Causes of the apparent scale independence of fractal indices associated with forest fragmentation in Bolivia

In a recent investigation, Landsat TM and ETM+ data were used to simulate different resolutions of remotely-sensed images (from 30 to 1100 m) and to analyze the effect of resolution on a range of landscape metrics associated with spatial patterns of forest fragmentation in Chapare, Bolivia since the mid-1980s. Whereas most metrics were found to be highly dependent on pixel size, several fractal metrics (DLFD, MPFD, and AWMPFD) were apparently independent of image resolution, in contradiction with a sizeable body of literature indicating that fractal dimensions of natural objects depend strongly on image characteristics. The present re-analysis of the Chapare images, using two alternative algorithms routinely used for the evaluation of fractal dimensions, shows that the values of the box-counting and information fractal dimensions are systematically larger, sometimes by as much as 85%, than the "fractal" indices DLFD, MPFD, and AWMFD for the same images. In addition, the geometrical fractal features of the forest and non-forest patches in the Chapare region strongly depend on the resolution of images used in the analysis. The largest dependency on resolution occurs for the box-counting fractal dimension in the case of the non-forest patches in 1993, where the difference between the 30 and I 100 m-resolution images corresponds to 24% of the full theoretical range (1.0 to 2.0) of the mass fractal dimension. The observation that the indices DLFD, MPFD, and AWMPFD, unlike the classical fractal dimensions, appear relatively unaffected by resolution in the case of the Chapare images seems due essentially to the fact that these indices are based on a heuristic, "non-geometric" approach to fractals. Because of their lack of a foundation in fractal geometry, nothing guarantees that these indices will be resolution-independent in general. (C) 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

On the use of headline indices to link environmental quality and income at the level of the nation state

This paper deconstructs the relationship between the Environmental Sustainability Index (ESI) and national income. The ESI attempts to provide a single figure which encapsulates environmental sustainability' for each country included in the analysis, and this allied with a 'league table' format so as to name and shame bad performers, has resulted in widespread reporting within the popular presses of a number of countries. In essence, the higher the value of the ESI then the more 'environmentally sustainable' a country is deemed to be. A logical progression beyond the use of the ESI to publicise environmental sustainability is its use within a more analytical context. Thus an index designed to simplify in order to have an impact on policy is used to try and understand causes of good and bad performance in environmental sustainability. For example the creators of the ESI claim that ESI is related to GDP/capita (adjusted for Purchasing Power Parity) such that the ESI increases linearly with wealth. While this may in a sense be a comforting picture, do the variables within the ESI allow for alternatives to the story, and if they do then what are the repercussions for those producing such indices for broad consumption amongst the policy makers, mangers, the press, etc.? The latter point is especially important given the appetite for such indices amongst non-specialists, and for all their weaknesses the ESI and other such aggregated indices will not go away. (C) 2007 Elsevier Ltd. All rights reserved.

Making 'dirty' nations look clean? The nation state and the problem of selecting and weighting indices as tools for measuring progress towards sustainability

Pressing global environmental problems highlight the need to develop tools to measure progress towards "sustainability." However, some argue that any such attempt inevitably reflects the views of those creating such tools and only produce highly contested notions of "reality." To explore this tension, we critically assesses the Environmental Sustainability Index (ESI), a well-publicized product of the World Economic Forum that is designed to measure 'sustainability' by ranking nations on league tables based on extensive databases of environmental indicators. By recreating this index, and then using statistical tools (principal components analysis) to test relations between various components of the index, we challenge ways in which countries are ranked in the ESI. Based on this analysis, we suggest (1) that the approach taken to aggregate, interpret and present the ESI creates a misleading impression that Western countries are more sustainable than the developing world; (2) that unaccounted methodological biases allowed the authors of the ESI to over-generalize the relative 'sustainability' of different countries; and, (3) that this has resulted in simplistic conclusions on the relation between economic growth and environmental sustainability. This criticism should not be interpreted as a call for the abandonment of efforts to create standardized comparable data. Instead, this paper proposes that indicator selection and data collection should draw on a range of voices, including local stakeholders as well as international experts. We also propose that aggregating data into final league ranking tables is too prone to error and creates the illusion of absolute and categorical interpretations. (c) 2004 Elsevier Ltd. All rights reserved.

The use of bootstrapped Malmquist indices to reassess productivity change findings: an application to a sample of Polish farms

This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

Productivity change in Polish agriculture: an illustration of a bootstrapping procedure applied to Malmquist indices

This article illustrates the usefulness of applying bootstrap procedures to total factor productivity Malmquist indices, derived with data envelopment analysis (DEA), for a sample of 250 Polish farms during 1996-2000. The confidence intervals constructed as in Simar and Wilson suggest that the common portrayal of productivity decline in Polish agriculture may be misleading. However, a cluster analysis based on bootstrap confidence intervals reveals that important policy conclusions can be drawn regarding productivity enhancement.

Winter wheat in England and Wales, 1923 - 1995: What do indices of genetic diversity reveal?

Genealogical data have been used very widely to construct indices with which to examine the contribution of plant breeding programmes to the maintenance and enhancement of genetic resources. In this paper we use such indices to examine changes in the genetic diversity of the winter wheat crop in England and Wales between 1923 and 1995. We find that, except for one period characterized by the dominance of imported varieties, the genetic diversity of the winter wheat crop has been remarkably stable. This agrees with many studies of plant breeding programmes elsewhere. However, underlying the stability of the winter wheat crop is accelerating varietal turnover without any significant diversification of the genetic resources used. Moreover, the changes we observe are more directly attributable to changes in the varietal shares of the area under winter wheat than to the genealogical relationship between the varieties sown. We argue, therefore, that while genealogical indices reflect how well plant breeders have retained and exploited the resources with which they started, these indices suffer from a critical limitation. They do not reflect the proportion of the available range of genetic resources which has been effectively utilized in the breeding programme: complex crosses of a given set of varieties can yield high indices, and yet disguise the loss (or non-utilization) of a large proportion of the available genetic diversity.

Assessment of projected changes in upland environments using simple climatic indices

Climate controls upland habitats, soils and their associated ecosystem services; therefore, understanding possible changes in upland climatic conditions can provide a rapid assessment of climatic vulnerability over the next century. We used 3 different climatic indices that were optimised to fit the upland area classified by the EU as a Severely Disadvantaged Area (SDA) 1961–1990. Upland areas within the SDA covered all altitudinal ranges, whereas the maximum altitude of lowland areas outside of the SDA was ca. 300 m. In general, the climatic index based on the ratio between annual accumulated temperature (as a measure of growing season length) and annual precipitation predicted 96% of the SDA mapped area, which was slightly better than those indices based on annual or seasonal water deficit. Overall, all climatic indices showed that upland environments were exposed to some degree of change by 2071–2100 under UKCIP02 climate projections for high and low emissions scenarios. The projected area declined by 13 to 51% across 3 indices for the low emissions scenario and by 24 to 84% for the high emissions scenario. Mean altitude of the upland area increased by +11 to +86 m for the low scenario and +21 to +178 m for the high scenario. Low altitude areas in eastern and southern Great Britain were most vulnerable to change. These projected climatic changes are likely to affect upland habitat composition, long-term soil carbon storage and wider ecosystem service provision, although it is not yet possible to determine the rate at which this might occur.

On-line prediction of cheese making using backscatter of near infrared indices light

The potential of a fibre optic sensor, detecting light backscatter in a cheese vat during coagulation and syneresis, to predict curd moisture, fat loses and curd yield was examined. Temperature, cutting time and calcium levels were varied to assess the strength of the predictions over a range of processing conditions. Equations were developed using a combination of independent variables, milk compositional and light backscatter parameters. Fat losses, curd yield and curd moisture content were predicted with a standard error of prediction (SEP) of +/- 2.65 g 100 g(-1) (R-2 = 0.93), +/- 0.95% (R-2 = 0.90) and +/- 1.43% (R-2 = 0.94), respectively. These results were used to develop a model for predicting curd moisture as a function of time during syneresis (SEP = +/- 1.72%; R-2 = 0.95). By monitoring coagulation and syneresis, this sensor technology could be employed to control curd moisture content, thereby improving process control during cheese manufacture. (c) 2007 Elsevier Ltd. All rights reserved..

Influence of curd cutting programme and stirring speed on the prediction of syneresis indices in cheese-making using NIR light backscatter

An NIR reflectance sensor, with a large field of view and a fibre-optic connection to a spectrometer for measuring light backscatter at 980 nm, was used to monitor the syneresis process online during cheese-making with the goal of predicting syneresis indices (curd moisture content, yield of whey and fat losses to whey) over a range of curd cutting programmes and stirring speeds. A series of trials were carried out in an 11 L cheese vat using recombined whole milk. A factorial experimental design consisting of three curd stirring speeds and three cutting programmes, was undertaken. Milk was coagulated under constant conditions and the casein gel was cut when the elastic modulus reached 35 Pa. Among the syneresis indices investigated, the most accurate and most parsimonious multivariate model developed was for predicting yield of whey involving three terms, namely light backscatter, milk fat content and cutting intensity (R2 = 0.83, SEy = 6.13 g/100 g), while the best simple model also predicted this syneresis index using the light backscatter alone (R2 = 0.80, SEy = 6.53 g/100 g). In this model the main predictor was the light backscatter response from the NIR light back scatter sensor. The sensor also predicted curd moisture with a similar accuracy.