Addressing inequality and intolerance in human–wildlife coexistence

Millennia of human conflict with wildlife have built a culture of intolerance toward wildlife among some stakeholders. We explored 2 key obstacles to improved human–wildlife coexistence: coexistence inequality (how the costs and benefits of coexisting with wildlife are unequally shared) and intolerance. The costs of coexisting with wildlife are often disproportionately borne by the so-called global south and rural communities, and the benefits often flow to the global north and urban dwellers. Attitudes and behaviors toward wildlife (tolerance versus intolerance) vary with social and cultural norms. We suggest more empathetic advocacy is needed that, for example, promotes conservation while appropriately considering those who bear the costs of conflict with wildlife. To achieve more equitable cost-sharing, we suggest limiting the costs incurred by those most affected or by sharing those costs more widely. For example, we advocate for the development of improved wildlife compensation schemes, increasing the scale of rewilding efforts, and preventing wildlife-derived revenue leaching out of the local communities bearing the costs of coexistence.     

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

In the mid nineteen eighties the Dutch NO_x air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NO_x concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

Separating the effects of partial submergence and soil oxygen demand on plant physiology

In wetlands, a distinct zonation of plant species composition occurs along moisture gradients, due to differential flooding tolerance of the species involved. However, "flooding" comprises two important, distinct stressors (soil oxygen demand [SOD] and partial submergence) that affect plant survival and growth. To investigate how these two flooding stressors affect plant performance, we executed a factorial experiment (water depth x SOD) for six plant species of nutrient-rich and nutrient-poor conditions, occurring along a moisture gradient in Dutch dune slacks. Physiological, growth, and biomass responses to changed oxygen availability were quantified for all species. The responses were consistent with field zonation, but the two stressors affected species differently. Increased SOD increased root oxygen deprivation, as indicated by either raised porosity or increased alcohol dehydrogenase (ADH) activity in roots of flood-intolerant species (Calamagrostis epigejos and Carex arenaria). While SOD affected root functioning, partial submergence tended more to reduce photosynthesis (as shown both by gas exchange and 13C assimilation), leaf dark respiration, 13C partitioning from shoots to roots, and growth of these species. These processes were especially affected if the root oxygen supply was depleted by a combination of flooding and increased SOD. In contrast, the most flood-tolerant species (Juncus subnodulosus and Typha latifolia) were unaffected by any treatment and maintained high internal oxygen concentrations at the shoot : root junction and low root ADH activity in all treatments. For these species, the internal oxygen transport capacity was well in excess of what was needed to maintain aerobic metabolism across all treatments, although there was some evidence for effects of SOD on their nitrogen partitioning (as indicated by 865N values) and photosynthesis. Two species intermediate in flooding tolerance (Carex nigra and Schoenus nigricans) responded more idiosyncratically, with different parameters responding to different treatments. These results show that partial submergence and soil flooding are two very different stressors to which species respond in different ways, and that their effects on physiology, survival, and growth are interactive. Understanding species zonation with water regimes can be improved by a better appreciation of how these factors affect plant metabolism independently and interactively.     

Coral cavity sponges depend on reef-derived food resources: stable isotope and fatty acid constraints

The diet of cavity sponges on the narrow fringing reefs of Curaçao, Caribbean was studied. The origin and resources of the bulk food of these sponges, i.e., dissolved organic matter (DOM), were identified using stable carbon and nitrogen isotopes and fatty acid biomarkers. We found that phytoplankton and its derived DOM from the adjacent open sea and from reef overlying water is not the main source of food for most of the sponges examined nor is bacterioplankton. Interestingly, dual stable isotope signatures (δ¹³C_org, δ¹⁵N_org) and fatty acid biomarkers appoint coral mucus and organic matter derived from crustose coralline algae (CCA) as probable food sources for encrusting sponges. Mucus-derived DOM may contribute up to 66% to the diet of examined sponges based on results of dual isotope mixing model analysis. The contribution of CCA (as purported representative for benthic algae) was smaller with values up to 31%. Together, mucus- and CCA-derived substrates contributed for 48–73% to the diet of sponges. The presence of the exogenous fatty acid 20:4ω6 in sponges, which is abundant in coral mucus of Madracis mirabilis and in CCA, highlights these reef-derived resources as sources of nutrition for DOM feeding cavity sponges. The relatively high concentrations of exogenous 20:4ω6 in all sponges examined supports our hypothesis that the bulk of the food of the cavity sponge community is reef-derived. Our results imply that cavity sponges play an important role in conserving food and energy produced within the reef.     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Floristic composition and vegetation ecology of the Malindi bay coastal dune field, Kenya

A short outline is given of the floristic composition, structure and distribution of coastal dune vegetation found at Malindi Bay, Kenya. The area was studied by air photo interpretation and field sampling to determine the relationship of plants to aeolian features. TWINSPAN classification was used to distinguish geomorphological units on the basis of their species composition. In this paper, an inventory and first quantitative analysis of vegetation distribution is presented. We identified 174 plant species from 62 families in the sand dunes and several plant communities are distinguished based on the species content and the connection with morphological units.Papilionaceae with 18 species andPoaceae with 17 species were the most represented families. A distinct zonal distribution of the plant communities was found. The most important plant species are the pioneer vegetation consisting ofHalopyrum mucronatum, Ipomoea pescaprae andScaevola plumieri. The woody shrub species which have colonized the established primary dunes and hummock dunes areCordia somaliensis, Pluchea discoridis, Tephrosia purpurea (dunensis). Succulent herbs were identified in the dune slacks and salt marsh that are moist and damp environments.     

Transforming conservation science and practice for a postnormal world

We examine issues to consider when reframing conservation science and practice in the context of global change. New framings of the links between ecosystems and society are emerging that are changing peoples’ values and expectations of nature, resulting in plural perspectives on conservation. Reframing conservation for global change can thus be regarded as a stage in the evolving relationship between people and nature rather than some recent trend. New models of how conservation links with transformative adaptation include how decision contexts for conservation can be reframed and integrated with an adaptation pathways approach to create new options for global‐change‐ready conservation. New relationships for conservation science and governance include coproduction of knowledge that supports social learning. New processes for implementing adaptation for conservation outcomes include deliberate practices used to develop new strategies, shift world views, work with conflict, address power and intergenerational equity in decisions, and build consciousness and creativity that empower agents to act. We argue that reframing conservation for global change requires scientists and practitioners to implement approaches unconstrained by discipline and sectoral boundaries, geopolitical polarities, or technical problematization. We consider a stronger focus on inclusive creation of knowledge and the interaction of this knowledge with societal values and rules is likely to result in conservation science and practice that meets the challenges of a postnormal world.     

Nest desertion is not predicted by cuckoldry in the Eurasian penduline tit

Engagement in extra-pair copulations is an example of the abundant conflicting interests between males and females over reproduction. Potential benefits for females and the risk of cuckoldry for males are expected to have important implications on the evolution of parental care. However, whether parents adjust parental care in response to parentage remains unclear. In Eurasian penduline tits Remiz pendulinus, which are small polygamous songbirds, parental care is carried out either by the male or by the female. In addition, one third of clutches is deserted by both male and female. Desertion takes place during the egg-laying phase. Using genotypes of nine microsatellite loci of 443 offspring and 211 adults, we test whether extra-pair paternity predicts parental care. We expect males to be more likely to desert cuckolded broods, whereas we expect females, if they obtain benefits from having multiple sires, to be more likely to care for broods with multiple paternity. Our results suggest that parental care is not adjusted to parentage on an ecological timescale. Furthermore, we found that male attractiveness does not predict cuckoldry, and we found no evidence for indirect benefits for females (i.e., increased growth rates or heterozygosity of extra-pair offspring). We argue that male Eurasian penduline tits may not be able to assess the risk of cuckoldry; thus, a direct association with parental care is unlikely to evolve. However, timing of desertion (i.e., when to desert during the egg-laying phase) may be influenced by the risk of cuckoldry. Future work applying extensive gene sequencing and quantitative genetics is likely to further our understanding of how selection may influence the association between parentage and parental care.     

Twenty years of salt marsh succession on a Dutch coastal barrier island

After a formerly grazed salt marsh was released from cattle grazing, changes in plant species composition were monitored for 20 yr, using vegetation maps and permanent plots. Three areas, differing in age and nutrient status were compared. The number of plant species and plant communities decreased.Elymus athericus (Elytrigia pungens) became dominant in most plant communities after 5–20 yr on the oldest and most productive salt marsh. In younger areas it took more time forE. athericus to become dominant. At least 7 cm of clay seemed to be a prerequisite for this plant species to increase in dominance. The results from monitoring over decades are discussed in view of the knowledge on succession over centuries as derived from a chronosequence.