Reforesting degraded agricultural landscapes with Eucalypts: effects on carbon storage and soil fertility after 26years

In the Western Australian wheatbelt, the restoration of native eucalypt forests for managing degraded agricultural landscapes is a critical part of managing dryland salinity and rebuilding biodiversity. Such reforestation will also sequester carbon. Whereas most investigative emphasis has been on carbon stored in biomass, the effects of reforestation on soil organic carbon (SOC) stores and fertility are not known. Two 26 year old reforestation experiments with four Eucalyptus species (E. cladocalyx var nana, E. occidentalis, E. sargentii and E. wandoo) were compared with agricultural sites (Field). SOC stores (to 0.3 m depth) ranged between 33 and 55 Mg ha−1, with no statistically significant differences between tree species and adjacent farmland. Farming comprised crop and pasture rotations. In contrast, the reforested plots contained additional carbon in the tree biomass (23–60 Mg ha−1) and litter (19–34 Mg ha−1), with the greatest litter accumulation associated with E. sargentii. Litter represented between 29 and 56% of the biomass carbon and the protection or utilization of this litter in fire-prone, semi-arid farmland will be an important component of carbon management. Exch-Na and Exch-Mg accumulated under E. sargentii and E. occidentalis at one site. The results raise questions about the conclusions of SOC sequestration studies following reforestation based on limited sampling and reiterate the importance of considering litter in reforestation carbon accounts.

A sustainable agricultural landscape for Australia: A review of interlacing carbon sequestration, biodiversity and salinity management in agroforestry systems

Transformation of the south-western Australian landscape from deep-rooted woody vegetation systems to shallow-rooted annual cropping systems has resulted in the severe loss of biodiversity and this loss has been exacerbated by rising ground waters that have mobilised stored salts causing extensive dry land salinity. Since the original plant communities were mostly perennial and deep rooted, the model for sustainable agriculture and landscape water management invariably includes deep rooted trees. Commercial forestry is however only economical in higher rainfall (>700 mm yr−1) areas whereas much of the area where biodiversity is threatened has lower rainfall (300–700 mm yr−1). Agroforestry may provide the opportunity to develop new agricultural landscapes that interlace ecosystem services such as carbon mitigation via carbon sequestration and biofuels, biodiversity restoration, watershed management while maintaining food production. Active markets are developing for some of these ecosystem services, however a lack of predictive metrics and the regulatory environment are impeding the adoption of several ecosystem services. Nonetheless, a clear opportunity exists for four major issues – the maintenance of food and fibre production, salinisation, biodiversity decline and climate change mitigation – to be managed at a meaningful scale and a new, sustainable agricultural landscape to be developed.

Three decades of policy layering and politically sustainable reform in the European Union’s Agricultural Policy

The study of policy reform has tended to focus on single-stage reforms taking place over a relatively short period. Recent research has drawn attention to gradual policy changes unfolding over extended periods. One strategy of gradual change is layering, in which new policy dimensions are introduced by adding new policy instruments or by redesigning existing ones to address new concerns. The limited research on single-stage policy reforms highlights that these may not endure in the postenactment phase when circumstances change. We argue that gradual policy layering may create sustainability dynamics that can result in lasting reform trajectories. The European Union’s Common Agricultural Policy (CAP) has changed substantially over the last three decades in response to emerging policy concerns by adding new layers. This succession of reforms proved durable and resilient to reversal in the lead-up to the 2013 CAP reform when institutional and political circumstances changed.

Don’t aim too high for your kids: parental over-aspiration undermines students’ learning in mathematics

Previous research has suggested that parents’ aspirations for their children’s academic attainment can have a positive influence on children’s actual academic performance. Possible negative effects of parental over-aspiration, however, have found little attention in the psychological literature. Employing a dual-change score model with longitudinal data from a representative sample of German schoolchildren and their parents (N = 3,530; grades 5 to 10), we showed that parental aspiration and children’s mathematical achievement were linked by positive reciprocal relations over time. Importantly, we also found that parental aspiration that exceeded their expectation (i.e., over-aspiration) had negative reciprocal relations with children’s mathematical achievement. These results were fairly robust after controlling for a variety of demographic and cognitive variables such as children’s gender, age, intelligence, school type, and family SES. The results were also replicated with an independent sample of US parents and their children. These findings suggest that unrealistically high parental aspiration can be detrimental for children’s achievement.

Heathland restoration on former agricultural land: effects of artificial acidification on the availability and uptake of toxic metal cations

Lowland heath is an internationally important habitat type that has greatly declined in abundance throughout Western Europe. In recent years this has led to a growing interest in the restoration of heathland on agricultural land. This generally requires the use of chemical treatments to return soil chemical conditions to those appropriate for the support of heathland ecosystems. However, the potential for negative impacts on the environment due to the potential of these treatments to increase the availability of trace metals via raised soil acidity requires investigation. A large-scale field study investigated the effect of two chemical treatments used in heathland restoration, elemental sulphur and ferrous sulphate, on soil acidity and whether it is possible to predict the effect of the treatments on availability of two potentially toxic cations (Al and Cd) in the soil along with their subsequent accumulation in the shoots of the grass Agrostis capillaris. Results showed that both treatments decreased soil pH, but that only elemental sulphur produced a pH similar to heathland soil. The availability of Al, measured by extraction with 1 M ammonium nitrate, could not be predicted by soil pH, depth in the soil and total Al concentration in the soil. By contrast, availability of Cd could be predicted from these three variables. Concentrations of both Al and Cd in the shoots of A. capillaris showed no significant relationship with the extractable concentration in the soil. Results are discussed in light of the possible environmental impacts of the chemical restoration techniques.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.