Exploring the contribution of nature-based solutions for environmental challenges in the Netherlands.

Nature-based solutions (NbS) offer a promising and sustainable approach to addressing multiple environmental challenges, including climate change, pollution, and biodiversity loss. Despite the potential of NbS, their actual effectiveness in solving these challenges remains uncertain. Therefore, this study evaluates the contribution of NbS implemented in a nature-inclusive scenario for six environmental challenges and associated policy targets in the Netherlands. Fifteen different NbS were applied in the scenario in urban, agricultural, aquatic, and protected nature areas, with measures like flower field margins, green roofs, groundwater level management, and river restoration. The spatially-explicit Natural Capital Model was used to quantify the effectiveness of all applied NbS at a national-scale. Results show NbS significantly contribute to simultaneously solving all six assessed environmental challenges. The most significant impact was seen in improving the quality of water bodies (+34 %), making agriculture more sustainable (+24 %), and protecting and restoring biodiversity (+22 %). The contribution of NbS to address the quality of the living environment (+13 %), climate change (+10 %), and the energy transition was less effective (+2 %). Furthermore, NbS can help to achieve sectoral policy targets at the global, EU, and national levels, including those related to the Birds Habitats Directives, carbon emission, and pesticide reduction targets. This study highlights the potential of NbS to effectively address multiple environmental challenges, although they do not provide a complete solution, and suggests that future research could focus on identifying even more effective ways to implement NbS, and to mainstream their use in policy and practice.

Effects of land use on infestation and parasitism rates of cabbage seed weevil in oilseed rape.

BACKGROUND: This study investigated how infestation rates of an important oilseed rape pest, the cabbage seed weevil (Ceutorhynchus obstrictus) and rates of parasitization by its parasitoids are affected by land use, up to 1000 m from 18 focal fields. RESULTS: The mean proportion of C. obstrictus-infested pods per plant was 8% (2-19.5%). Infestation rates were higher if the adjacent habitat was a herbaceous semi-natural habitat than if it was either another crop or a woody habitat. Infestation rates were positively related to the area of herbaceous semi-natural vegetation, permanent grassland and wheat (which followed oilseed rape in the crop rotation) at a spatial scale of at least 1 km. The mean parasitism rate of C. obstrictus larvae was 55% (8.3-87%), sufficient to provide efficient biocontrol. Parasitism rates were unrelated to adjacent habitats, however, they were positively related to the presence of herbaceous linear elements in the landscape and negatively related to permanent grasslands at a spatial scale of 200 m. CONCLUSION: Proximity of herbaceous elements increased both infestation rates and parasitism, while infestation was also related to landscape factors at larger distances. The findings provide an empirical basis for designing landscapes that suppress C. obstrictus, at both field and landscape scales. © 2018 Society of Chemical Industry.

Exploitation of chemical signaling by parasitoids: impact on host population dynamics.

Chemical information mediates species interactions in a wide range of organisms. Yet, the effect of chemical information on population dynamics is rarely addressed. We designed a spatio-temporal parasitoid--host model to investigate the population dynamics when both the insect host and the parasitic wasp that attacks it can respond to chemical information. The host species, Drosophila melanogaster, uses food odors and aggregation pheromone to find a suitable resource for reproduction. The larval parasitoid, Leptopilina heterotoma, uses these same odors to find its hosts. We show that when parasitoids can respond to food odors, this negatively affects fruit fly population growth. However, extra parasitoid responsiveness to aggregation pheromone does not affect fruit fly population growth. Our results indicate that the use of the aggregation pheromone by D. melanogaster does not lead to an increased risk of parasitism. Moreover, the use of aggregation pheromone by the host enhances its population growth and enables it to persist at higher parasitoid densities.

Timing in a fluctuating environment: environmental variability and asymmetric fitness curves can lead to adaptively mismatched avian reproduction.

Adaptation in dynamic environments depends on the grain, magnitude and predictability of ecological fluctuations experienced within and across generations. Phenotypic plasticity is a well-studied mechanism in this regard, yet the potentially complex effects of stochastic environmental variation on optimal mean trait values are often overlooked. Using an optimality model inspired by timing of reproduction in great tits, we show that temporal variation affects not only optimal reaction norm slope, but also elevation. With increased environmental variation and an asymmetric relationship between fitness and breeding date, optimal timing shifts away from the side of the fitness curve with the steepest decline. In a relatively constant environment, the timing of the birds is matched with the seasonal food peak, but they become adaptively mismatched in environments with temporal variation in temperature whenever the fitness curve is asymmetric. Various processes affecting the survival of offspring and parents influence this asymmetry, which collectively determine the 'safest' strategy, i.e. whether females should breed before, on, or after the food peak in a variable environment. As climate change might affect the (co)variance of environmental variables as well as their averages, risk aversion may influence how species should shift their seasonal timing in a warming world.

Odor-mediated aggregation enhances the colonization ability of Drosophila melanogaster.

Animal aggregation is a general phenomenon in ecological systems. Aggregations are generally considered as an evolutionary advantageous state in which members derive the benefits of mate choice and protection against natural enemies, balanced by the costs of limiting resources and intraspecific competition. Many insects use chemical information to find conspecifics and to form aggregations. In this study, we describe a spatio-temporal simulation model designed to explore and quantify the effects of the strength of chemical attraction, on the colonization ability of a fruit fly (Drosophila melanogaster) population. We found that the use of infochemicals is crucial for colonizing an area. Fruit flies subject to an Allee effect that are unable to respond to chemical information could not successfully colonize the area and went extinct within four generations. This was mainly caused by very high mortality due to the Allee effect. Even when the Allee effect did not play a role, the random dispersing population had more difficulties in colonizing the area and is doomed to extinction in the long run. When fruit flies had the ability to respond to chemical information, they successfully colonized the orchard. This happened faster, for stronger attraction to chemical information. In addition, more fruit flies were able to find the resources and the settlement on the resources was much higher. This resulted in a reduced mortality due to the Allee effect for fruit flies able to respond to chemical information. Odor-mediated aggregation thus enhances the colonization ability of D. melanogaster. Even a weak attraction to chemical information paved the way to successfully colonize the orchard.

The effect of chemical information on the spatial distribution of fruit flies: II Parameterization, calibration, and sensitivity.

In a companion paper (Lof et al., in Bull. Math. Biol., 2008), we describe a spatio-temporal model for insect behavior. This model includes chemical information for finding resources and conspecifics. As a model species, we used Drosophila melanogaster, because its behavior is documented comparatively well. We divide a population of Drosophila into three states: moving, searching, and settled. Our model describes the number of flies in each state, together with the concentrations of food odor and aggregation pheromone, in time and in two spatial dimensions. Thus, the model consists of 5 spatio-temporal dependent variables, together with their constituting relations. Although we tried to use the simplest submodels for the separate variables, the parameterization of the spatial model turned out to be quite difficult, even for this well-studied species. In the first part of this paper, we discuss the relevant results from the literature, and their possible implications for the parameterization of our model. Here, we focus on three essential aspects of modeling insect behavior. First, there is the fundamental discrepancy between the (lumped) measured behavioral properties (i.e., fruit fly displacements) and the (detailed) properties of the underlying mechanisms (i.e., dispersivity, sensory perception, and state transition) that are adopted as explanation. Detailed quantitative studies on insect behavior when reacting to infochemicals are scarce. Some information on dispersal can be used, but quantitative data on the transition between the three states could not be found. Second, a dose-response relation as used in human perception research is not available for the response of the insects to infochemicals; the behavioral response relations are known mostly in a qualitative manner, and the quantitative information that is available does not depend on infochemical concentration. We show how a commonly used Michaelis-Menten type dose-response relation (incorporating a saturation effect) can be adapted to the use of two different but interrelated stimuli (food odors and aggregation pheromone). Although we use all available information for its parameterization, this model is still overparameterized. Third, the spatio-temporal dispersion of infochemicals is hard to model: Modeling turbulent dispersal on a length scale of 10 m is notoriously difficult. Moreover, we have to reduce this inherently three-dimensional physical process to two dimensions in order to fit in the two-dimensional model for the insects. We investigate the consequences of this dimension reduction, and we demonstrate that it seriously affects the parameterization of the model for the infochemicals. In the second part of this paper, we present the results of a sensitivity analysis. This sensitivity analysis can be used in two manners: firstly, it tells us how general the simulation results are if variations in the parameters are allowed, and secondly, we can use it to infer which parameters need more precise quantification than is available now. It turns out that the short term outcome of our model is most sensitive to the food odor production rate and the fruit fly dispersivity. For the other parameters, the model is quite robust. The dependence of the model outcome with respect to the qualitative model choices cannot be investigated with a parameter sensitivity analysis. We conclude by suggesting some experimental setups that may contribute to answering this question.

The effect of chemical information on the spatial distribution of fruit flies: I Model results.

Animal aggregation is a general phenomenon in ecological systems. Aggregations are generally considered as an evolutionary advantageous state in which members derive the benefits of protection and mate choice, balanced by the costs of limiting resources and competition. In insects, chemical information conveyance plays an important role in finding conspecifics and forming aggregations. In this study, we describe a spatio-temporal simulation model designed to explore and quantify the effects of these infochemicals, i.e., food odors and an aggregation pheromone, on the spatial distribution of a fruit fly (Drosophila melanogaster) population, where the lower and upper limit of local population size are controlled by an Allee effect and competition. We found that during the spatial expansion and strong growth of the population, the use of infochemicals had a positive effect on population size. The positive effects of reduced mortality at low population numbers outweighed the negative effects of increased mortality due to competition. At low resource densities, attraction toward infochemicals also had a positive effect on population size during recolonization of an area after a local population crash, by decreasing the mortality due to the Allee effect. However, when the whole area was colonized and the population was large, the negative effects of competition on population size were larger than the positive effects of the reduction in mortality due to the Allee effect. The use of infochemicals thus has mainly positive effects on population size and population persistence when the population is small and during the colonization of an area.