Area-Based Refinement for Selection of Reserve Sites with the Benefit-Function Approach

Abstract:  Optimization of resource use is necessary for efficient conservation planning. Many reserve-selection algorithms aim to identify representative but inexpensive networks, which may lead to selecting small sites due to their lower costs and collectively higher species richness. Nevertheless, larger sites would be preferable regarding species' long-term persistence. An area-based refinement can be used to overcome this problem. We used a reserve-planning framework in which continuous benefit functions valued representation (numbers of populations), and differential species weights were based on a species' local rarity and threatened status. We introduced a refinement based on the species-area relationship that provides relatively higher values for larger sites. We applied the proposed method to rich fen vegetation in southern Finland. The species-area refinement resulted in a network of significantly larger sites with minor trade-offs with representation (numbers of populations). Giving endangered species higher weights ensured that the trade-off occurred mostly between site size and representation of low-priority species. We recommend using a species-area refinement for practical, maximum-coverage conservation planning.     

Cost-Efficiency of Decaying Wood as a Surrogate for Overall Species Richness in Boreal Forests

Abstract:  Decaying wood is one of the most important elements for species richness in boreal forests. We tested how well reserve selection based on the amount and quality of decaying wood results in a representation of four ecologically different taxa (beetles, birds, wood-inhabiting fungi, and vascular plants). We also compared the cost-efficiency of the use of dead-wood indicators with comprehensive species inventory. Our database included 32 seminatural old-forest stands located in northern Finland. Decaying wood was a relatively good indicator of saproxylic species but not overall species richness. Even though dead wood did not reflect accurately overall species richness, our results indicated that the use of decaying wood as an indicator in site selection was more cost-efficient than using information from large-scale species inventories. Thus, decaying wood is a valuable surrogate for species richness, but other cost-efficient indicators that reflect the requirements of those species which are not dependent on decaying wood should be identified.     

江西省永平铜矿排土场植被复垦

介绍江西省永平铜矿十多年来植被复垦试验与推广的实践经验和取得的效果，提出今后复垦应解决和注意的问题。     

Econometric modeling of fisheries with complex life histories: Avoiding biological management failures

Economics of the fishery has focused on the wastefulness of common pool resource exploitation. Pure open access fisheries dissipate economic rents and degrade biological stocks. Biologically managed fisheries also dissipate rents but are thought to hold biological stocks at desired levels. We develop and estimate an empirical bioeconomic model of the Gulf of Mexico gag fishery that questions the presumptive success of biological management. Unlike previous bioeconomic life history studies, we provide a way to circumvent calibration problems by embedding our estimation routine directly in the dynamic bioeconomic model. We nest a standard biological management model that accounts for complex life history characteristics of the gag. Biological intuition suggests that a spawning season closure will reduce fishing pressure and increase stocks, and simulations of the biological management model confirm this finding. However, simulations of the empirical bioeconomic model suggest that these intended outcomes of the spawning closure do not materialize. The behavioral response to the closure appears to be so pronounced that it offsets the restriction in allowable fishing days. Our results indicate that failure to account for fishing behavior may play an important role in fishery management failures.     

Predicting and Mapping Potential Whooping Crane Stopover Habitat to Guide Site Selection for Wind Energy Projects

Migratory stopover habitats are often not part of planning for conservation or new development projects. We identified potential stopover habitats within an avian migratory flyway and demonstrated how this information can guide the site‐selection process for new development. We used the random forests modeling approach to map the distribution of predicted stopover habitat for the Whooping Crane (Grus americana), an endangered species whose migratory flyway overlaps with an area where wind energy development is expected to become increasingly important. We then used this information to identify areas for potential wind power development in a U.S. state within the flyway (Nebraska) that minimize conflicts between Whooping Crane stopover habitat and the development of clean, renewable energy sources. Up to 54% of our study area was predicted to be unsuitable as Whooping Crane stopover habitat and could be considered relatively low risk for conflicts between Whooping Cranes and wind energy development. We suggest that this type of analysis be incorporated into the habitat conservation planning process in areas where incidental take permits are being considered for Whooping Cranes or other species of concern. Field surveys should always be conducted prior to construction to verify model predictions and understand baseline conditions. Predicción y Mapeo del Hábitat Potencial de Descanso de la Grulla Americana para Guiar la Selección de Sitios para Proyectos de Energía Eólica.     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

Detecting Population Declines over Large Areas with Presence-Absence, Time-to-Encounter, and Count Survey Methods

Abstract:  Ecologists often discount presence-absence surveys as a poor way to gain insight into population dynamics, in part because these surveys are not amenable to many standard statistical tests. Still, presence-absence surveys are sometimes the only feasible alternative for monitoring large areas when funds are limited, especially for sparse or difficult-to-detect species. I undertook a detailed simulation study to compare the power of presence-absence, count, and time-to-encounter surveys to detect regional declines in a population. I used a modeling approach that simulates both population numbers and the monitoring process, accounting for observation and other measurement errors. In gauging the efficacy of presence-absence surveys versus other approaches, I varied the number of survey sites, the spatial variation in encounter rate, the mean encounter rate, and the type of population loss. My results showed that presence-absence data can be as or more powerful than count data in many cases. Quantitative guidelines for choosing between presence-absence surveys and count surveys depend on the biological and logistical constraints governing a conservation monitoring situation. Generally, presence-absence surveys work best when there is little variability in abundance among the survey sites, the organism is rare, and the species is difficult to detect so that the time spent getting to each survey site is less than or equal to the time spent surveying each site. Count surveys work best otherwise. I present a case study with count data on the Northern Flicker ( Colaptes auratus ) from the North American Breeding Bird Survey to illustrate how the method might be used with field-survey data. The case study demonstrates that a count survey would be the most cost-effective design but would entail reduction in the number of sites. If this site reduction is not desirable, a presence-absence survey would be the most cost-effective survey.     

Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations

Abstract: Species’ assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection–nondetection records) are generated. Within‐season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site‐occupancy models are applied directly to the detection‐history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site‐occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen‐science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.