Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Quantifying the squeezing or stretching of fisheries as they adapt to displacement by marine reserves

The designation of no‐take marine reserves involves social and economic concerns due to the resulting displacement of fishing effort, when fishing rights are removed from those who traditionally fished within an area. Displacement can influence the functioning of the fishery and success of the reserve, yet levels of displacement are seldom quantified after reserve implementation and very rarely before that. We devised a simple analytical framework based on set theory to facilitate reserve placement. Implementation of the framework requires maps of fishing grounds, fishing effort, or catch per unit effort for at least 2 years. The framework quantifies the level of conflict that a reserve designation might cause in the fishing sector due to displacement and the opportunities to offset the conflict through fisher spatial mobility (i.e., ability of fishers to fish elsewhere). We also considered how the outputs of the framework can be used to identify targeted management interventions for each fishery. We applied the method in Honduras, where the largest marine protected area in Central America is being placed, for which spatial data on fishing effort were available for 6 fisheries over 3 years. The proposed closure had a greater negative impact on the shrimp and lobster scuba fisheries, which concentrated respectively 28% and 18% of their effort inside the reserve. These fisheries could not accommodate the displacement within existing fishing grounds. Both would be forced to stretch into new fishing grounds, which are available but are of unknown quality. These stakeholders will likely require compensation to offset costly exploratory fishing or to travel to fishing grounds farther away from port.     

Effects of productivity on biodiversity in forest ecosystems across the United States and China

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem‐wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground‐sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump‐shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity–biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.     

Characterizing the Width of Amphibian Movements During Postbreeding Migration

Habitat linkages can help maintain connectivity of animal populations in developed landscapes. However, the lack of empirical data on the width of lateral movements (i.e., the zigzagging of individuals as they move from one point to point another) makes determining the width of such linkages challenging. We used radiotracking data from wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in a managed forest in Maine (U.S.A.) to characterize movement patterns of populations and thus inform planning for the width of wildlife corridors. For each individual, we calculated the polar coordinates of all locations, estimated the vector sum of the polar coordinates, and measured the distance from each location to the vector sum. By fitting a Gaussian distribution over a histogram of these distances, we created a population‐level probability density function and estimated the 50th and 95th percentiles to determine the width of lateral movement as individuals progressed from the pond to upland habitat. For spotted salamanders 50% of lateral movements were ≤13 m wide and 95% of movements were ≤39 m wide. For wood frogs, 50% of lateral movements were ≤17 m wide and 95% of movements were ≤ 51 m wide. For both species, those individuals that traveled the farthest from the pond also displayed the greatest lateral movement. Our results serve as a foundation for spatially explicit conservation planning for pond‐breeding amphibians in areas undergoing development. Our technique can also be applied to movement data from other taxa to aid in designing habitat linkages. Caracterización de la Amplitud de Movimiento de Anfibios durante la Migración Pos‐Reproducción     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Archaeological Evidence of Validity of Fish Populations on Unexploited Reefs as Proxy Targets for Modern Populations

Reef‐fish management and conservation is hindered by a lack of information on fish populations prior to large‐scale contemporary human impacts. As a result, relatively pristine sites are often used as conservation baselines for populations near sites affected by humans. This space‐for‐time approach can only be validated by sampling assemblages through time. We used archaeological remains to evaluate whether the remote, uninhabited Northwestern Hawaiian Islands (NWHI) might provide a reasonable proxy for a lightly exploited baseline in the Main Hawaiian Islands (MHI). We used molecular and morphological techniques to describe the taxonomic and size composition of the scarine parrotfish catches present in 2 archaeological assemblages from the MHI, compared metrics of these catches with modern estimates of reproductive parameters to evaluate whether catches represented by the archaeological material were consistent with sustainable fishing, and evaluated overlap between size structures represented by the archaeological material and modern survey data from the MHI and the NWHI to assess whether a space‐for‐time substitution is reasonable. The parrotfish catches represented by archaeological remains were consistent with sustainable fishing because they were dominated by large, mature individuals whose average size remained stable from prehistoric (AD approximately 1400–1700) through historic (AD 1700–1960) periods. The ancient catches were unlike populations in the MHI today. Overlap between the size structure of ancient MHI catches and modern survey data from the NWHI or the MHI was an order of magnitude greater for the NWHI comparison, a result that supports the validity of using the NWHI parrotfish data as a proxy for the MHI before accelerated, heavy human impacts in modern times. Evidencia Arqueológica de la Validez de Poblaciones de Peces en Arrecifes Sin Explotar como Objetivos de Apoderamiento para Poblaciones Actuales