residue uses are also identified as significant barriers. Second, with the use of agroecosystem modelling and estimations of bioenergy potentials and greenhouse gas emissions till mid‐century, we evaluate the ability of agricultural management to tackle the identified agronomic and environmental challenges. Integrated site‐specific management based on (a) humus balancing, (b) optimized fertilization and (c) winter soil cover performs better than our reference scenario with respect to all investigated variables. At the regional level, we estimate (a) a 5% increase in technical residue potentials and displaced emissions from substituting fossil fuels by bioethanol, (b) an 8% decrease in SOC losses and associated emissions, (c) an 18% decrease in nitrous oxide emissions, (d) a 37% decrease in mineral fertilizer requirements and emissions from their production and (e) a 16% decrease in nitrate leaching. Results are spatially variable and, despite improvements induced by management, limited amounts of crop residues are exploitable for bioenergy in areas prone to SOC decline. In order to sustainably intensify crop residue exploitation for bioenergy and reconcile climate change mitigation with other sustainability objectives, such as those on soil and water quality, residue management needs to be designed in an integrated and site‐specific manner.     

Reversed-phase HPLC enantioseparation of pantoprazole using a teicoplanin aglycone stationary phase—Determination of the enantiomer elution order using HPLC-CD analyses

A direct HPLC method was developed for the enantioseparation of pantoprazole using macrocyclic glycopeptide-based chiral stationary phases, along with various methods to determine the elution order without isolation of the individual enantiomers. In the preliminary screening, four macrocyclic glycopeptide-based chiral stationary phases containing vancomycin (Chirobiotic V), ristocetin A (Chirobiotic R), teicoplanin (Chirobiotic T), and teicoplanin-aglycone (Chirobiotic TAG) were screened in polar organic and reversed-phase mode. Best results were achieved by using Chirobiotic TAG column and a methanol-water mixture as mobile phase. Further method optimization was performed using a face-centered central composite design to achieve the highest chiral resolution. Optimized parameters, offering baseline separation (resolution = 1.91 ± 0.03) were as follows: Chirobiotic TAG stationary phase, thermostated at 10°C, mobile phase consisting of methanol/20mM ammonium acetate 60:40 v/v, and 0.6 mL/min flow rate. Enantiomer elution order was determined using HPLC hyphenated with circular dichroism (CD) spectroscopy detection. The online CD signals of the separated pantoprazole enantiomers at selected wavelengths were compared with the structurally analogous esomeprazole enantiomer. For further verification, the inline rapid, multiscan CD signals were compared with the quantum chemically calculated CD spectra. Furthermore, docking calculations were used to investigate the enantiorecognition at molecular level. The molecular docking shows that the R-enantiomer binds stronger to the chiral selector than its antipode, which is in accordance with the determined elution order on the column—S- followed by the R-isomer. Thus, combined methods, HPLC-CD and theoretical calculations, are highly efficient in predicting the elution order of enantiomers.     

Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data

Relatively simple foraging radius models have the potential to generate predictive distributions for a large number of species rapidly, thus providing a cost-effective alternative to large-scale surveys or complex modelling approaches. Their effectiveness, however, remains largely untested. Here we compare foraging radius distribution models for all breeding seabirds in Ireland, to distributions of empirical data collected from tracking studies and aerial surveys. At the local/colony level, we compared foraging radius distributions to GPS tracking data from seabirds with short (Atlantic puffin Fratercula arctica, and razorbill Alca torda) and long (Manx shearwater Puffinus puffinus, and European storm-petrel Hydrobates pelagicus) foraging ranges. At the regional/national level, we compared foraging radius distributions to extensive aerial surveys conducted over a two-year period. Foraging radius distributions were significantly positively correlated with tracking data for all species except Manx shearwater. Correlations between foraging radius distributions and aerial survey data were also significant, but generally weaker than those for tracking data. Correlations between foraging radius distributions and aerial survey data were benchmarked against generalised additive models (GAMs) of the aerial survey data that included a range of environmental covariates. While GAM distributions had slightly higher correlations with aerial survey data, the results highlight that the foraging radius approach can be a useful and pragmatic approach for assessing breeding distributions for many seabird species. The approach is likely to have acceptable utility in complex, temporally variable ecosystems and when logistic and financial resources are limited.     

Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.