BIOFRAG – a new database for analyzing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a consistent and flexible database permits simple data retrieval for subsequent analyses. We present a relational database that links such field data to taxonomic nomenclature, spatial and temporal plot attributes, and environmental characteristics. Field assessments include measurements of the response(s) (e.g., presence, abundance, ground cover) of one or more species linked to plots in fragments within a partially forested landscape. The database currently holds 9830 unique species recorded in plots of 58 unique landscapes in six of eight realms: mammals 315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods 85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes were sampled as long-term time series (\u3e10 years). Seven hundred and eleven species are found in two or more landscapes. Consolidating the substantial amount of primary data available on biodiversity responses to fragmentation in the context of land-use change and natural disturbances is an essential part of understanding the effects of increasing anthropogenic pressures on land. The consistent format of this database facilitates testing of generalizations concerning biologic responses to fragmentation across diverse systems and taxa. It also allows the re-examination of existing datasets with alternative landscape metrics and robust statistical methods, for example, helping to address pseudoreplication problems. The database can thus help researchers in producing broad syntheses of the effects of land use. The database is dynamic and inclusive, and contributions from individual and large-scale data-collection efforts are welcome

How indeterminism shapes ecologists’ contributions to managing socio-ecological systems

To make a difference in policy making about socio-ecological systems, ecologists must grasp when decision makers are amenable to acting on ecological expertise and when they are not. To enable them to do so we present a matrix for classifying a socio-ecological system by the extent of what we don’t know about its natural components and the social interactions that affects them. We use four examples, Midcontinent Mallards, Laysan Ducks, Pallid Sturgeon, and Rocky Mountain Grey Wolves to illustrate how the combination of natural and social source of indeterminism matters. Where social indeterminism is high, ecologists can expand the range of possible science-based options decision makers might consider even while recognizing societal-based concerns rather than science will dominate decision making. In contrast, where natural indeterminism is low, ecologists can offer reasonably accurate predictions that may well serve as inputs into decision making. Depending on the combination of natural and social indeterminism characterizing a particular circumstance, ecologists have different roles to play in informing socio-ecological system management

If larvae were smart: a simple model for optimal settlement behavior of competent larvae

Much research has been done on larval settlement cues. Rather than having simple fixed responses to constant environmental stimuli, it seems likely that settlement decisions made by individual larvae should vary depending on the individual and the conditions under which it encounters that cue. Here, we present a simple stochastic dynamic programming model that explores the conditions under which larvae may maximize their lifetime fitness by accepting lower quality habitat rather than continuing to search for superior habitat. Our model predicts that there is a relatively narrow range of parameter values over which larval selectivity among habitat types changes dramatically from 1 (larvae accept only optimal substrata) to 0 (indiscriminant settlement). This narrow range coincides with our best estimate of parameter values gleaned from empirical studies, and the model output matches data for the polychaete worm Hydroides dianthus remarkably well. The relative availability of habitats and the total time available to search for high quality habitat (i.e. the ability to delay metamorphosis) had the greatest effects on larval selectivity. In contrast, intuitive factors, including larval energetics and mortality, showed little effect on larval habitat preference, but could still alter the proportion of larvae settling in different habitats by reducing search time. Our model predicts that a given larva may behave differently depending on where it falls in the optimality decision matrix at the instant in which it locates substrata. This model provides a conceptual framework in which to conduct future studies involving variability in settlement decisions among individual larvae, and in which to consider the selective forces driving the evolution of specific larval settlement cues. Our results suggest that a combination of the maximum search period and the relative frequency and quality of optimal habitat likely exert the greatest influence on the evolution of larval selectivity in the field

Maximizing a new quantity in sequential reserve selection

The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. Numerous empirical studies support the notion that defining and measuring objectives in terms of species richness (where the value of a site is equal to the number of species it contains, or contributes to an existing reserve network) can be inadequate for maintaining biodiversity in the long term. An existing site-assessment framework that implicitly maximized the persistence probability of multiple species was integrated with a dynamic optimization model. The problem of sequential reserve selection as a Markov decision process was combined with stochastic dynamic programming to find the optimal solution. The approach represents a compromise between representation-based approaches (maximizing occurrences) and more complex tools, like spatially-explicit population models. The method, the inherent problems and interesting conclusions are illustrated with a land acquisition case study on the central Platte River

Stochastic Variation in Food Availability Influences Weight and Age at Maturity

Variation in mean food availability, and in the variance around the mean, affects the growth rate during development. Previous theoretical work on the influence of environmental quality or growth rates on the phenotypic traits age and size at maturation assumed that there is no variation in growth rate or food availability within a generation. We develop a stochastic dynamic programming (SDP) model of the foraging behavior of aphidophagous syrphids, and use this model to predict when syrphids should pupate (mature) when average food availability changes, or varies stochastically, during development. The optimal strategy takes into account not only the availability of food, but also the timing of its availability. Food availability, when small, influences developmental time, but not weight at pupation. Food availability, when large, influences weight at pupation, but not developmental time. When the food supply is low, the optimal strategy adjusts the size at pupation downwards for stochastic as opposed to deterministic availability of food. The conclusions reinforce the need for lifehistory studies to consider state dependence and short-term variability in growth rates

Stochastic Variation in Food Availability Influences Weight and Age at Maturity

Variation in mean food availability, and in the variance around the mean, affects the growth rate during development. Previous theoretical work on the influence of environmental quality or growth rates on the phenotypic traits age and size at maturation assumed that there is no variation in growth rate or food availability within a generation. We develop a stochastic dynamic programming (SDP) model of the foraging behavior of aphidophagous syrphids, and use this model to predict when syrphids should pupate (mature) when average food availability changes, or varies stochastically, during development. The optimal strategy takes into account not only the availability of food, but also the timing of its availability. Food availability, when small, influences developmental time, but not weight at pupation. Food availability, when large, influences weight at pupation, but not developmental time. When the food supply is low, the optimal strategy adjusts the size at pupation downwards for stochastic as opposed to deterministic availability of food. The conclusions reinforce the need for lifehistory studies to consider state dependence and short-term variability in growth rates

Abundance estimation from multiple data types for groupliving animals: An example using dhole (Cuon alpinus)

Large carnivores are declining globally and require baseline population estimates for management, however large-scale population estimation is problematic for species without unique natural marks. We used camera trap records of dhole Cuon alpinus, a group-living species, from three national parks in Thailand as a case study in which we develop integrated likelihood models to estimate abundance incorporating two different data sets, count data and detection/non-detection data. We further investigated relative biases of the models using different proportions of data with lower versus higher quality and assessed parameter identifiability. The simulations indicated that the relative bias on average across 24 tested scenarios was 2% with a 95% chance that the simulated data sets obtained the true animal abundances. We found that bias was high (\u3e10%) when sampling 60 sites with only 5 sampling occasions. We tested four additional scenarios with varying proportions of count data. Our model tolerated the use of relatively low proportions of the higher quality count data, but below 10% the results began to show bias (\u3e6%). Data cloning indicated that the parameters were identifiable with all posterior variances shrinking to near zero. Our model demonstrates the benefits of combining data from multiple studies even with different data types. Furthermore, the approach is not limited to camera trap data. Detection/non-detection data from track surveys or counts from transects could also be combined. Particularly, our model is potentially useful for assessing populations of rare species where large amounts of by-catch datasets are available

Inferring process from pattern: Can territory occupancy provide information about life history parameters?

A significant problem in wildlife management is identifying "good" habitat for species within the short time frames demanded by policy makers. Statistical models of the response of species presence/absence to predictor variables are one solution, widely known as habitat modeling. We use a "virtual ecologist" to test logistic regression as a means of developing habitat models within a spatially explicit, individual-based simulation that allows habitat quality to influence either fecundity or survival with a continuous scale. The basic question is how good are logistic regression models of habitat quality at identifying habitat where birth rates are high and death rates low (i.e., "source" habitat)? We find that, even when all the important variables are perfectly measured, and there is no error in surveying the species of interest, demographic stochasticity and the limiting effect of localized dispersal generally prevent an explanation of much more than half of the variation in territory occupancy as a function of habitat quality. This is true regardless of whether fecundity or survival is influenced by habitat quality. In addition, habitat models only detect a significant effect of habitat on territory occupancy when habitat quality is spatially autocorrelated. We find that habitat models based on logistic regression really measure the ability of the species to reach and colonize areas, not birth or death rates

CHANNEL WIDTH AND LEAST TERN AND PIPING PLOVER NESTING INCIDENCE ON THE LOWER PLATTE RIVER, NEBRASKA

Endangered interior least terns (Sternula antillarum athalassos) and threatened northern Great Plains piping plovers (Charadrius melodus) nest together on midstream sandbars in large rivers in the interior of North America. We investigated the relationship between river channel width and tern and plover nesting incidence on the lower Platte River, Nebraska, using a model-based logistic regression analysis. Multiple channel width measurements and a long-term nesting data set were used in the analysis. Nesting incidence was positively associated with increasing river channel width proximal to the nesting site. At a greater distance, up to 802 m away from the nesting site, there was no relationship with channel width. Managers and regulators should use these results to aid decisions pertaining to habitat creation and assessing impacts of future projects. Future research should address whether relationships exist between river channel width and nest counts and reproductive rates of interior least tern and piping plovers on the lower Platte River

CHANNEL WIDTH AND LEAST TERN AND PIPING PLOVER NESTING INCIDENCE ON THE LOWER PLATTE RIVER, NEBRASKA

Endangered interior least terns (Sternula antillarum athalassos) and threatened northern Great Plains piping plovers (Charadrius melodus) nest together on midstream sandbars in large rivers in the interior of North America. We investigated the relationship between river channel width and tern and plover nesting incidence on the lower Platte River, Nebraska, using a model-based logistic regression analysis. Multiple channel width measurements and a long-term nesting data set were used in the analysis. Nesting incidence was positively associated with increasing river channel width proximal to the nesting site. At a greater distance, up to 802 m away from the nesting site, there was no relationship with channel width. Managers and regulators should use these results to aid decisions pertaining to habitat creation and assessing impacts of future projects. Future research should address whether relationships exist between river channel width and nest counts and reproductive rates of interior least tern and piping plovers on the lower Platte River