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AbstractGlobal challenges related to land, biodiversity, food and climate interact in diverse ways depending on local conditions and the broader context in which they are embedded. This diversity challenges learning and integrated decision-making to sustainably transform the nexus, that is to say the interactions between these land-based challenges. Providing aggregated insights, archetype analysis has revealed recurrent patterns within the multitude of interactions, i.e. interaction archetypes that are essential to enhance the understanding of nexus relations. This paper synthesises the state of knowledge on interaction or nexus archetypes related to land, biodiversity, food and climate based on a systematic literature review. It focusses on the coverage of thematic aspects, regional distribution, social dimensions and methodologies. The results show that consideration of comprehensive land–biodiversity–food–climate interactions is rare. Furthermore, there are pronounced regional knowledge gaps, social dimensions are inadequately captured, and methodological shortcomings are evident. To enhance the investigation of interaction archetypes, we have framed a future research agenda providing directions to fully capture interactions across space and time, better use the potential of scenario archetypes and up-scale transformative actions. These advances will constructively contribute insights that help to achieve the ambitious objective to sustainably transform the nexus between land, biodiversity, food and climate.
AbstractArchetype analysis is a promising approach in sustainability science to identify patterns and explain mechanisms shaping the sustainability of social-ecological systems. Although considerable efforts have been devoted to developing quality standards and methodological advances for archetype analysis, archetype validation remains a major challenge. Drawing on the insights from two international workshops on archetype analysis and on broader literature on validity, we propose a framework that identifies and describes six dimensions of validity: conceptual; construct; internal; external; empirical; and application validity. We first discuss the six dimensions in relation to different methodological approaches and purposes of archetype analysis. We then present an operational use of the framework for researchers to assess the validity of archetype analysis and to support sound archetype identification and policy-relevant applications. Finally, we apply our assessment to 18 published archetype analyses, which we use to describe the challenges and insights in validating the different dimensions and suggest ways to holistically improve the validity of identified archetypes. With this, we contribute to more rigorous archetype analyses, helping to develop the potential of the approach for guiding sustainability solutions.
Coastal sand dunes near the Baltic Sea are a dynamic environment marking the boundary between land and sea and oftentimes covered by Scots pine (Pinus sylvestris L.) forests. Complex climate-environmental interactions characterize these ecosystems and largely determine the productivity and state of these coastal forests. In the face of future climate change, understanding interactions between coastal tree growth and climate variability is important to promote sustainable coastal forests. In this study, we assessed the effect of microsite conditions on tree growth and the temporal and spatial variability of the relationship between climate and Scots pine growth at nine coastal sand dune sites located around the south Baltic Sea. At each site, we studied the growth of Scots pine growing at microsites located at the ridge and bottom of a dune and built a network of 18 ring-width and 18 latewood blue intensity chronologies. Across this network, we found that microsite has a minor influence on ring-width variability, basal area increment, latewood blue intensity, and climate sensitivity. However, at the local scale, microsite effects turned out to be important for growth and climate sensitivity at some sites. Correlation analysis indicated that the strength and direction of climate-growth responses for the ring-width and blue intensity chronologies were similar for climate variables over the 1903–2016 period. A strong and positive relationship between ring-width and latewood blue intensity chronologies with winter-spring temperature was detected at local and regional scales. We identified a relatively strong, positive influence of winter-spring/summer moisture availability on both tree-ring proxies. When climate-growth responses between two intervals (1903–1959, 1960–2016) were compared, the strength of growth responses to temperature and moisture availability for both proxies varied. More specifically, for the ring-width network, we identified decreasing temperature-growth responses, which is in contrast to the latewood blue intensity network, where we documented decreasing and increasing temperature-growth relationships in the north and south respectively. We conclude that coastal Scots pine forests are primarily limited by winter-spring temperature and winter-spring/summer drought despite differing microsite conditions. We detected some spatial and temporal variability in climate-growth relationships that warrant further investigation.
Determining the effect of a changing climate on tree growth will ultimately depend on our understanding of wood formation processes and how they can be affected by environmental conditions. In this context, monitoring intra-annual radial growth with high temporal resolution through point dendrometers has often been used. Another widespread approach is the microcoring method to follow xylem and phloem formation at the cellular level. Although both register the same biological process (secondary growth), given the limitations of each method, each delivers specific insights that can be combined to obtain a better picture of the process as a whole. To explore the potential of visualizing combined dendrometer and histological monitoring data and scrutinize intra-annual growth data on both dimensions (dendrometer → continuous; microcoring → discrete), we developed DevX (Dendrometer vs. Xylogenesis), a visualization application using the “Shiny” package in the R programming language. The interactive visualization allows the display of dendrometer curves and the overlay of commonly used growth model fits (Gompertz and Weibull) as well as the calculation of wood phenology estimates based on these fits (growth onset, growth cessation, and duration). Furthermore, the growth curves have interactive points to show the corresponding histological section, where the amount and development stage of the tissues at that particular time point can be observed. This allows to see the agreement of dendrometer derived phenology and the development status at the cellular level, and by this help disentangle shrinkage and swelling due to water uptake from actual radial growth. We present a case study with monitoring data for Acer pseudoplatanus L., Fagus sylvatica L., and Quercus robur L. trees growing in a mixed stand in northeastern Germany. The presented application is an example of the innovative and easy to access use of programming languages as basis for data visualization, and can be further used as a learning tool in the topic of wood formation and its ecology. Combining continuous dendrometer data with the discrete information from histological-sections provides a tool to identify active periods of wood formation from dendrometer series (calibrate) and explore monitoring datasets.
Sal (Shorea robusta) forests, a dominant forest type in Nepal, experience different disturbance intensities depending on management regimes. This study compares the impact of disturbance on Nepalese Sal forests, which are managed on three major management regimes: protected area, state-managed forest, and buffer zone community forest. Using a systematic sampling approach, we sampled 20 plots, each covering 500 square meters, and nested plots within each main plot to measure pole and regeneration for each management regime. We recorded forest characteristics including tree species, counts, diameter, height, crown cover, and disturbance indicators. We compared forest attributes such as diversity indices, species richness, and stand structure by management regime using analysis of variance and regression analysis. The forest management regimes were classified into three disturbance levels based on disturbance factor bundles, and the buffer zone community forest was found to have the highest disturbance while the protected forest had the lowest disturbance. Species richness, diversity, evenness, abundance, density and basal area were higher, but regeneration was lower in protected area and state-managed forest compared to the buffer zone community forests. This suggests positive impacts of moderate disturbance on regeneration. The management plan should prioritize the minimization of excessive disturbance to balance forest conservation and provide forest resources to local users.
A massive shift in agricultural practices over the past decades, to support exceptionally high yields and productivities involving intensive agriculture, have led to unsustainable agriculture practices across the globe. Sustenance of such high yields and productivities demand high use of organic and industrial fertilizers. This acts as a negative pressure on the environment. Excessive use of fertilizers leads to nutrient surplus in the fields, which, as a part of catchment runoff, flows into the water bodies as diffuse pollution. These nutrients through rivers are eventually passed into seas. High nutrients ending up into water bodies cause eutrophication. The situation is worsened when such unsustainable agricultural activities are carried out on drained peatlands. As a result, the nutrients that were not part of the nutrient cycle in the landscape for years begin to leach out due to mineralization of peatlands, thereby putting an additional load of nutrients on the environment, that was already under the negative impact of nutrient surplus. In view of the above, a small lowland catchment of the Ryck river in northeast Germany was assessed for its nitrogen losses from agricultural lands through empirical modelling. Initial empirical modelling resulted in an average annual total nitrogen loss of 14.7 kg ha−1 year−1. After a comparative analysis of these results with procured data, the empirical equation was modified to suit the catchment, yielding more accurate results. The study showed that 75.6% of peatlands in the catchment are under agricultural use. Subsequently, a proposal was made for potential wetland buffer zones in the Ryck catchment. Altogether, 13 peatland sites across 8 sub-catchments were recommended for mitigation of high nutrient runoff. In the end, nutrient efficiency of proposed WBZs in one of the sub-catchments of Ryck has been discussed. The results show that (i) the modified empirical equation can act as a key tool in application-based future strategies for nitrogen reduction in the Ryck catchment, (ii) restoration of peatlands and introduction of WBZs can help in mitigating the nutrient runoff for improved water quality of Ryck, and subsequently (ii) contribute to efficient reduction of riverine loads of nutrients into the Baltic Sea.
Samples of two duckweed species, Spirodela polyrhiza and Lemna minor, were collected around small ponds and investigated concerning the question of whether natural populations of duckweeds constitute a single clone, or whether clonal diversity exists. Amplified fragment length polymorphism was used as a molecular method to distinguish clones of the same species. Possible intraspecific diversity was evaluated by average-linkage clustering. The main criterion to distinguish one clone from another was the 95% significance level of the Jaccard dissimilarity index for replicated samples. Within natural populations of L. minor, significant intraspecific genetic differences were detected. In each of the three small ponds harbouring populations of L. minor, based on twelve samples, between four and nine distinct clones were detected. Natural populations of L. minor consist of a mixture of several clones representing intraspecific biodiversity in an aquatic ecosystem. Moreover, identical distinct clones were discovered in more than one pond, located at a distance of 1 km and 2.4 km from each other. Evidently, fronds of L. minor were transported between these different ponds. The genetic differences for S. polyrhiza, however, were below the error-threshold of the method within a pond to detect distinct clones, but were pronounced between samples of two different ponds.
Pollen productivity estimates (PPEs) are a key parameter for quantitative land-cover reconstructions from pollen data. PPEs are commonly estimated using modern pollen-vegetation data sets and the extended R-value (ERV) model. Prominent discrepancies in the existing studies question the reliability of the approach. We here propose an implementation of the ERV model in the R environment for statistical computing, which allows for simplified application and testing. Using simulated pollen-vegetation data sets, we explore sensitivity of ERV application to (1) number of sites, (2) vegetation structure, (3) basin size, (4) noise in the data, and (5) dispersal model selection. The simulations show that noise in the (pollen) data and dispersal model selection are critical factors in ERV application. Pollen count errors imply prominent PPE errors mainly for taxa with low counts, usually low pollen producers. Applied with an unsuited dispersal model, ERV tends to produce wrong PPEs for additional taxa. In a comparison of the still widely applied Prentice model and a Lagrangian stochastic model (LSM), errors are highest for taxa with high and low fall speed of pollen. The errors reflect the too high influence of fall speed in the Prentice model. ERV studies often use local scale pollen data from for example, moss polsters. Describing pollen dispersal on his local scale is particularly complex due to a range of disturbing factors, including differential release height. Considering the importance of the dispersal model in the approach, and the very large uncertainties in dispersal on short distance, we advise to carry out ERV studies with pollen data from open areas or basins that lack local pollen deposition of the taxa of interest.
Changing climate can strongly affect tree growth and forest productivity. The dendrochronological approach to assessing the impact of climate change on tree growth is possible through climate–growth correlation analysis. This study uses an individual tree-based approach to model Pinus wallichiana (P. wallichiana) radial growth response to climate across the physiographic gradients in the lower distributional range of Nepal. This study sampled six sites across the Makwanpur district of central Nepal that varied in elevation and aspect, obtaining 180 tree-ring series. Climate data series were obtained from Climate Research Unit (CRU 4.0). The pair correlation approach was used to assess P. wallichiana growth response to climate and site-level physiographic variables such as site-level environmental stress. The study also determined long-term growth trends across the elevation and aspect gradients. Trees at sites with higher elevation and northeast aspect (NEA) were more responsive to winter and spring precipitation, whereas trees with lower elevation and northwest aspect (NWA) were more responsive to winter and spring precipitation. Basal area increment (BAI) analysis showed the variation of growth at site-level environmental stress, suggesting that the sensitivity of forest ecosystems to changing climate will vary across the lower growth limit of P. wallichiana due to differences in local physiographic conditions.
Agriculture in the populated islands of the Galapagos Archipelago, a protected area due to its unique biodiversity, has been detrimental to its conservation but highly required to meet food necessities. A potential solution to make agricultural farming more sustainable is adopting water-saving technologies (WSTs). Therefore, this study aimed to test the effectiveness of using WSTs such as Groasis Waterboxx® in three of the most valuable crops in the islands through participatory research with the involvement of a group of farmers from the Floreana and Santa Cruz islands and explore a possible transition to more sustainable agricultural practices. Capsicum annuum, Cucumis sativus and Solanum lycopersicum were cultivated using Groasis Waterboxx® and compared to conventional irrigation practices (drip-irrigated controls) to assess the variability of productivity, the number of fruits and individual fruit weight (IFW). In addition, differences in plant traits were analyzed by crop, and island. Results suggested that WSTs such as Groasis Waterboxx® may provide on-farm benefits regarding the yields of the studied traits. From this study, it is difficult to determine whether participation in such a research study will permanently change irrigation practices. However, the participant’s responses to the study suggest an increase in their understanding of the use and benefits of WST.