Even Tjørve

How to resolve the SLOSS debate: lessons from species-diversity models.

The SLOSS debate--whether a single large reserve will conserve more species than several small--of the 1970s and 1980s never came to a resolution. The first rule of reserve design states that one large reserve will conserve the most species, a rule which has been heavily contested. Empirical data seem to undermine the reliance on general rules, indicating that the best strategy varies from case to case. Modeling has also been deployed in this debate. We may divide the modeling approaches to the SLOSS enigma into dynamic and static approaches. Dynamic approaches, covered by the fields of island equilibrium theory of island biogeography and metapopulation theory, look at immigration, emigration, and extinction. Static approaches, such as the one in this paper, illustrate how several factors affect the number of reserves that will save the most species. This article approaches the effect of different factors by the application of species-diversity models. These models combine species-area curves for two or more reserves, correcting for the species overlap between them. Such models generate several predictions on how different factors affect the optimal number of reserves. The main predictions are: Fewer and larger reserves are favored by increased species overlap between reserves, by faster growth in number of species with reserve area increase, by higher minimum-area requirements, by spatial aggregation and by uneven species abundances. The effect of increased distance between smaller reserves depends on the two counteracting factors: decreased species density caused by isolation (which enhances minimum-area effect) and decreased overlap between isolates. The first decreases the optimal number of reserves; the second increases the optimal number. The effect of total reserve-system area depends both on the shape of the species-area curve and on whether overlap between reserves changes with scale. The approach to modeling presented here has several implications for conservational strategies. It illustrates well how the SLOSS enigma can be reduced to a question of the shape of the species-area curve that is expected or generated from reserves of different sizes and a question of overlap between isolates (or reserves).

THE SPECIES–AREA RELATIONSHIP, SELF‐SIMILARITY, AND THE TRUE MEANING OF THE z‐VALUE

The power model, S= cA(z) (where S is number of species, A is area, and c and z are fitted constants), is the model most commonly fitted to species-area data assessing species diversity. We use the self-similarity properties of this model to reveal patterns implicated by the z parameter. We present the basic arithmetic leading both to the fraction of new species added when two areas are combined and to species overlap between two areas of the same size, given a continuous sampling scheme. The fraction of new species resulting from expansion of an area can be expressed as alpha(z)-1, where alpha is the expansion factor. Consequently, z-values can be converted to a scale-invariant species overlap between two equally sized areas, since the proportion of species in common between the two areas is 2-2(z). Calculating overlap when adding areas of the same size reveals the intrinsic effect of distance assumed by the bisectional scheme. We use overlap area relationships from empirical data sets to illustrate how answers to the single large or several small reserves (SLOSS) question vary between data sets and with scale. We conclude that species overlap and the effect of distance between sample areas or isolates should be addressed when discussing species area relationships, and lack of fit to the power model can be caused by its assumption of a scale-invariant overlap relationship.

Shapes and functions of bird-growth models: how to characterise chick postnatal growth

We compare four candidate models (logistic, Gompertz, von Bertalanffy, and extreme value function) for modelling the growth of birds. We fitted the models to two empirical data sets of chick growth (six biometric measurements) of African black oystercatchers Haematopus moquini from South Africa and little stints Calidris minuta from Russia, and identified the best-fitting growth curves by Akaikes information criterion. We also determine fitted and derived parameters, including the relative value (size) at hatching, the placement of inflection, the (normalised) growth rate constant, and the adult value (upper asymptote). The preferred model together with these factors describes how fast (or abruptly) the curves asymptote, and illustrates why growth is poorly characterised by the growth rate constant alone. Though the extreme value function model has not (as far as we know) been applied to chick growth data before, it appears to return the best fit for some parameters in our data sets. For example, we found that in African black oystercatchers two very different models best characterise two of the measurements: the extreme value function model and the Bertalanffy model for tarsus growth and body mass growth, respectively. In addition, we discuss the usefulness of fixing the upper asymptote to the adult value (e.g., adult body mass) and recommend a fixed upper asymptote in most cases.

The effects of distance and belonging on second-home markets.

Abstract This article discusses the effect of distance between markets and second-home areas in a mountain region and how peoples preferences are modified by the degree of belonging or attachment to the area of their second home, expressed as former or present ties. A second-home market is here defined as a cluster of permanent residences of second-home owners and is identified by the application of the kernel-density method, which to our knowledge is new to tourism research. We used data from two postal surveys of owners of second homes in two mountain locations in southern Norway. We have concluded that average travel distance would not be a good measure of peoples preferences, partly because the decay of local markets reduces the observed distances between permanent addresses and second homes, and partly because people with any belonging to the second-home areas are less sensitive to distance or travel time. Consequently, the distances between markets and second-home areas are expected to deviate from those predicted from distance-decay models, which predict a rapid decay with distances beyond the weekend zone. Instead, where a high number of owners with a sense of belonging were found, distances were not heavily restricted to the weekend zone. This pattern, with large distances between an urban market and a second-home area, seems to persist across generations and is comprised mostly of owners of traditional, low-standard second homes. For urban owners with no belonging, however, the absolute distance to markets certainly has become increasingly important, despite higher mobility and generally shorter travel times, and this has restricted ownership to the weekend zone. These owners typically prefer modern, high-standard second homes.

The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family

The Gompertz model is well known and widely used in many aspects of biology. It has been frequently used to describe the growth of animals and plants, as well as the number or volume of bacteria and cancer cells. Numerous parametrisations and re-parametrisations of varying usefulness are found in the literature, whereof the Gompertz-Laird is one of the more commonly used. Here, we review, present, and discuss the many re-parametrisations and some parameterisations of the Gompertz model, which we divide into Ti (type I)- and W0 (type II)-forms. In the W0-form a starting-point parameter, meaning birth or hatching value (W0), replaces the inflection-time parameter (Ti). We also propose new “unified” versions (U-versions) of both the traditional Ti -form and a simplified W0-form. In these, the growth-rate constant represents the relative growth rate instead of merely an unspecified growth coefficient. We also present U-versions where the growth-rate parameters return absolute growth rate (instead of relative). The new U-Gompertz models are special cases of the Unified-Richards (U-Richards) model and thus belong to the Richards family of U-models. As U-models, they have a set of parameters, which are comparable across models in the family, without conversion equations. The improvements are simple, and may seem trivial, but are of great importance to those who study organismal growth, as the two new U-Gompertz forms give easy and fast access to all shape parameters needed for describing most types of growth following the shape of the Gompertz model.

Properties of first-time vs. repeat visitors: lessons for marketing Norwegian ski resorts

This paper explores the potential in foreign markets for winter tourism in Norway and discusses the influencing factors explaining why foreign tourists visit and revisit Norway on ski vacations. In a decreasing market, it becomes increasingly important to destination managers and marketers to choose the right marketing strategies and direction. We focus on characteristics that influence and explain why foreign tourists choose to return. More than 3000 respondents from Sweden, Denmark, and Germany were asked for their image of Norwegian ski destinations and criteria for winter vacation selection. We fitted mainly hurdle and quantile regressions to gain consistent and less biased estimates. Stable snow conditions, combining alpine and cross-country skiing, and no fees for the latter are some of Norways competitive but seldom marketed advantages, and especially towards repeat visitors. Repeaters typically prefer self-catering accommodation and are less price sensitive. Surprisingly, foreign ski tourists are not very interested in other snow-based activities or cultural attractions. Despite repeaters constituting the majority of foreign ski tourists, neither the national development and marketing agency (Innovation Norway) nor local tourist organizations and marketers have a strategy for targeting them. We recommend a shift from profile marketing towards segmented marketing, aimed especially at the repeat-visitor segment.

The Shift from Hotels and Lodges to Second-Home Villages in Mountain-Resort Accommodation

Abstract The importance of second-home villages compared with the traditional accommodation industry has been seldom studied and is not well understood. A common belief is that the hotels constitute the gravitational point of the ski resort. Yet both data and general observation suggest that this orthodoxy has ceased to reflect the changes that have occurred over the last couple of decades. We are thus able to conclude that the second-home villages have become the new economic gravitational point of Norwegian winter-tourism resorts, and both the trade and the politicians need to act accordingly. The traditional accommodation providers now face increasing challenges. These providers could choose to stay in their traditional but decreasing markets by lowering their prices, reducing the number of commercial beds, and becoming active providers of food and beverages to the second-home dweller. Or they could close down completely and sell off to estate developers who will convert hotels or lodges into apartments for the second-home market. The continuing focus on how to save the traditional accommodation industry, which has lost its customers to the second-home market, is misguided. Instead a strategy is needed to nurture and develop the opportunities created by the rapid development of the second-home villages.

How to allow SAR collapse across local and continental scales: a resolution of the controversy between Storch et al. (2012) and Lazarina et al. (2013)

Up-scaling species richness from local to continental scales is an unsolved problem of macroecology. Macroecologists hope that proper up-scaling can uncover the hidden rules that underlie spatial patterns in species richness, but a machinery to up-scale species richness also has a purely practical side at the scales and for the habitats where direct observations cannot be performed. The species–area relationship (SAR) could provide a tool for up-scaling, but no valid method has yet been put forward. Such a method would have resulted from Storch et al.’s (2012) suggestion that there is a universal curve to which each rescaled SAR collapses, if Lazarina et al. (2013) had not shown that it does not: both arguments were supported by data analyses. Here we present an analytical model for mainland SAR and argue in favour of the latter authors. We identify (i) the variation in mean species-range size, (ii) the variation in forces that drive SAR at various scales, and (iii) the finite-area effect, as the reasons for the absence of collapse. Finally, we suggest a rescaling that might fix the problem. We conclude, however, that ecologists are still far from finding a practical, robust and easy-to-use solution for up-scaling species richness from SARs.