A simulation model to explore the response of the Gulf of Maine food web to large-scale environmental and ecological changes

A dynamic simulation model was constructed using outputs from a balanced Gulf of Maine (GOM) energy budget model as the initial parameter set. The model was structured to provide a recipient control set of dynamics, largely based off of flows to and from different biological groups. The model was used to produce Monte Carlo simulations that were compared (percent change in biomass) with basecase simulations for a variety of scenarios. Changes in primary production, large increases in pelagic and demersal fish biomass, increases in fishing mortality, and large increases in top predators such as baleen whales and pinnepids were simulated. These scenarios roughly simulated the potential impacts of climate change, altered fishing pressure, additional protected species mitigations, and combinations thereof. Results suggest that the GOM system is primarily influenced by bottom-up processes involving phytoplankton, zooplankton, and bacterial biomass. Pelagic and demersal fish were important in determining trends in some of the scenarios. Marine mammals, large pelagic fish, and seabirds have a minor role in the GOM system in terms of biomass flows among the ecosystem components. The system is resilient to large-scale change due, in part to many predator–prey linkages. However, major alterations could occur from sustained climate change, high fishing rates, and by combinations of these types of external forcing mechanisms.     

Comparing network analysis methodologies for consumer–resource relations at species and ecosystems scales

This research compares two existing methodologies, mixed trophic impact analysis and utility analysis, which use network analysis to evaluate the direct, pair-wise, and indirect, holistic, ecological relations between ecosystem compartments. The two approaches have many similarities, but differ in some key assumptions which affect both the final results and interpretations. Here, we briefly introduce both methodologies through a series of two simple examples; a 3-compartment competition model and a 3-compartment food chain model, and then apply the methodologies to a 15-compartment ecosystem model of the Chesapeake Bay. This example demonstrates how implementing the various conceptual and methodological assumptions lead to differing results. Notably, the overall number of positive relations is greatly affected by the treatment of the self-interactions and the handling of detritus compartments lead to a distinction between ecological or trophic relations. We recommend slight changes to both methodologies, not necessarily in order to bring them completely together, but because each has some points which are stronger and better defensible.     

Occupancy Patterns of Regionally Declining Grassland Sparrow Populations in a Forested Pennsylvania Landscape

Organisms can be affected by processes in the surrounding landscape outside the boundary of habitat areas and by local vegetation characteristics. There is substantial interest in understanding how these processes affect populations of grassland birds, which have experienced substantial population declines. Much of our knowledge regarding patterns of occupancy and density stem from prairie systems, whereas relatively little is known regarding how occurrence and abundance of grassland birds vary in reclaimed surface mine grasslands. Using distance sampling and single‐season occupancy models, we investigated how the occupancy probability of Grasshopper (Ammodramus savannarum) and Henslow's Sparrows (A. henslowii) on 61 surface mine grasslands (1591 ha) in Pennsylvania changed from 2002 through 2011 in response to landscape, grassland, and local vegetation characteristics . A subset (n = 23; 784 ha) of those grasslands were surveyed in 2002, and we estimated changes in sparrow density and vegetation across 10 years. Grasshopper and Henslow's Sparrow populations declined 72% and 49%, respectively from 2002 to 2011, whereas overall woody vegetation density increased 2.6 fold. Henslow's Sparrows avoided grasslands with perimeter–area ratios ≥0.141 km/ha and woody shrub densities ≥0.04 shrubs/m². Both species occupied grasslands ≤13 ha, but occupancy probability declined with increasing grassland perimeter–area ratio and woody shrub density. Grassland size, proximity to nearest neighboring grassland ( = 0.2 km), and surrounding landscape composition at 0.5, 1.5, and 3.0 km were not parsimonious predictors of occupancy probability for either species. Our results suggest that reclaimed surface mine grasslands, without management intervention, are ephemeral habitats for Grasshopper and Henslow's Sparrows. Given the forecasted decline in surface coal production for Pennsylvania, it is likely that both species will continue to decline in our study region for the foreseeable future. Patrones de Ocupación de Poblaciones Regionalmente Declinantes de Gorriones de Pastizales en un Paisaje Boscoso de Pennsylvania     

Looking forward: Disasters at 40

This paper reflects on contemporary studies of and responses to disasters, highlighting the importance of historical, spatial, and intersectional modes of analysis, and draws on the author's ongoing research on Southern‐led and local community responses to displacement in the Middle East. Acknowledging the plurality of ‘international communities of response’, it begins by critiquing the depiction of selected responses to disasters as ‘positive’ ‘paradigm shifts’, including in reference to the ‘localisation of aid, and the United Nations’ Regional Refugee and Resilience Plan for Syria. Next it turns to three key themes that are central to disasters studies: migration; forced displacement; and Southern‐led responses to disasters. Among other things, the paper argues that exploring the principles and modalities of South–South cooperation, rather than promoting the incorporation of Southern actors into the ‘international humanitarian system’ via the localisation agenda, presents a critical opportunity for studies of and responses to disasters.     

Using a social–ecological framework to inform the implementation of conservation plans

One of the key determinants of success in biodiversity conservation is how well conservation planning decisions account for the social system in which actions are to be implemented. Understanding elements of how the social and ecological systems interact can help identify opportunities for implementation. Utilizing data from a large‐scale conservation initiative in southwestern of Australia, we explored how a social–ecological system framework can be applied to identify how social and ecological factors interact to influence the opportunities for conservation. Using data from semistructured interviews, an online survey, and publicly available data, we developed a conceptual model of the social–ecological system associated with the conservation of the Fitz‐Stirling region. We used this model to identify the relevant variables (remnants of vegetation, stakeholder presence, collaboration between stakeholders, and their scale of management) that affect the implementation of conservation actions in the region. We combined measures for these variables to ascertain how areas associated with different levels of ecological importance coincided with areas associated with different levels of stakeholder presence, stakeholder collaboration, and scales of management. We identified areas that could benefit from different implementation strategies, from those suitable for immediate conservation action to areas requiring implementation over the long term to increase on‐the‐ground capacity and identify mechanisms to incentivize implementation. The application of a social–ecological framework can help conservation planners and practitioners facilitate the integration of ecological and social data to inform the translation of priorities for action into implementation strategies that account for the complexities of conservation problems in a focused way.     

Golden Eagle fatalities and the continental‐scale consequences of local wind‐energy generation

Renewable energy production is expanding rapidly despite mostly unknown environmental effects on wildlife and habitats. We used genetic and stable isotope data collected from Golden Eagles (Aquila chrysaetos) killed at the Altamont Pass Wind Resource Area (APWRA) in California in demographic models to test hypotheses about the geographic extent and demographic consequences of fatalities caused by renewable energy facilities. Geospatial analyses of δ²H values obtained from feathers showed that ≥25% of these APWRA‐killed eagles were recent immigrants to the population, most from long distances away (>100 km). Data from nuclear genes indicated this subset of immigrant eagles was genetically similar to birds identified as locals from the δ²H data. Demographic models implied that in the face of this mortality, the apparent stability of the local Golden Eagle population was maintained by continental‐scale immigration. These analyses demonstrate that ecosystem management decisions concerning the effects of local‐scale renewable energy can have continental‐scale consequences.     

Divergence in sink contributions to population persistence

Population sinks present unique conservation challenges. The loss of individuals in sinks can compromise persistence; but conversely, sinks can improve viability by improving connectivity and facilitating the recolonization of vacant sources. To assess the contribution of sinks to regional population persistence of declining populations, we simulated source–sink dynamics for 3 very different endangered species: Black‐capped Vireos (Vireo atricapilla) at Fort Hood, Texas, Ord's kangaroo rats (Dipodomys ordii) in Alberta, and Northern Spotted Owls (Strix occidentalis caurina) in the northwestern United States. We used empirical data from these case studies to parameterize spatially explicit individual‐based models. We then used the models to quantify population abundance and persistence with and without long‐term sinks. The contributions of sink habitats varied widely. Sinks were detrimental, particularly when they functioned as strong sinks with few emigrants in declining populations (e.g., Alberta's Ord's kangaroo rat) and benign in robust populations (e.g., Black‐capped Vireos) when Brown‐headed Cowbird (Molothrus ater) parasitism was controlled. Sinks, including ecological traps, were also crucial in delaying declines when there were few sources (e.g., in Black‐capped Vireo populations with no Cowbird control). Sink contributions were also nuanced. For example, sinks that supported large, variable populations were subject to greater extinction risk (e.g., Northern Spotted Owls). In each of our case studies, new context‐dependent sinks emerged, underscoring the dynamic nature of sources and sinks and the need for frequent re‐assessment. Our results imply that management actions based on assumptions that sink habitats are generally harmful or helpful risk undermining conservation efforts for declining populations.     

The case for policy‐relevant conservation science

Drawing on the “evidence‐based” (Sutherland et al. 2013) versus “evidence‐informed” debate (Adams & Sandbrook 2013), which has become prominent in conservation science, I argue that science can be influential if it holds a dual reference (Lentsch & Weingart 2011) that contributes to the needs of policy makers whilst maintaining technical rigor. In line with such a strategy, conservation scientists are increasingly recognizing the usefulness of constructing narratives through which to enhance the influence of their evidence (Leslie et al. 2013; Lawton & Rudd 2014). Yet telling stories alone is rarely enough to influence policy; instead, these narratives must be policy relevant. To ensure that evidence is persuasive alongside other factors in a complex policy‐making process, conservation scientists could follow 2 steps: reframe within salient political contexts and engage more productively in boundary work, which is defined as the ways in which scientists “construct, negotiate, and defend the boundary between science and policy” (Owens et al. 2006:640). These will both improve the chances of evidence‐informed conservation policy.     

Geography of conservation spending,biodiversity, and culture

We used linear and multivariate models to examine the associations between geography, biodiversity, per capita economic output, national spending on conservation, governance, and cultural traits in 55 countries. Cultural traits and social metrics of modernization correlated positively with national spending on conservation. The global distribution of this spending culture was poorly aligned with the distribution of biodiversity. Specifically, biodiversity was greater in the tropics where cultures tended to spend relatively less on conservation and tended to have higher collectivism, formalized and hierarchical leadership, and weaker governance. Consequently, nations lacking social traits frequently associated with modernization, environmentalism, and conservation spending have the largest component of Earth's biodiversity. This has significant implications for setting policies and priorities for resource management given that biological diversity is rapidly disappearing and cultural traits change slowly. Therefore, we suggest natural resource management adapt to and use characteristics of existing social organization rather than wait for or promote social values associated with conservation spending. Supporting biocultural traditions, engaging leaders to increase conservation commitments, cross‐national efforts that complement attributes of cultures, and avoiding interference with nature may work best to conserve nature in collective and hierarchical societies. Spending in modernized nations may be a symbolic response to a symptom of economic development and environmental degradation, and here conservation actions need to ensure that biodiversity is not being lost.     

SOME SIMPLE MODELS FOR CONTINUOUS VARIATE TIME SERIES1

ABSTRACT: A survey is given of recently developed models for continuous variate non–Gaussian time series. The emphasis is on marginally specific models with given correlation structure. Exponential, Gamma, Weibull, Laplace, Beta and Mixed Exponential models are considered for the marginal distributions of the stationary time series. Most of the models are random coefficient, additive linear models. Some discussion of the meaning of autoregression and linearity is given, as well as suggestions for higher–order linear residual analysis for non–Gaussian models.