Matching biodiversity indicators to policy needs

At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (e.g., the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision-making, and supports preventative action.     

Collapse and reorganization of a food web of Mwanza Gulf, Lake Victoria

Lake Victoria in East Africa is the world's second largest freshwater system. Over the past century the ecosystem has undergone drastic changes. Some 30 years after the introduction of Nile perch (Lates niloticus) and Nile tilapia (Oreochromis niloticus) in the 1950s, the highly diverse community of native haplochromines collapsed, leaving a system dominated by only four species: the native cyprinid dagaa (Rastrineobola argentea) and shrimp (Caridina nilotica), as well as the introduced Nile perch and Nile tilapia. More recently, an unexpected resurgence of haplochromines has been reported. To understand these changes in terms of ecosystem functioning and of changes in growth of trophic groups, we created mass balances of the food web near Mwanza, Tanzania, before, during, and after the Nile perch boom (1977, 1987, and 2005), using the application ECOPATH. We connected these mass balances with a dynamic model assuming linear trends in net growth rates of the trophic groups. Our analysis suggests that the Nile perch boom initially altered the biomass distribution over trophic levels. Also, results indicate that not only fishing but also changes at the detritivores' trophic level might have played an important role in driving changes in the system. Both the mass balances and the dynamic model connecting them reveal that, after a major distortion during the Nile perch boom, the biomass distribution over the main trophic levels had largely recovered its original (1977) state by 2005. However, no such return appeared in terms of community structure. Biodiversity in the new state is dramatically lower, consisting of introduced species and a few native surviving species. We conclude that at an aggregate level Lake Victoria's ecosystem has proved to be resilient in the sense that its overall trophic structure has apparently recovered after a major perturbation. By contrast, its intricate functional structure and associated biodiversity have proved to be fragile and seem unlikely to recover.     

Effect of variable fishing strategy on fisheries under changing effort and pressure: An agent-based model application

An agent-based model was used to evaluate the response of a two-species fish community to fishing boat exploration strategies, namely: boats following high-yield boats (Cartesian); boats fishing at random sites (stochast-random); and boats fishing at least exploited sites (stochast-pressure). At low fishing pressure, the stochast-random mode yielded a high average catch per boat while sustaining fish biomass. At high fishing pressure, the Cartesian mode was more effective. For the Cartesian strategy, fish biomass exhibited four distinct behaviors with increasing number of boats. In the first phase, the fish biomass dropped with increasing number of boats due to a corresponding rise in biomass extraction. Rapid exploitation occurred in the second phase, when two or more boats occupied the same initial area, that led to the faster abandonment of those sites which then underwent biomass recovery. In the third phase, adding more boats resulted in a fluctuating stock biomass, where the combined effects of initial spatial distribution of boats and rapid localization led to either full stock recovery when boats were eventually confined to a single location due to spillovers, or stock extirpation when the entire area became fully occupied. Beyond the third phase, stock extirpation was assured. In order to break the pattern of localization (bandwagon effect), we introduced stochast-random intruders in a Cartesian-dominated fishery. Adding a single intruder changed the patchy-structured stock biomass pattern of a purely Cartesian fishery to a uniformly explored stock biomass pattern because of the additional spatial information provided by the intruder. Consequently, the average catch per boat increased but at the expense of a disproportionate decline in equilibrium biomass.     

Interactions between cod, herring and sprat in the changing environment of the Baltic Sea: A dynamic model analysis

The interactions between cod (Gadus morhua), herring (Clupea harengus) and sprat (Sprattus sprattus) in the Central Baltic Sea were examined with a simple dynamic model, an alternative to more complicated and data-demanding multispecies and ecosystem models. The main aims of the study were to compare the effect of alternative structures on the model output and examine the control relationships in the fish assemblage under different environmental conditions. The effect of environmental conditions was modelled using a stock-recruitment equation for cod incorporating an environmental index. The model output was especially sensitive to the functional response in predation by cod on herring and sprat. The type II functional response led to a collapse of the clupeid stocks when cod was abundant, while the type III response produced more realistic stock dynamics. According to the simulations, an abundant cod stock was able to keep the sprat stock at a low level, while the herring stock was less affected and benefited from the decreased density of sprat. Simulation of different fishing scenarios indicated that reducing fishing mortality to the level currently advised by ICES would allow the recovery of the cod stock even in unfavourable environmental conditions.     

Protecting biodiversity and economic returns in resource-rich tropical forests

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. We examined how protection of biodiversity and economic revenues can be balanced in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimized the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon across a range of opportunity costs (i.e., sacrifices of extractive profit). We also applied spatial statistics to remotely sensed, historic deforestation data to focus the optimization on areas most threatened by imminent forest loss. Giving up 5% of a year's oil profits (US$221 million) allowed for a protected area network that retained an average of 65% of the extent of each species and ecosystem. This performance far exceeded that of the network produced by simple optimization for land area (which required a sacrifice of approximately 40% of annual oil profits [US$1.7 billion]) and used only marginally less land to achieve equivalent levels of ecological protection. We identified what we call emergency conservation targets: regions that are essential components of a cost-effective conservation reserve network but at imminent risk of destruction, thus requiring urgent and effective protection. Governments can use our methods when evaluating extractive-led development options to responsibly manage the associated ecological and economic trade-offs and protect natural capital.     

Effects of Fishing on the Ecosystem Structure of Coral Reefs

Overfishing is considered one of the three most significant threats to coral reef ecosystems. Exponentially increasing human populations in the tropics have placed enormous demands upon reefs as a food source. At high intensities, termed ecosystem or Malthusian overfishing, fishing causes major direct and indirect effects on the community structure of fishes and other organisms. It reduces species diversity and leads to local extinctions not only of target species but also of other species not fished directly. Conceivably it could also lead to global extinctions. Loss of keystone species, such as predators of echinoderms, through fishing, can lead to major effects on reef processes, such as accretion of calcium carbonate. Ultimately, sustained heavy fishing may lead to loss of entire functional groups of species, resulting in impairment of the potentially important ecosystem functions provided by those groups. Overfishing has been shown to interact with other agents of disturbance to reduce the ability of reefs to recover from natural occurrences such as hurricanes. Effective management of fishing will require a deeper understanding of the effects of exploitation than we now possess. Research initiatives are underway to examine the responses of fish populations to fishing, generally responses to protection from fishing. There is, however, an urgent need to look beyond fish communities and to consider the entire reef ecosystem. Studies that integrate population and community biology with ecosystem processes will provide a much better understanding of the effects of biodiversity loss on reef function and will improve our ability to manage these complex systems.     

A habitat‐based approach to predict impacts of marine protected areas on fishers

Although marine protected areas can simultaneously contribute to biodiversity conservation and fisheries management, the global network is biased toward particular ecosystem types because they have been established primarily in an ad hoc fashion. The optimization of trade‐offs between biodiversity benefits and socioeconomic values increases success of protected areas and minimizes enforcement costs in the long run, but it is often neglected in marine spatial planning (MSP). Although the acquisition of spatially explicit socioeconomic data is perceived as a costly or secondary step in MSP, it is critical to account for lost opportunities by people whose activities will be restricted, especially fishers. We developed an easily reproduced habitat‐based approach to estimate the spatial distribution of opportunity cost to fishers in data‐poor regions. We assumed the most accessible areas have higher economic and conservation values than less accessible areas and their designation as no‐take zones represents a loss of fishing opportunities. We estimated potential distribution of fishing resources from bathymetric ranges and benthic habitat distribution and the relative importance of the different resources for each port of total catches, revenues, and stakeholder perception. In our model, we combined different cost layers to produce a comprehensive cost layer so that we could evaluate of trade‐offs. Our approach directly supports conservation planning, can be applied generally, and is expected to facilitate stakeholder input and community acceptance of conservation.     

Effects of local fisheries and ocean productivity on the northeastern Ionian Sea ecosystem

To better understand the effects of fisheries and ocean productivity on the northeastern Ionian Sea we constructed an Ecopath with Ecosim model with 22 functional groups. Data on biomass, production/biomass, consumption/biomass, and diet for each group were estimated or extrapolated from the literature. Fisheries landings and discards were also included. Temporal trajectories were simulated using Ecosim. The model was fitted with time-series data for the most important groups from 1964 to 2006. Simulations highlighted a decline of top predators and of most of the commercial species since the late 1970s. The model shows that the decline of fish resources was mainly caused by an intensive fishing pressure that occurred in the area until the end of the 1990s and also by changes in primary production that impacted the trajectories of the main functional groups. In particular, simulated changes through time in PP impacted the abundance trends of all the commercial species, showing a cascade-up effect through the ecosystem. The application of Ecopath with Ecosim was a useful tool for understanding the trends of the main functional groups of the northeastern Ionian Sea. The model underlined that management actions are needed to restore and protect target species including marine mammals, pelagic and demersal fishes. In particular, measures to reduce overfishing, illegal fishing activities and to respect existing legislations are in need. Moreover, the adoption of marine protected areas could be an effective management measure to guarantee prey survival and to sustain marine predators.     

Threats of illegal,unregulated, and unreported fishing to biodiversity and food security in the Republic of the Congo

Illegal, unregulated, and unreported (IUU) fishing poses a major threat to effective management of marine resources, affecting biodiversity and communities dependent on these coastal resources. Spatiotemporal patterns of industrial fisheries in developing countries are often poorly understood, and global efforts to describe spatial patterns of fishing vessel activity are currently based on automatic identification system (AIS) data. However, AIS is often not a legal requirement on fishing vessels, likely resulting in underestimates of the scale and distribution of legal and illegal fishing activity, which could have significant ramifications for targeted enforcement efforts and the management of fisheries resources. To help address this knowledge gap, we analyzed 3 years of vessel monitoring system (VMS) data in partnership with the national fisheries department in the Republic of the Congo to describe the behavior of national and distant-water industrial fleets operating in these waters. We found that the spatial footprint of the industrial fisheries fleet encompassed over one-quarter of the Exclusive Economic Zone. On average, 73% of fishing activity took place on the continental shelf (waters shallower than 200 m). Our findings highlight that VMS is not acting as a deterrent or being effectively used as a proactive management tool. As much as 33% (13% on average) of fishing effort occurred in prohibited areas set aside to protect biodiversity, including artisanal fisheries resources, and the distant-water fleet responsible for as much as 84% of this illegal activity. Given the growth in industrial and distant-water fleets across the region, as well as low levels of management and enforcement, these findings highlight that there is an urgent need for the global community to help strengthen regional and national capacity to analyze national scale data sets if efforts to combat IUU fishing are to be effective.     

Regional policy models for forest biodiversity analysis: lessons from coastal Oregon.

The crisis in the early 1990s over conservation of biodiversity in the forests of the Pacific Northwest caused an upheaval in forest policies for public and private landowners. These events led to the development of the Coastal Landscape Assessment and Modeling Study (CLAMS) for the Coast Range Physiographic Province of Oregon, a province containing over two million hectares of forest with a complex mixture of public and private ownership. Over a decade, CLAMS scientists developed regional data bases and tools to enable assessments of the implications of current policies for biodiversity and have begun using these data and tools to test ideas for solving policy problems. We summarize here four main lessons from our work: (1) Regional ecosystem perspectives, while rewarding, are difficult to achieve. Helping policy makers and the public understand biodiversity policies for an entire province can assist in developing more reasoned policies. However, this result is difficult to achieve because needed scientific building blocks generally do not exist, few policy institutions address regional cross-ownership issues, people can find it difficult to take a regional view, and the appropriate region for analysis changes with the policy problem. (2) Interest in environmental policy analysis may come as much from a pursuit of power as a pursuit of understanding. Biodiversity policy analyses are often viewed as weapons in an ongoing political battle. Also, results that might destabilize existing policies generally will not be well received by those in power. (3) The relationship of regional analyses to civic processes remains challenging and unsettled. Communication between citizens and scientists takes real effort. Also, collaborative processes both inspire and constrain regional policy analysis, and scientific work often proceeds at a different pace than these processes. In the end, CLAMS's most important effect on the civic dialogue may be to change how people think about the Coast Range. (4) An important role exists for anticipatory assessments done independently by scientists. Independent review will be especially important as policy analyses shift to management of nonfederal forests. Our future efforts in CLAMS will focus on evaluating ideas for fundamental changes in forest management.     

Multiple functions increase the importance of biodiversity for overall ecosystem functioning

Biodiversity is proposed to be important for the rate of ecosystem functions. Most biodiversity-ecosystem function studies, however, consider only one response variable at a time, and even when multiple variables are examined they are analyzed separately. This means that a very important aspect of biodiversity is overlooked: the possibility for different species to carry out different functions at any one time. We propose a conceptual model to explore the effects of species loss on overall ecosystem functioning, where overall functioning is defined as the joint effect of many ecosystem functions. We show that, due to multifunctional complementarity among species, overall functioning is more susceptible to species loss than are single functions. Modeled relationships between species richness and overall ecosystem functioning using five empirical data sets on monocultures reflected the range of effects of species loss on multiple functions predicted by the model. Furthermore, an exploration of the correlations across functions and the degree of redundancy within functions revealed that multifunctional redundancy was generally lower than single-function redundancy in these empirical data sets. We suggest that by shifting the focus to the variety of functions maintained by a diversity of species, the full importance of biodiversity for the functioning of ecosystems can be uncovered. Our results are thus important for conservation and management of biota and ecosystem services.     

Modeling an exploited rocky coastal ecosystem: Bahia Tortugas, Mexico

A trophic structure model of the rocky coastal ecosystem in Bahia Tortugas, Mexico was constructed using Ecopath software to represent the main biomass flows in the system. Data for the model came from field observations (biomass estimates, stomach contents, and ecological observations for sea snails, abalones, lobster, some demersal finfishes, and macroalgae) carried out through ten field trips from 2006 to 2008. The results provide a snapshot of how the ecosystem operates. The model considers 23 functional groups. The total system throughput was 553 t/km²/year, 57% corresponds to internal consumption, 28% to respiration, 14% becomes detritus, and only 1% is removed through commercial fishing. The model suggests that even for exploited populations, predation and competition are heavier stresses than current fishing effort; however, because spiny lobster showed the second highest keystoneness’ index value, increasing fishing pressure on this group could strongly impact the entire ecosystem. We believe that this model has the potential to support management by allowing the exploration of the potential impacts of different fishing decisions at ecosystem level.     

Mapping social–ecological vulnerability to inform local decision making

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social–ecological vulnerability offers a valuable framework for identifying and understanding important social–ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social–ecological vulnerability. We developed a method to map social–ecological vulnerability based on information on human–nature dependencies and ecosystem services at local scales. We applied our method to the small‐scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social–ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human–nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social–ecological vulnerability framework for policy, planning, and participatory management decisions.     

Effects of near‐future ocean acidification,fishing, and marine protection on a temperate coastal ecosystem

Understanding ecosystem responses to global and local anthropogenic impacts is paramount to predicting future ecosystem states. We used an ecosystem modeling approach to investigate the independent and cumulative effects of fishing, marine protection, and ocean acidification on a coastal ecosystem. To quantify the effects of ocean acidification at the ecosystem level, we used information from the peer‐reviewed literature on the effects of ocean acidification. Using an Ecopath with Ecosim ecosystem model for the Wellington south coast, including the Taputeranga Marine Reserve (MR), New Zealand, we predicted ecosystem responses under 4 scenarios: ocean acidification + fishing; ocean acidification + MR (no fishing); no ocean acidification + fishing; no ocean acidification + MR for the year 2050. Fishing had a larger effect on trophic group biomasses and trophic structure than ocean acidification, whereas the effects of ocean acidification were only large in the absence of fishing. Mortality by fishing had large, negative effects on trophic group biomasses. These effects were similar regardless of the presence of ocean acidification. Ocean acidification was predicted to indirectly benefit certain species in the MR scenario. This was because lobster (Jasus edwardsii) only recovered to 58% of the MR biomass in the ocean acidification + MR scenario, a situation that benefited the trophic groups lobsters prey on. Most trophic groups responded antagonistically to the interactive effects of ocean acidification and marine protection (46%; reduced response); however, many groups responded synergistically (33%; amplified response). Conservation and fisheries management strategies need to account for the reduced recovery potential of some exploited species under ocean acidification, nonadditive interactions of multiple factors, and indirect responses of species to ocean acidification caused by declines in calcareous predators.     

Optimization of an artificial neural network for identifying fishing set positions from VMS data: An example from the Peruvian anchovy purse seine fishery

The spatial behavior of numerous fishing fleets is nowadays well documented thanks to satellite Vessel Monitoring Systems (VMS). Vessel positions are recorded on a frequent and regular basis which opens promising perspectives for improving fishing effort estimation and management. However, no specific information is provided on whether the vessel is fishing or not. To answer that question, existing works on VMS data usually apply simple criteria (e.g. threshold on speed). Those simple criteria generally focus in detecting true positives (a true fishing set detected as a fishing set); conversely, estimation errors are given no attention. For our case study, the Peruvian anchovy fishery, those criteria overestimate the total number of fishing sets by 182%. To overcome this problem an artificial neural network (ANN) approach is presented here. In order to set both the optimal parameterization and use “rules” for this ANN, we perform an extensive sensitivity analysis on the optimization of (1) the internal structure and training algorithm of the ANN and (2) the “rules” used for choosing both the relative size and the composition of the databases (DBs) used for training and inferring with the ANN. The “optimized” ANN greatly improves the estimates of the number and location of fishing events. For our case study, ANN reduces the total estimation error on the number of fishing sets to 1% (in average) and obtains 76% of true positives. This spatially explicit information on effort, provided with error estimation, should greatly reduce misleading interpretations of catch per unit effort and thus significantly improve the adaptive management of fisheries. While fitted on Peruvian anchovy fishery data, this type of neural network approach has wider potential and could be implemented in any fishery relying on both VMS and at-sea observer data. In order to increase the accuracy of the ANN results, we also suggest some criteria for improving sampling design by at-sea observers and VMS data.     

When are no-take zones an economically optimal fishery management strategy?

Discussions on the use of marine reserves (no-take zones) and, more generally, spatial management of fisheries are, for the most part, devoid of analyses that consider the ecological and economic effects simultaneously. To fill this gap, we develop a two-patch ecological-economic model to investigate the effects of spatial management on fishery profits. Because the fishery effects of spatial management depend critically on the nature of the ecological connectivity, our model includes both juvenile and adult movement, with density dependence in settlement differentiating the two types of dispersal. Rather than imposing a reserve on our system and measuring its effect on profits, we ask: "When does setting catch levels to maximize system-wide profits imply that a reserve should be created?" Closing areas to fishing is an economically optimal solution when the value derived from spillover from the reserve outweighs the value of fishing in the patch. The condition, while simple to state in summary form, is complex to interpret because it depends on the settlement success of the dispersing organisms, the nature of the costs of the fishing, the economic and ecological heterogeneity of the system, the discount rate, and growth characteristics of the fish population. The condition is more likely to be satisfied when the closed area is a net exporter of biomass and has higher costs of fishing, and for fish populations with density-independent settlement ("adult movement") than with density-dependent settlement ("larval dispersal"). Rather surprisingly, there are circumstances whereby closing low biological productivity areas, and even sometimes low cost areas to fish, can result in greater fishing profits than when both areas are open to fishing.     

Crediting uncertain ecosystem services in a market

The margin of safety (MOS) approach is an increasingly prevalent tool for ensuring the integrity of market-based programs for providing ecosystem services. Over-crediting is reduced by setting aside mean estimates of uncertain services in favor of a more conservative estimate. Like many environmental policy problems, ecosystem service markets involve the aggregation of uncertainty over multiple scales, e.g. from landowners to market intermediaries to the overall market. We examine how the MOS instrument affects, and is affected by, an ecosystem services market. We show that the common bottom-up approach of imposing risk preferences at a local, disaggregated level—held over from earlier development in the context of toxics and command and control-style health risk regulation—leads to several unintended consequences. Furthermore, discounting landowner services can actually increase their profits, conditional on the elasticity of credit demand. We illustrate theoretical insights with an empirical application to greenhouse gas offset crediting in agriculture.     

Effects of Changes in Biodiversity on Ecosystem Function in Tropical Forests

Changing land use in the tropics has resulted in vast areas of damaged and degraded lands where biodiversity has been reduced. The majority of research on biodiversity has been focused on population and community dynamics and has rarely considered the ecosystem processes that are intimately related. We present a framework for examining the effects of changes in biodiversity on ecosystem function in natural, managed, and damaged tropical forests. Using a whole-ecosystem approach, the framework identifies key nutrient and energy cycling processes and critical junctures or pathways, termed interfaces, where resources are concentrated and transferred between the biotic and abiotic components of the ecosystem. Processes occurring at these interfaces, and the organisms or attributes participating in these processes, exert a strong influence on ecosystem structure. We use examples from Puerto Rico, Southern China, Dominica, and Nicaragua to illustrate how the functional diversity framework can be applied to critically examine the effects of changes in biodiversity on ecosystem function, and the relative success or failure of rehabilitation strategies. The few available data suggest that functional diversity, and not just species richness, is important in maintaining the integrity of nutrient and energy fluxes. High species richness, however, may increase ecosystem resiliency following disturbance by increasing the number of alternative pathways for the flow of resources. We suggest ways in which the framework of functional diversity can be used to design research to examine the effects of changes in biodiversity on ecosystem processes and in the design and evaluation of ecosystem management and land rehabilitation projects in the tropics.     

Technological change and fisheries sustainability: The point of view of Adaptive Dynamics

The analysis of a simple model shows that exploitation of fish stocks can entrain in the long run the substantial decline or even the collapse of the stock, as well as difficulties in stock recovery, loss of fishery resilience, and reduction of the mean fish size. The results are in agreement with numerous observations, even though they are obtained with a simple model in which the harvesting fleet and the fish stock are considered as unstructured predator and prey. The study is carried out for the typical case of fleet dimension not too sensitive to the year-to-year fluctuations of the stock and assuming that the sole cause of evolution is technological innovation. The analysis is performed by means of Adaptive Dynamics, an approach born in theoretical biology which is used here in the context of technological change. Although the results are qualitatively consistent with those obtained long ago through the principles of bioeconomics, it is fair to stress that the underlying assumptions are different. In fact, in the bioeconomic approach fleet technology does not evolve and fishing effort varies to produce economic optimization, while in the Adaptive Dynamics approach technological innovation is the key driver. The paper is purely theoretical and the proposed model can hardly be tuned on any real fishery. No practical guidelines for managers can therefore be drawn, if not the general conclusion that long-term sustainability of exploited fish stocks can only be achieved if strategic parameters influencing technological change are kept under strict control.     

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (-16%) and pasture (-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.