313 – Joining the dots versus growing the blobs

For the recent AARES conference in Adelaide, Maksym Polyakov did a wonderfully creative poster presenting our research on optimal targeting of ecological restoration.

There is a small image of the poster below, but if you want to see the details, go here. (Scroll down when you get there to see the poster.)

Not surprisingly, it won the prize for the best poster at the conference.

Abstract

The primary causes of biodiversity decline worldwide are habitat destruction, alteration and fragmentation resulting from human economic activities such as agriculture or property development. Public- and private-sector organizations allocate considerable resources to slow down biodiversity decline by developing conservation networks that preserve the remaining habitat. In this study we use simulation to compare several strategies to spatially target ecological restoration effort to create conservation networks, on private lands in a fragmented agricultural landscape. The evaluated targeting strategies are aggregation, connectivity and representativeness. The effectiveness of these targeting strategies is compared to the effectiveness of ecological restoration without targeting. We allow for heterogeneity of landowners’ willingness to participate in restoration projects and explicitly assume that that not all parcels within target areas will be restored. We model the probability of participation in restoration projects as a function of the private benefits of ecological restoration captured by the landowner. The results of the simulation are analyzed using regression analysis. Our results suggest that effectiveness of the targeting strategies depends on landscape characteristics (level of fragmentation) and species characteristics (habitat requirements and area of home range). On average, when uncertainty about whether landowners will participate is considered, for most analyzed species, the aggregation strategy outperforms the connectivity strategy with the representativeness strategy performing worst. This is contrary to the findings of previous studies and Government policy, that connectivity is the most effective strategy in fragmented landscapes. Accounting for the landowners’ behavior through a private benefits function improves the biodiversity outcome for most species.

312 – The economics of nitrogen in agriculture

The global challenge of feeding seven billion people would be more difficult without nitrogen fertilizer, but it causes pollution of rivers, lakes and coastal waters around the world, and it contributes to emissions of greenhouse gases. It increases the profitability of individual farmers, but it is over-applied in many cases, wasting money and needlessly worsening environmental problems.

These are, in large part, economic issues. In a recent paper I attempted to summarise the large and diverse research literatures on the economics of nitrogen in agriculture. Here are some of the key points.

At the farm level

The production function for nitrogen (N) fertilizer (the relationship between yield and the rate of nitrogen fertilizer) always exhibits diminishing marginal returns – it flattens out at higher fertilizer rates. In dry conditions, yield may even fall at high N rates.

The rate of nitrogen fertilizer that maximises expected profit is less than the rate that maximises expected yield, sometimes much less.

Here’s a really neat tool that shows the relationships between N, yield and profit for corn in the US. http://cnrc.agron.iastate.edu/

Visual effect of nitrogen fertilizer on corn

Risk

N fertilizer affects the riskiness of cropping. For two reasons, higher N rates are more risky (i.e. profits are more variable at higher N rates). One reason is that the grain price is itself risky. Since profit depends on grain price times yield, and yield usually increases with increasing N rate, the more N you apply, the more variable your profit will be. In addition, yield also tends to be slightly more variable at higher N rates.

Flat payoff functions

There always exists a range of fertilizer rates that are only slightly less profitable than the profit-maximising rate (i.e. a range where the payoff function is relatively flat), and in most cases, that flat range is wide. This means that the farmer has flexibility in choosing the fertilizer rate. If a lower rate would better satisfy another objective (e.g. risk reduction), the farmer can choose that rate with little sacrifice of profit. If regulators require a moderate reduction in fertilizer rate below the farmer’s economic optimum, the cost to the farmer will be small. Flat payoff functions also mean that the benefits of precision-agriculture technologies that spatially adjust fertilizer rates within a field will usually be small.

Nitrogen pollution

Typically, the marginal cost to farmers of nitrogen emissions abatement is low for low levels of abatement but increases at an increasing rate as the required level of abatement increases. As a result, modest targets for abatement can often be achieved at low cost, but ambitious targets can be extremely costly.

Spatial targeting of abatement effort (both at the regional and international scales) can generate much larger benefits than untargeted policies, although these additional benefits are likely to be offset to some degree by increased costs required to run a targeted program (costs of information and administration).

Policies intended to increase farmers’ incomes can have the unintended consequence of increasing nitrogen pollution by increasing the incentive to apply fertilizer.

Further reading

Pannell, D.J. (2017). Economic perspectives on nitrogen in farming systems: managing trade-offs between production, risk and the environment, Soil Research 55, 473-478. Journal web page

Gandorfer, M., Pannell, D.J. and Meyer-Aurich, A. (2011). Analyzing the Effects of Risk and Uncertainty on Optimal Tillage and Nitrogen Fertilizer Intensity for field crops in Germany, Agricultural Systems 104(8), 615-622. Journal web page ♦ IDEAS page

Schilizzi, S. and Pannell, D.J. (2001). The economics of nitrogen fixation, Agronomie 21(6/7), 527-538.

Pannell, D.J. and Falconer, D.A. (1988). The relative contributions to profit of fixed and applied nitrogen in a crop‑livestock farm system, Agricultural Systems 26(1), 1‑17. Journal web page ♦ IDEAS page

Pannell, D.J. (2006). Flat-earth economics: The far-reaching consequences of flat payoff functions in economic decision making, Review of Agricultural Economics 28(4), 553-566. Journal web page ♦ IDEAS page