NUTGRANJA 2.0: a simple mass balance model to explore the effects of different management strategies on nitrogen and greenhouse gases losses and soil phosphorus changes in dairy farms

Farm nutrient management has been identified as one of the most important factors determining the economic and environmental performance of dairy cattle (Bos taurus) farming systems. Given the environmental problems associated with dairy farms, such as emissions of greenhouse gases (GHG), and the complex interaction between farm management, environment and genetics, there is a need to develop robust tools which enable scientists and policy makers to study all these interactions. This paper describes the development of a simple model called NUTGRANJA 2.0 to evaluate GHG emissions and nitrogen (N) and phosphorus (P) losses from dairy farms. NUTGRANJA 2.0 is an empirical mass-balance model developed in order to simulate the main transfers and flows of N and P through the different stages of the dairy farm management. A model sensitivity test was carried out to explore some of the sensitivities of the model in relation to the simulation of GHG and N emissions. This test indicated that both management (e.g. milk yield per cow, annual fertiliser N rate) and site-specific factors (e.g. % clover (Trifolium) in the sward, soil type, and % land slope) had a large effect on most of the model state variables studied (e.g. GHG and N losses).     

The adaptive capacity of institutions in the spatial planning,water, agriculture and nature sectors in the Netherlands

The climate change problem calls for a continuously responding society. This raises the question: Do our institutions allow and encourage society to continuously adapt to climate change? This paper uses the Adaptive Capacity Wheel (ACW) to assess the adaptive capacity of formal and informal institutions in four sectors in the Netherlands: spatial planning, water, agriculture and nature. Formal institutions are examined through an assessment of 11 key policy documents and informal institutions are analysed through four case studies covering each sector. Based on these ACW analyses, both sector-specific and more general strengths and weaknesses of the adaptive capacity of institutions in the Netherlands are identified. The paper concludes that the most important challenge for increasing institutional adaptive capacity lies in combining decentralized, participatory approaches with more top-down methods that generate leadership (visions, goals) standards, instruments, resources and monitoring.     

Exploring the association between working memory and driving performance in Parkinson's disease

Objective: The aim of this study was to explore whether varying levels of operational and tactical driving task demand differentially affect drivers with Parkinson's disease (PD) and control drivers in their sign recall.

Methods: Study participants aged between 50 and 70 years included a group of drivers with PD (n = 10) and a group of age- and sex-matched control drivers (n = 10). Their performance in a sign recall task was measured using a driving simulator.

Results: Drivers in the control group performed better than drivers with PD in a sign recall task, but this trend was not statistically significant (P =.43). In addition, regardless of group membership, subjects' performance differed according to varying levels of task demand. Performance in the sign recall task was more likely to drop with increasing task demand (P =.03). This difference was significant when the variation in task demand was associated with a cognitive task; that is, when drivers were required to apply the instructions from working memory.

Conclusions: Although the conclusions drawn from this study are tentative, the evidence presented here is encouraging with regard to the use of a driving simulator to examine isolated cognitive functions underlying driving performance in PD. With an understanding of its limitations, such driving simulation in combination with functional assessment batteries measuring physical, visual, and cognitive abilities could comprise one component of a multitiered system to evaluate medical fitness to drive.     

Maximizing Returns from Payments for Water‐Based Ecosystem Services: Incorporating Externality Effects of Land Management

Given the expansion of payments for water‐based ecosystem services (PWES) worldwide, two relevant issues are as follows: (1) determination of efficient allocations of payments among land managers, and (2) how this might change when paying one manager to implement a best management practice (BMP) to enhance an ecosystem service impacts the cost‐effectiveness of BMPs considered by other land managers not currently involved in PWES. Such externalities may be negative if diminishing returns dominate, or positive if mechanisms such as “social diffusion” dominate. We analyze how a planner should optimally allocate payments, depending on whether the expected externalities are negligible, negative, or positive. We employ (1) an optimal control model to gain insights on the problem’s dynamics, and (2) stochastic dynamic programming to determine optimal funding strategies using a specific application. The study contributes to the literature by identifying dynamically optimal PWES payment patterns, and illustrates how they should change when one accounts for externalities induced by the program. Because such impacts have not been addressed previously in a rigorous way, this treatment provides useful value added for PWES design and implementation.     

Runoff Storage Potential of Drained Upland Depressions on the Des Moines Lobe of Iowa

We present estimates of the volumetric storage capacities of currently drained upland depressions and catchment depressional specific storage and runoff storage indices for the Des Moines Lobe of Iowa (DML‐IA) subregion of the Prairie Pothole Region of North America. Storage capacities were determined using hydrologically enforced Light Detection and Ranging‐derived digital elevation models, and a unique geoprocessing algorithm. Depressional specific storage was estimated for each 12‐digit Hydrologic Unit Code (HUC12) watershed in the region from total catchment‐specific depressional storage volume and catchment area. Runoff storage indices were calculated using catchment depressional specific storage values and estimates of the amount of rainfall likely to fall within each watershed during sub‐annual and 1‐, 2‐, 5‐, and 10‐year 24‐h events. The 173,171 identified drained depressions in the DML‐IA can store up to 903.5 Mm³ of runoff. Most of this capacity is in depressions located in the north of the region. Specific storage varies from nearly 109 mm in the younger landscapes to <10 mm in older more eroded areas. For 95% of the HUC12 watersheds comprising the region, depressional storage will likely be exhausted by rainfall‐derived runoff in excess of a 1‐year 24‐h event. Rainfall amounts greater than a 5‐year 24‐h event will exceed all available depressional storage. Therefore, the capacity of drained depressions in the DML‐IA to mitigate flooding resulting from infrequent, but large, storm events is limited.     

The State of the Mammal Community of Boreal Forest Ecosystems in the Vicinity of a Nickel-Smelting Plant

The effect of industrial air pollution on natural small mammal populations has been studied in the northern taiga subzone of the boreal forest zone. The results of long-term monitoring have been used to demonstrate the possibility of predicting changes in the main population and community characteristics of the animal species studied as dependent on the degree of anthropogenic impact.