Knowledge for sustainable development: a worldviews perspective

A huge tension exists between recognizing sustainable development (SD) as a meta-discourse and accepting a limitless interpretational width. We analyse the impacts of diversity of worldviews on the interpretation of SD—as a knowledge-based concept—through a critical literature review, resulting in recommendations on the topic. We apply a social-constructionist approach, appreciating the complex socio-ecological interactions at the heart of SD. Only recently worldviews are recognized as constitutive elements of SD. Little attention has been given to the impacts on generated knowledge for SD. Variety of worldviews induces a variety of knowledge claims and needs. To retain SD’s ‘universal’ appeal as practical decision-guiding strategy for policy and action, we propose an integrative approach towards knowledge for SD—entailing an explicit pluralization of knowledge. SD should be re-interpreted as a joint worldviews construct, embracing a diversity of views in collaborative research and co-production of knowledge. Interpreting SD as a joint endeavour is necessary to overcome historical obstacles like cultural hegemony and a hierarchy of knowledge systems. We identified the following requirements for an inclusive knowledge for SD paradigm: re-interpretation of SD as a worldview constructs in progress; interpretative flexibility; co-production of knowledge; subjectivity awareness and self-reflexivity; respect for a diversity of worldviews/knowledges; identifying shared goals; collaborative research; a systems approach; transdisciplinarity; and recognition of contextuality. Further research—concerning potential methodologies and typologies—to reconcile variety of worldviews and knowledge systems in a joint SD worldviews construct is urgently needed.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Metapopulation dynamics in the butterfly Hipparchia semele changed decades before occupancy declined in The Netherlands

The survival of many species in human-dominated, fragmented landscapes depends on metapopulation dynamics, i.e., on a dynamic equilibrium of extinctions and colonizations in patches of suitable habitat. To understand and predict distributional changes, knowledge of these dynamics can be essential, and for this, metapopulation studies are preferably based on long-time-series data from many sites. Alas, such data are very scarce. An alternative is to use opportunistic data (i.e., collected without applying standardized field methods), but these data suffer from large variations in field methods and search intensity between sites and years. Dynamic site-occupancy models offer a general approach to adjust for variable survey effort. These models extend classical metapopulation models to account for imperfect detection of species and yield estimates of the probabilities of occupancy, colonization, and survival of species at sites. By accounting for detection, they fully correct for among-year variability in search effort. As an illustration, we fitted a dynamic site-occupancy model to 60 years of presence-absence data (more precisely, detection-nondetection) of the heathland butterfly Hipparchia semele in The Netherlands. Detection records were obtained from a database containing volunteer-based data from 1950-2009, and nondetection records were deduced from database records of other butterfly species. Our model revealed that metapopulation dynamics of Hipparchia had changed decades before the species' distribution began to contract. Colonization probability had already started to decline from 1950 onward, but this was counterbalanced by an increase in the survival of existing populations, the result of which was a stable distribution. Only from 1990 onward was survival not sufficient to compensate for the further decrease of colonization, and occupancy started to decline. Hence, it appears that factors acting many decades ago triggered a change in the metapopulation dynamics of this species, which ultimately led to a severe decline in occupancy that only became apparent much later. Our study emphasizes the importance of knowledge of changes in survival and colonization of species in modern landscapes over a very long time scale. It also demonstrates the power of site-occupancy modeling to obtain important population dynamics information from databases containing opportunistic sighting records.     

Genomic erosion in a demographically recovered bird species during conservation rescue

The pink pigeon (Nesoenas mayeri) is an endemic species of Mauritius that has made a remarkable recovery after a severe population bottleneck in the 1970s to early 1990s. Prior to this bottleneck, an ex situ population was established from which captive-bred individuals were released into free-living subpopulations to increase population size and genetic variation. This conservation rescue led to rapid population recovery to 400–480 individuals, and the species was twice downlisted on the International Union for the Conservation of Nature (IUCN) Red List. We analyzed the impacts of the bottleneck and genetic rescue on neutral genetic variation during and after population recovery (1993–2008) with restriction site-associated sequencing, microsatellite analyses, and quantitative genetic analysis of studbook data of 1112 birds from zoos in Europe and the United States. We used computer simulations to study the predicted changes in genetic variation and population viability from the past into the future. Genetic variation declined rapidly, despite the population rebound, and the effective population size was approximately an order of magnitude smaller than census size. The species carried a high genetic load of circa 15 lethal equivalents for longevity. Our computer simulations predicted continued inbreeding will likely result in increased expression of deleterious mutations (i.e., a high realized load) and severe inbreeding depression. Without continued conservation actions, it is likely that the pink pigeon will go extinct in the wild within 100 years. Conservation rescue of the pink pigeon has been instrumental in the recovery of the free-living population. However, further genetic rescue with captive-bred birds from zoos is required to recover lost variation, reduce expression of harmful deleterious variation, and prevent extinction. The use of genomics and modeling data can inform IUCN assessments of the viability and extinction risk of species, and it helps in assessments of the conservation dependency of populations.     

Invasive plants as biosorbents for environmental remediation: a review

Environmental Chemistry Letters - Water contamination is an environmental burden for the next generations, calling for advanced methods such as adsorption to remove pollutants. For instance,...     

Plastic waste as a valuable resource: strategy to remove heavy metals from wastewater in bench scale application

Environmental Science and Pollution Research - Single-use plastic waste is gradually considered a potential material for circular economy. Ion exchange resin obtained from polystyrene waste by...     

Assessment of total concentrations of heavy metals in industrial sludges from the North of Vietnam and their potential impact on the ecosystem

Environmental Science and Pollution Research - Industrial sludges from wastewater treatment plants of industrial parks and a drinking water treatment plant in northern Vietnam were investigated in...     

Ecological and physiological controls of species composition in green macroalgal blooms

Green macroalgal blooms have substantially altered marine community structure and function, specifically by smothering seagrasses and other primary producers that are critical to commercial fisheries and by creating anoxic conditions in enclosed embayments. Bottom-up factors are viewed as the primary drivers of these blooms, but increasing attention has been paid to biotic controls of species composition. In Washington State, USA, blooms are often dominated by Ulva spp. intertidally and Ulvaria obscura subtidally. Factors that could cause this spatial difference were examined, including competition, grazer preferences, salinity, photoacclimation, nutrient requirements, and responses to nutrient enrichment. Ulva specimens grew faster than Ulvaria in intertidal chambers but not significantly faster in subtidal chambers. Ulva was better able to acclimate to a high-light environment and was more tolerant of low salinity than Ulvaria. Ulvaria had higher tissue N content, chlorophyll, chlorophyll b: chlorophyll a, and protein content than Ulva. These differences suggest that nitrogen availability could affect species composition. A suite of five grazers preferred Ulva to Ulvaria in choice experiments. Thus, bottom-up factors allow Ulva to dominate the intertidal zone while resistance to grazers appears to allow Ulvaria to dominate the subtidal zone. While ulvoid algae are in the same functional-form group, they are not functionally redundant.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

Controlling mechanisms of aluminium in soil solution--an evaluation of 180 podzolic forest soils.

To monitor the level of soil acidification in the county of V?rmland in the middle west of Sweden 180 podzolic forest soils were investigated. Soil solutions from four horizons were obtained by centrifugation and the soil was sampled for a determination of the exchangeable pool by extraction. The concentrations of inorganic Al and its fraction of the total Al in solution were greater in the south of the county (up to 50%). The factors influencing the total Al and free inorganic Al3+ in the soil solutions were evaluated. Saturation indices (SI) for five different mineral phases were calculated but none implied equilibrium conditions. The relationships between pAl3+ and pH (in the pH range 4-6.2) gave slopes of about 1, which indicated that ion exchange/complexation reactions may be important for determining the Al3+ concentration in the B and C horizons. In the E horizon solutions complexation with soluble organic acids seemed to be the major factor which influenced the Al3+ activity. The influence of organic matter on Al solubility was supported by partial least square (PLS) regressions.