Search

Despite the potential of diversification strategies to achieve sustainability, diversified systems such as agroforestry are still not widely implemented by farmers, which indicates the need to further understand and adequately assess the impacts of diversification to inform the design of complex systems. In this paper, we conduct a systematic literature review focused on agroforestry coffee systems, to assess (i) how current methods and indicators are used to quantify the impact of diversification on multiple dimensions of system sustainability, and (ii) to assess the impact of diversification through coffee agroforestry on multiple dimensions of sustainability. Our analysis was based on 215 selected papers and all the indicators identified could be classified in one of the sustainability dimensions proposed in our framework: ecosystem services (57.2%), biodiversity (35.6%), input use (4%), socio-economic sustainability (2.7%) and resilience capacity (0.5%). Despite the broad scope of the indicators, individual studies were found to often lack interdisciplinarity and a systemic view on agroecosystems. Besides, not only were there few studies that included the impacts of diversification on input use, socio-economic sustainability and resilience capacity, but specific biodiversity attributes (e.g. functional diversity, landscape diversity) and ecosystem services (e.g. soil biological quality, water regulation, pollination) were generally underreported. The impact of diversification was more positive than negative in all dimensions of sustainability, with the exception of crop productivity. Yet, diversified systems are associated with reduced costs and high yields can still be achieved in diversified systems with appropriate agricultural management (e.g. adequate number and type of shade trees). Key to reaping the benefits of diversified systems is that the diversity of elements is carefully integrated considering the impact on multiple dimensions of system sustainabil

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

Nitrogen (N) management is important for farmers to balance production, economic and environmental performance of their farms. This is particularly true in the intensive cropping systems of northwest Europe where tuber, root and bulb crops are cultivated in rotation with cereal crops and where an intensive livestock sector makes organic manures available at low cost for arable farmers. Here, we build upon a large database of farmer field data to assess mineral and organic fertiliser N performance, and its determinants, for the major arable crops in the Netherlands according to the guidelines provided by the EU N Expert Panel (EUNEP). The EUNEP framework quantifies N outputs and N inputs, N-use efficiency as the ratio between N outputs and N inputs (NUE in kg N output harvested per kg N input) and N surplus as the difference between N inputs and N outputs (Ns in kg N ha−1). As a next step, biophysical and crop management determinants of N performance were explored using data from different years, soil types and N management in relation to the amount, source, time and method of N applied. NUE was on average ca. 0.95 kg N kg−1 N for seed potato, sugar beet and spring onion, 0.87 kg N kg−1 N for ware potato, ca. 0.80 kg N kg−1 N for starch potato and winter wheat and, ca. 0.70 kg N kg−1 N for spring barley, all within or above the target range of 0.50–0.90 kg N kg−1 N proposed by the EUNEP. Ns was on average below the EUNEP threshold of 80 kg N ha−1 for all crops: 78 kg N ha−1 for ware potato and winter wheat, ca. 70 kg N ha−1 for starch potato, ca. 50 kg N ha−1 for spring barley, ca. 25 kg N ha−1 for sugar beet and spring onion and less than 20 kg N ha−1 for seed potato. Although average Ns was below 80 kg N ha−1, ca. 40% of the ware potato, starch potato and winter wheat fields analyzed had Ns above this threshold. The relatively high NUE combined with high Ns for most crops are the result of high N outputs (yields) combined with high N application rates. Moreover, hi

During fieldwork to assess the status and ecology of Physcomitrium eurystomum Sendtn. in Britain, a naturally occurring sporophytic hybrid was found involving female Physcomitrium patens (Hedw.) Mitt. and male P. eurystomum, previously given the invalid name Physcomitrella amanni Głow. nom. nud. Recent authors have usually placed P. patens in Physcomitrella Bruch & Schimp. or hanorrhegma Sull., but Medina et al. (2019) show both are synonymous with Physcomitrium. Hill et al. (2006) comment Physcomitrella × hampei Limpr. is usually interpreted as Physcomitrium patens × P. eurystomum, for example by Frey et al. (2006), but the protologue for P. × hampei clearly describes parentage as female P. patens and male P. sphaericum (Limpricht 1885), as stated correctly by various subsequent authors, such as Britton (1895), Györffy (1907) and Nieuwkoop (2016). The purpose of this note is to provide a valid name and description for the sporophytic hybrid Physcomitrium patens × P. eurystomum, and to describe its differentiation and designate a type. Turland et al. (2018) is followed for nomenclatural guidance.

Yield gaps and water productivity are key indicators to monitor the progress towards more sustainable and productive cropping systems. Individual farmers are collecting increasing amounts of data (‘big data’), which can help monitor the process of sustainable intensification at local level. In this study, we build upon such data to quantify the magnitude and identify the biophysical and management determinants of on-farm yield gaps and water productivity for the main arable crops cultivated in the Netherlands. The analysis focused on ware, seed and starch potatoes, sugar beet, spring onion, winter wheat and spring barley and covered the period 2015–2017. A crop modelling approach based on crop coefficients (kc) and daily weather data was used to estimate the potential yield (Yp), radiation intercepted and potential evapotranspiration (ETP) for each crop. Yield gaps were estimated to be ca. 10% of Yp for sugar beet, 25–30% of Yp for ware, seed and starch potato and spring barley, and 35–40% of Yp for spring onion and winter wheat. Variation in actual yields was associated with water availability in key periods of the growing season as well as with sowing and harvest dates. However, the R2 of the fitted regressions was rather low (20–49%). Current levels of crop water productivity ranged between 13 kg DM ha−1 mm−1 for spring barley, ca. 15 kg DM ha−1 mm−1 for seed potato, spring onion and winter wheat, 23 kg DM ha−1 mm−1 for ware potato and ca. 25 kg DM ha−1 mm−1 for starch potato and sugar beet. These values are about half of their potential, but increasing actual water productivity further is restricted by rainfall amount and distribution. However, doing so should not be prioritized over reducing environmental impacts of these intensive cropping systems in the short-term and may require large investments from farm to regional levels in the long-term. Although these findings are most relevant to similar cropping systems in NW Europe, the underlying methods are generi

• Background and Aims Although phenotypic plasticity has been shown to be beneficial for plant competitiveness for light, there is limited knowledge on how variation in these plastic responses plays a role in determining competitiveness. • Methods A combination of detailed plant experiments and functional–structural plant (FSP) modelling was used that captures the complex dynamic feedback between the changing plant phenotype and the within-canopy light environment in time and 3-D space. Leaf angle increase (hyponasty) and changes in petiole elongation rates in response to changes in the ratio between red and far-red light, two important shade avoidance responses in Arabidopsis thaliana growing in dense population stands, were chosen as a case study for plant plasticity. Measuring and implementing these responses into an FSP model allowed simulation of plant phenotype as an emergent property of the underlying growth and response mechanisms. • Key Results Both the experimental and model results showed that substantial differences in competitiveness may arise between genotypes with only marginally different hyponasty or petiole elongation responses, due to the amplification of plant growth differences by small changes in plant phenotype. In addition, this study illustrated that strong competitive responses do not necessarily have to result in a tragedy of the commons; success in competition at the expense of community performance. • Conclusions Together, these findings indicate that selection pressure could probably have played a role in fine-tuning the sensitive shade avoidance responses found in plants. The model approach presented here provides a novel tool to analyse further how natural selection could have acted on the evolution of plastic responses.

Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.

Background and Aims The rising atmospheric CO2 concentration ([CO2]) is a ubiquitous selective force that may strongly impact species distribution and vegetation functioning. Plant–plant interactions could mediate the trajectory of vegetation responses to elevated [CO2], because some plants may benefit more from [CO2] elevation than others. The relative contribution of plastic (within the plant’s lifetime) and genotypic (over several generations) responses to elevated [CO2] on plant performance was investigated and how these patterns are modified by plant–plant interactions was analysed. Methods Plantago asiatica seeds originating from natural CO2 springs and from ambient [CO2] sites were grown in mono stands of each one of the two origins as well as mixtures of both origins. In total, 1944 plants were grown in [CO2]-controlled walk-in climate rooms, under a [CO2] of 270, 450 and 750 ppm. A model was used for upscaling from leaf to whole-plant photosynthesis and for quantifying the influence of plastic and genotypic responses. Key Results It was shown that changes in canopy photosynthesis, specific leaf area (SLA) and stomatal conductance in response to changes in growth [CO2] were mainly determined by plastic and not by genotypic responses. We further found that plants originating from high [CO2] habitats performed better in terms of whole-plant photosynthesis, biomass and leaf area, than those from ambient [CO2] habitats at elevated [CO2] only when both genotypes competed. Similarly, plants from ambient [CO2] habitats performed better at low [CO2], also only when both genotypes competed. No difference in performance was found in mono stands. Conclusion The results indicate that natural selection unde

According to the Shifting Defense Hypothesis, invasive plants should trade-off their costly quantitative defense to cheaper qualitative defense and growth due to the lack of natural specialist enemies and the presence of generalist enemies in the introduced areas. Several studies showed that plant genotypes from the invasive areas had a better qualitative defense than genotypes from the native area but only a few studies have focused on the quantitative defenses and tolerance ability. We compared structural defenses, tolerance and growth between invasive and native plant populations from different continents using the model plant Jacobaea vulgaris. We examined several microscopical structure traits, toughness, amount of cell wall proteins, growth and root-shoot ratio, which is a proxy for tolerance. The results show that invasive Jacobaea vulgaris have thinner leaves, lower leaf mass area, lower leaf cell wall protein contents and a lower root-shoot ratio than native genotypes. It indicates that invasive genotypes have poorer structural defense and tolerance to herbivory but potentially higher growth compared to native genotypes. These findings are in line with the Evolution of Increased Competitive Ability hypothesis and Shifting Defense Hypothesis. We also show that the invasiveness of this species in three geographically separated regions is consistently associated with the loss of parts of its quantitative defense and tolerance ability. The simultaneous change in quantitative defense and tolerance of the same magnitude and direction in the three invasive regions can be explained by parallel evolution. We argue that such parallel evolution might be attributed to the absence of natural enemies rather than adaptation to local abiotic factors, since climate conditions among these three regions were different. Understanding such evolutionary changes helps to understand why plant species become invasive and might be important for biological control.

Excessive growth of non-woody plants and shrubs on degraded lands can strongly hamper tree growth and thus secondary forest succession. A common method to accelerate succession, called liberation, involves opening up the vegetation canopy around young target trees. This can increase growth of target trees by reducing competition for light with neighboring plants. However, liberation has not always had the desired effect, likely due to differences in light requirement between tree species. Here we present a 3D-model, which calculates photosynthetic rate of individual trees in a vegetation stand. It enables us to examine how stature, crown structure, and physiological traits of target trees and characteristics of the surrounding vegetation together determine effects of light on tree growth. The model was applied to a liberation experiment conducted with three pioneer species in a young secondary forest in Vietnam. Species responded differently to the treatment depending on their height, crown structure and their shade-tolerance level. Model simulations revealed practical thresholds over which the tree growth response is heavily influenced by the height and density of surrounding vegetation and gap radius. There were strong correlations between calculated photosynthetic rates and observed growth: the model was well able to predict growth of trees in young forests and the effects of liberation there upon. Thus, our model serves as a useful tool to analyze light competition between young trees and surrounding vegetation and may help assess the potential effect of tree liberation.