Valuing high-seas ecosystem conservation

The high seas provide a variety of ecosystem services that benefit society. There have, however, been few attempts to quantify the human welfare impacts of changes to the delivery of these benefits. We assessed the values of several key ecosystem service benefits derived from protecting ecosystems in the high seas of the Flemish Cap through choice experiments conducted in Canada, Norway, and Scotland. Rather than solely eliciting public willingness to pay, we also explored the determinants of variance in the estimates of willingness to pay. We aimed to determine how much respondents were willing to pay for high-seas ecosystems conservation, which factors influence individuals’ willingness to pay, and whether individuals in Canada had a higher willingness to pay relative to those living in Norway and Scotland. This latter point captures distance-decay effects. On average, the public placed positive value on conserving high-seas ecosystems and on developing economic activities related to the exploitation and exploration of marine resources, despite a lack of awareness and familiarity with these environments. Distance-decay effects on willingness to pay were not clear. Scots had the highest willingness to pay and the Norwegians the lowest willingness to pay for all attributes, with the only exception being willingness to pay for a large increase in new jobs, in which case Canadians’ willingness to pay was higher than Scots’. The public's willingness to pay was influenced by sociodemographic characteristics and their perceptions of high-seas ecosystems. Our results provide evidence of the impacts of high-seas governance on human welfare and that improved governance could increase the value people place on high-seas ecosystems and the services they produce.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Who counts in evaluating the effects of air pollution policies on households? Non-market valuation in the presence of dependencies

Individuals who are likely to realize the largest benefits from improvements in air quality often depend on other members of their households to make time or monetary contributions to their care. The presence of these dependency relationships among household members poses challenges for benefit estimation since it is unlikely that the conditions necessary for recovering the underlying individual preferences from household choices are satisfied in this setting. We propose a conceptual framework that highlights the role of these dependencies in the choice models used to estimate the willingness to pay for environmental quality improvements. We design a complementary stated preference survey that describes hypothetical dependency relationships for household members of different ages to test the implications of our conceptual model. Respondents' stated choices take into account the proposed care-giving responsibilities for young children and teenagers but not for older adults.     

Exurban development

Exurbia, the rural area beyond the built-up urban and contiguous suburban area, is being developed rapidly with attendant losses in habitat and ecosystem services. This paper analyzes a spatial dynamic model with two production technologies for residential development—municipal sewer service for suburban development and septic systems for exurban development. In outlying agricultural areas, the additional sewer extension costs can significantly reduce the value of agricultural land in suburban use. Exurban development, while at lower density, can occur immediately and requires only the onsite conversion costs of septic systems. Hence, the willingness to pay for exurban use from households with higher preferences for lot size may exceed the agricultural landowner's reservation price on future suburban use for a range of distances from the city boundary. This results in a “feasible zone” for exurban leapfrog development and another fundamental reason for scattered development in the urban–rural fringe.     

Demand for environmental policies to improve health: Evaluating community-level policy scenarios

Using a national survey and a discrete choice experiment format, we estimate demand for environmental polices to improve health. We use a richly detailed community-level approach that describes illnesses avoided, premature deaths avoided, policy duration, and the affected population size. We allow preferences for policy attributes to vary systematically with the scenario design, with the source of risk and type of health threat, and with respondent characteristics. Using a willingness to pay (WTP) framework similar to that used for studies of individual risk, we find that omission of illness information leads to an upward bias in estimates of the value of avoided premature deaths and that individuals view avoided deaths and avoided illnesses as substitutes. We also find evidence of strongly diminishing marginal utility in policy scope. Differences in marginal WTP from different sources of risk or types of illness appear very small relative to differences associated with respondent characteristics and/or perceptions. Self-interest strongly dominates altruistic considerations.     

Estimating net benefits of recreation under conditions of excess demand

The public provision of outdoor recreation necessitates the development of nonmarket measures of the value of resources in recreational use. Such values can be used as surrogates for market values in the decision-making process. Another aspect of recreation as a publicly provided good is the absence of a mechanism to eliminate automatically excess demand. The absence of such a mechanism has resulted in conditions of excess demand at many recreation sites.This paper deduces the implications of excess demand for the travel cost method of benefit estimation. We show that when excess demand results in rationing at a particular site, the travel cost method will underestimate the true benefits of the site. The results are important because they help identify the direction of bias of one measure of the benefits from the use of a natural resource.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Trophy hunters’ willingness to pay for wildlife conservation and community benefits

In the face of fundamental land‐use changes, the potential for trophy hunting to contribute to conservation is increasingly recognized. Trophy hunting can, for example, provide economic incentives to protect wildlife populations and their habitat, but empirical studies on these relationships are few and tend to focus on the effects of benefit‐sharing schemes from an ex post perspective. We investigated the conditions under which trophy hunting could facilitate wildlife conservation in Ethiopia ex ante. We used a choice experiment approach to survey international trophy hunters’ (n = 224) preferences for trips to Ethiopia, here operationalized as trade‐offs between different attributes of a hunting package, as expressed through choices with an associated willingness to pay. Participants expressed strong preferences and, consequently, were willing to pay substantial premiums for hunting trips to areas with abundant nontarget wildlife where domestic livestock was absent and for arrangements that offered benefit sharing with local communities. For example, within the range of percentages considered in the survey, respondents were on average willing to pay an additional $3900 for every 10 percentage points of the revenue being given to local communities. By contrast, respondents were less supportive of hunting revenue being retained by governmental bodies: Willingness to pay decreased by $1900 for every 10 percentage points of the revenue given to government. Hunters’ preferences for such attributes of hunting trips differed depending on the degree to which they declared an interest in Ethiopian culture, nature conservation, or believed Ethiopia to be politically unstable. Overall, respondents thus expressly valued the outcomes of nature conservation activities—the presence of wildlife in hunting areas—and they were willing to pay for them. Our findings highlight the usefulness of insights from choice modeling for the design of wildlife management and conservation policies and suggest that trophy hunting in Ethiopia could generate substantially more financial support for conservation and be more in line with conservation objectives than is currently the case.     

Assessing the Geographic Representativeness of Genebank Collections: the Case of Bolivian Wild Potatoes

Abstract: Genebank collection databases can be used for ecogeographical studies under the assumption that the accessions are a geographically unbiased sample. We evaluated the representativeness of a collection of wild potatoes from Bolivia and defined and assessed four types of bias: species, species-area, hotspot, and infrastructure. Species bias is the sampling of some species more often than others. Species-area bias is a sampling that is disproportionate to the total area in which a species is found. Hotspot bias is the disproportionate sampling of areas with high levels of diversity. Infrastructure bias is the disproportionate sampling of areas near roads and towns. Each of these biases is present in the Bolivian wild potato collection. The infrastructure bias was strong: 60% of all wild potato accessions were collected within 2 km of a road, as opposed to 22%, if collections had been made randomly. This analysis can serve as a guide for future collecting trips. It can also provide baseline information for the application of genebank data in studies based on geographic information systems.     

Economic Valuation of Biodiversity Conservation: the Meaning of Numbers

Abstract:  Recognition of the need to include economic criteria in the conservation policy decision-making process has encouraged the use of economic-valuation techniques. Nevertheless, whether it is possible to accurately assign economic values to biodiversity and if so what these values really represent is being debated. We reviewed 60 recent papers on economic valuation of biodiversity and carried out a meta-analysis of these studies to determine what factors affect willingness to pay for biodiversity conservation. We analyzed the internal variables of the contingent-valuation method (measure of benefits, vehicle of payment, elicitation format, or timing of payment) and anthropomorphic, anthropocentric and scientific factors. Funding allocation mostly favored the conservation of species with anthropomorphic and anthropocentric characteristics instead of considering scientific factors. We recommend researchers and policy makers contemplate economic valuations of biodiversity carefully, considering the inherent biases of the contingent-valuation method and the anthropomorphic and anthropocentric factors resulting from the public's attitude toward species. Because of the increasing trend of including economic considerations in conservation practices, we suggest that in the future interdisciplinary teams of ecologists, economists, and social scientists collaborate and conduct comparative analyses, such as we have done here. Use of the contingent-valuation method in biodiversity conservation policies can provide useful information about alternative conservation strategies if questionnaires are carefully constructed, respondents are sufficiently informed, and the underlying factors that influence willingness to pay are identified.     

Using a choice experiment and birder preferences to guide bird‐conservation funding

Conservation of biodiversity, including birds, continues to challenge natural‐area managers. Stated‐preference methods (e.g., choice experiment [CE]) are increasingly used to provide data for valuation of natural ecosystems. We used a CE to calculate birders’ willingness to pay for different levels of bioecological attributes (threatened species, endemic species, and diversity) of birding sites with hypothetical entry fees. The CE was delivered at popular birding and avitourism sites in Australia and the United Kingdom. Latent‐class modeling results revealed heterogeneous preferences among birders and correspondingly variable willingness to pay. Four clear groups were apparent: quantity‐driven birders, special‐birds seekers, confused respondents, and price‐is‐no‐object birders. Quantity‐driven birders were attracted to sites that deliver high levels of diversity and endemic species for which they were willing to pay $135 and $66 to visit, respectively, above what they were willing to pay to visit a site with low levels of diversity and few endemic and threatened species . Special‐bird seekers valued threatened species and high levels of endemic species most (willingness to pay $45 and $46, respectively). Confused respondents’ preferences were difficult to determine, but they were the most sensitive to the hypothetical entry fees, unlike the price‐is‐no‐object birders, who were not at all sensitive to cost. Our findings demonstrate that birders are amenable to paying for their preferred birding experience. These payments could provide an alternative source of funding in some avitourism sites on both public and private land. Such alternative revenue streams should be explored and given full consideration in increasingly competitive conservation‐financing environments.     

State subsidies induce gray jays to accept greater danger: an ecologically rational response?

Models of strictly rational choice assume that decision-makers evaluate options on relevant dimensions, assign fixed values to options, and then make consistent choices based on these values. If so, recent experience would have no impact on preference. But, recent events change an animal’s state, and preference may change accordingly. We explore how state affects willingness to accept greater danger to obtain larger food rewards. We tested how a supplement in state (hoard size) impacts this willingness in gray jays (Perisoreus canadensis). When subsidized, most of the subjects increased their willingness to trade danger for food. Why would they become less cautious when their hoard was increased? Superficially, it might seem prudent to play it safer in response to a subsidy. But imagining fitness as a sigmoid function of state (hoard size) provides a tentative explanation for our counterintuitive finding. Above a threshold hoard size, a subsidy should weaken the willingness to accept extra danger. Incremental increases in state in the deceleratory phase yield smaller fitness gains, so it would pay to increase emphasis on safety after receiving a subsidy. But below this threshold, incremental increases in state in the acceleratory phase yield bigger fitness gains, and so it would pay to decrease emphasis on safety after receiving a subsidy. Most of our subjects’ choice behavior was, thus, plausibly consistent with the possibility that effective hoard size is considerably smaller than the total number of items stored. We speculate that this response may reflect an ecologically rational compensation for the inevitable loss of hoards via theft and rot.     

Using the bootstrap with two-phase adaptive stratified samples from multiple populations at multiple locations

Recently the two-phase adaptive stratified sampling design proposed by Francis (1984) has been extended by Manly et al. (2002) for situations where several biological populations are sampled simultaneously, and where this is done at several different geographical locations in order to estimate population totals or means. The method uses the results from a first phase sample to decide how best to allocate a second phase sample to locations and strata, in order to maximise a criterion (based on estimated coefficients of variation) that measures the accuracy of estimation for population totals, for all variables at all locations. One potential problem with this method is bias in the estimators of the population totals and means. In this paper bootstrapping is considered as a means of overcoming these biases. It is shown using model populations of Pacific walrus and shellfish, based on real data, that bootstrapping is a useful tool for removing about half of the bias. This is also confirmed from some simulations using artificial data.     

How wrong can you be? Implications of incorrect utility function specification for welfare measurement in choice experiments

Despite the vital role of the utility function in welfare measurement, the implications of working with incorrect utility specifications have been largely neglected in the choice experiments literature. This paper addresses the importance of specification with a special emphasis on the effects of mistaken assumptions about the marginal utility of income. Monte Carlo experiments were conducted using different functional forms of utility to generate simulated choices. Multi-Nomial Logit and Mixed Logit models were then estimated on these choices under correct and incorrect assumptions about the true, underlying utility function. Estimated willingness to pay measures from these choice modeling results are then compared with the equivalent measures directly calculated from the true utility specifications. Results show that for the parameter values and functional forms considered, a continuous-quadratic or a discrete-linear attribute specification is a good option regardless of the true effects the attribute has on utility. We also find that mistaken assumptions about preferences over costs magnify attribute mis-specification effects.     

An integrated model of regional and local residential sorting with application to air quality

We examine the interconnectedness of demand for regionally and locally varying public goods using a residential sorting model. We propose a version of the model that describes household choices at the city (MSA) level and, conditional on city, the neighborhood (census tract) level. We use a two-stage budgeting argument to develop an empirically feasible sorting model that allows us to estimate preferences for regionally varying air quality while accounting for sorting at the local level. Our conceptual and empirical approach nests previous sorting models as special cases, allowing us to assess the importance of accounting for multiple spatial scales in our predictions for the cost of air pollution. Furthermore our preferred specification connects the city and neighborhood sorting margins to the upper and lower elements of a nested logit model, thereby establishing a useful correspondence between two stage budgeting and nested logit estimation. Empirically we find that estimates from a conventional model of sorting across MSAs imply a smaller marginal willingness to pay for air quality than estimates from our proposed model. We discuss how the difference is attributable in part to the omitted variable problems arising when tract level sorting is ignored.     

Estimating parameters of neutral communities: from one single large to several small samples

The neutral theory of S. P. Hubbell postulates a two-scale hierarchical framework consisting of a metacommunity following the speciation-drift equilibrium characterized by the "biodiversity number" theta, and local communities following the migration-drift equilibrium characterized by the "migration rate" m (or the "fundamental dispersal number" I). While Etienne's sampling formula allows simultaneous estimation of theta and m from a single sample of a local community, its applicability to a network of (rather small) samples is questionable. We define here an alternative two-stage approach estimating theta from an adequate subset of the individuals sampled in the field (using Ewens' sampling formula) and m from community samples (using Etienne's sampling formula). We compare its results with the simultaneous estimation of theta and m (one-stage estimation), for simulated neutral samples and for 50 1-ha plots of evergreen forest in South India. The one-stage approach exhibits problems of bias and of poor differentiability between high-theta, low-m and low-theta, high-m solution domains. Conversely, the two-stage approach yielded reasonable estimates and is to be preferred when several small, scattered plots are available instead of a single large one.     

Annual occurrence,abundance and diversity of fish in a South Carolina intertidal creek

An intertidal creek in North Inlet Estuary, South Carolina, USA, was sampled monthly for 1 year to determine the occurrence, abundance and diversity of fish species. Sampling was so conducted as to reduce sampling bias to a minimum and all individuals caught were weighed and measured. A total of 16,611 individuals weighing 202.45 kg and comprising 51 species and 25 families of fish was collected. Three diversity indices were calculated for species number. Analysis of variance revealed that season had a highly significant effect on all indices and the number of species, but had no effect on the number of individuals caught.This work was supported by the Belle W. Baruch Foundation and the South Carolina State Development Board, and is Contribution No. 71 of the Belle W. Baruch Institute for Marine Biology and Coastal Research.     

Time perspective and climate change policy

The tendency to foreshorten time units as we peer further into the future provides an explanation for hyperbolic discounting at an inter-generational time scale. We study implications of hyperbolic discounting for climate change policy, when the probability of a climate-induced catastrophe depends on the stock of greenhouse gasses. We characterize the set of Markov perfect equilibria (MPE) of the inter-generational game amongst a succession of policymakers. Each policymaker reflects her generation's preferences, including its hyperbolic discounting. For a binary action game, we compare the MPE set to a “restricted commitment” benchmark. We compare the associated “constant-equivalent discount rates” and the willingness to pay to control climate change with assumptions and recommendations in the Stern Review on Climate Change.“…My picture of the world is drawn in perspective…. I apply my perspective not merely to space but also to time”—Ramsey.     

Site-selection bias and apparent population declines in long-term studies

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.     

Willingness to Pay for Quality Improvements: Should Revealed and Stated Preference Data Be Combined?

In this article we propose theoretically consistent welfare measurement of use and nonuse values for an improvement in environmental quality with revealed and stated preference data. An analytical model based on the comparative static analysis of the variation function that describes the relationship between recreation demand and dichotomous choice contingent valuation models is estimated. Our results show that revealed and stated data should not be combined under the same assumed preference structure unless the two decisions imply the same change in behavior induced by the quality change. In addition, our results indicate scope effects in willingness to pay measures estimated with stated preference data.