Recovery of damaged ecosystems

From open access journal PLOS One this study on the ability of ecosystems to recover after major perturbations:

Rapid Recovery of Damaged Ecosystems

Background

Recent reports on the state of the global environment provide evidence that humankind is inflicting great damage to the very ecosystems that support human livelihoods. The reports further predict that ecosystems will take centuries to recover from damages if they recover at all. Accordingly, there is despair that we are passing on a legacy of irreparable damage to future generations which is entirely inconsistent with principles of sustainability.

Methodology/Principal Findings

We tested the prediction of irreparable harm using a synthesis of recovery times compiled from 240 independent studies reported in the scientific literature. We provide startling evidence that most ecosystems globally can, given human will, recover from very major perturbations on timescales of decades to half-centuries.

Significance/Conclusions

Accordingly, we find much hope that humankind can transition to more sustainable use of ecosystems.

Citation: Jones HP, Schmitz OJ (2009) Rapid Recovery of Damaged Ecosystems. PLoS ONE 4(5): e5653. doi:10.1371/journal.pone.0005653

Population growth rates per country

From the encyclopedia of earth figures on the latest population growth rates per country.

South Africa? 0.28%!

Fertility rate for South Africa is 2.43 births per women, just above the global replacement fertility rate of 2.33 children per women, and possibly well below the replacement fertility rate for a developing country such as South Africa burdened with high premature mortalities.

What are the implications? Medium to longer term population decline and serious questions whether a declining population can maintain the economic system. This is essence is not good news for South Africa's extensive social welfare system as well as the sustained flow of future pension payments.

Time for national policies to reverse declining populations? In the local context, that will be an interesting environment - social welfare debate.

Natural resource amenity and life expectancy

Better natural resource amenities increase life expectancy. That makes it a issue worthwhile of public health investment. Do not believe me? Well, here is a paper arguing just that (at least based on county level data in (I assume) the US):

Evaluating natural resource amenities in a human life expectancy production function

This study examined the effect of natural resource amenities on human life expectancy. Extending the existing model of the life expectancy production function, and correcting for spatial dependence, we evaluated the determinants of life expectancy using county level data. Results indicate that after controlling for socio-demographic and economic factors, medical facilities and risk factors, counties with natural amenities such as high proportion of land in forests, farmland, rangeland and water bodies, as well as mild climate such as longer sunlight hours during winter and cooler year around temperature exhibited longer life expectancies at birth. In addition, counties containing state parks and outdoor recreation facilities, and those located near federal wilderness parks were associated with the longer expectancies at birth. Findings from this study have several implications for natural resource economics and management, public health, and human development. An important message of our findings is that the traditional approach of public health should be extended beyond just controlling diseases or treating patients to a more comprehensive approach that also acknowledges the preservation and utilization of natural resources, environmental amenities, and outdoor recreation opportunities in maintaining public health, quality of life, and overall human development.

Keywords: Life expectancy; Natural resource amenities; Spatial error model; Production function; Public health

 

ERE conference Cape Town

For the first time in almost a decade South Africa had its own Environmental & Resource Economics conference. 

I scribbled down a few notes:

1. Sometimes one needs to speak a hard language to reach soft targets. Speaking in terms of rands and cents can help achieve objectives of care and justice. Economics can be used for the good. It is not only a throwing of "the bones". Really.

2. The narrative to see the environment as a provider of goods and services in support of human well-being is well-entrenched. 

3. Watch those numbers! Flow values, stock values, net present values, discounted values, operational costs etc etc. Always compare apples with apples.

4. Seems like we need a fresh injection of institutional economics to support an analysis on the creation of viable institutions that can support the development of markets in ecosystems services. 

5. The transition from no markets to full PES markets rises many questions on the speed, timing and focus of market reform.  There should be some good learning somewhere in the historical development of financial markets and the transition from communism to market-economies.

6. Talking about payments for ecosystems services (PES); it is not a macro-developmental concept yet, but the signs are encouraging.  With still comparable low values to water and carbon services generated in rural areas, volumes and scale factors remain crucial for success.

7. Be cautious on how much PES at the end will help the rural poor. Do not oversell. Power traps can be deeply entrenched.

8. With increased scarcity of ecosystems good and services, investment in understanding how the "ecosystem supply factory" is working makes sense. More integrated socio-ecological systems modelling.

9. ERE operates in context. Valuation is a means to and end. Economic analysis and modelling is one input to the decision-making process. Invest in understanding where this can achieve the highest leverage.

It was a great event.

 

Biodiversity conservation values and income

A new paper Are There Income Effects on Global Willingness to Pay for Biodiversity Conservation? by Jette Bredahl Jacobsen and Nick Hanley sheds some light on the question how biodiversity conservation values are related to income:

Abstract  This paper is concerned with the empirical relationship between biodiversity conservation values and income. We use random effects panel models to examine the effects of income, and then GDP per capita, on willingness to pay for habitat and biodiversity conservation. In a meta-analysis, 145 Willingness To Pay estimates for biodiversity conservation where existence value plays a major role were collected from 46 contingent valuation studies across six continents. Other effects included in the meta-analysis were the study year; habitat type; continent; scope as presented to respondents; whether WTP bids were for preventing a deterioration or gaining an improvement in conservation, whether a specific species or specific habitat was protected; whether the questionnaire used a dichotomous choice or an open-ended format; distribution format; and the choice of payment vehicle. GDP per capita seemed to perform as well as an explanatory variable as respondent’s mean stated income, indicating that it is wealth in society as a whole which determines variations in WTP. Even if large variation, our main conclusion is, that the demand for biodiversity conservation rises with a nation’s wealth, but the income elasticity of willingness to pay is less than one.

Why scientists and decision makers need intermediaries

From my ScienceDirect feeds this morning:

Fuzzy Adaptive Decision-making for Boundedly Rational Traders in Speculative Stock Markets

The development of new models that would enhance predictability for time series with dynamic time-varying, nonlinear features is a major challenge for speculators. Boundedly rational investors called “chartists” use advanced heuristics and rules-of-thumb to make profit by trading, or even hedge against potential market risks. This paper introduces a hybrid neurofuzzy system for decision-making and trading under uncertainty. The efficiency of a technical trading strategy based on the neurofuzzy model is investigated, in order to predict the direction of the market for 10 of the most prominent stock indices of U.S.A, Europe and Southeast Asia. It is demonstrated via an extensive empirical analysis that the neurofuzzy model allows technical analysts to earn significantly higher returns by providing valid information for a potential turning point on the next trading day. The total profit of the proposed neurofuzzy model, including transaction costs, is consistently superior to a recurrent neural network and a Buy & Hold strategy for all indices, particularly for the highly speculative, emerging Southeast Asian markets. Optimal prediction is based on the dynamic update and adaptive calibration of the heuristic fuzzy learning rules, which reflect the psychological and behavioral patterns of the traders.

An efficient heuristic for reliability design optimization problems

This paper develops an efficient heuristic to solve two typical combinatorial optimization problems frequently met when designing highly reliable systems. The first one is the redundancy allocation problem (RAP) of series-parallel binary-state systems. The design goal of the RAP is to select the optimal combination of elements and redundancy levels to maximize system reliability subject to the system budget and to the system weight. The second problem is the expansion-scheduling problem (ESP) of multi-state series-parallel systems. In this problem, the study period is divided into several stages. At each stage, the demand is represented as a piecewise cumulative load curve. During the system lifetime, the demand can increase and the total productivity may become insufficient to assume the demand. To increase the total system productivity, elements are added to the existing system. The objective in the ESP is to minimize the sum of costs of the investments over the study period while satisfying availability constraints at each stage. The heuristic approach developed to solve the RAP and the ESP is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. Numerical results for the test problems from previous research are reported and compared. The results show the advantages of the proposed approach for solving both problems.

Exploiting human fear

I am reading Dan Gartner's book Risk. The Science and Politics of Fear. This books contains fantastic observations on humankind's inability to fully comprehend and understand the risks we face. One aspect that really attracted my attention is the observation that the "marketing of fear" is not something only for marketing types. Scientists are also affected. Quoting from p180: 

The competing demands of being accurate and being heard can be particularly hard on scientists. Quoting Stephan Schneider: On the one hand, as scientists we are ethically bound to the scientific method, in effect promising to tell the truth, the whole truth and nothing but, - which means that we must include all the doubts, the caveats, the ifs, ands and buts. On the other hand, we are not just scientists, but human beings as well. And like most people we'd like to see the world a better place... To do that we need to get some broad-based support, to capture the public's imagination. That, of course, means getting loads of media coverage. So we have to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts we may have.

Explains a lot of scary headlines these days.