The role of insects in the productivity decline of cassava (Manihot esculenta Crantz) on a slash and burn site in the amazon territory of Venezuela

The consumption of bitter cassava by root boring, leaf chewing and leaf sucking insects was measured on a slash and burn agricultural site in the Amazon Territory of Venezuela. Chewing and boring insects consumed less than 3% of the tissue, possibly because of the presence of cyanogenic glucosides in the cassava plants. In contrast to the boring and chewing insects, leaf sucking insects were more effective herbivores. They may be able to consume the phloem sap without activating the hydrocyanic acid. However, even sucking insects consumed only about 14% of the phosphorus uptake of the plants. We conclude that insect herbivory did not play a major role in the decline of productivity on the slash and burn agricultural site.     

Element content in tissues of four rodent species sampled in the Geysers geothermal steamfield

Liver and kidney tissue samples from four rodent species collected in the Geysers geothermal steamfield of northern California were analyzed for content of 28 elements. Element concentrations in samples from the developed region of the Geysers were compared with samples from undeveloped reference regions to determine the influence of geothermal power development on element content in small mammal tissues. Eight elements (B, Ca, Cu, Mg, Mn, P, Sr, Ti) were enriched in samples from the Geysers, 12 (Ag, Al, Co, Cr, Fe, K, Mo, Na, Ni, Pb, Si, Zn) were decreased within the Geysers, Ba and Li were inconclusive, and six (As, Be, Cd, Hg, Sn, V) were below the minimum analytical limits. The longest-lived species (Neotoma fuscipes) had the greatest occurrence of statistically significant differences in element content. Sites in grassland habitat produced more significant differences in element content than either chaparral or streamside habitats for samples from Peromyscus maniculatus. Peromyscus boylii and P. truei provided additional data, but no distinct advantages for element monitoring. The data indicate regional influences from geothermal power development on element levels in rodent tissues.     

Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation

Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual‐based learning, stresses collaborative and generative insight making and is well‐suited for adaptive management. Adaptive‐management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real‐time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case‐study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy‐in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning.     

Addressing inequality and intolerance in human–wildlife coexistence

Millennia of human conflict with wildlife have built a culture of intolerance toward wildlife among some stakeholders. We explored 2 key obstacles to improved human–wildlife coexistence: coexistence inequality (how the costs and benefits of coexisting with wildlife are unequally shared) and intolerance. The costs of coexisting with wildlife are often disproportionately borne by the so-called global south and rural communities, and the benefits often flow to the global north and urban dwellers. Attitudes and behaviors toward wildlife (tolerance versus intolerance) vary with social and cultural norms. We suggest more empathetic advocacy is needed that, for example, promotes conservation while appropriately considering those who bear the costs of conflict with wildlife. To achieve more equitable cost-sharing, we suggest limiting the costs incurred by those most affected or by sharing those costs more widely. For example, we advocate for the development of improved wildlife compensation schemes, increasing the scale of rewilding efforts, and preventing wildlife-derived revenue leaching out of the local communities bearing the costs of coexistence.     

The Scaling of Water Governance Tasks: A Comparative Federal Analysis of the European Union and Australia

Conflicts over how to “scale” policy-making tasks have characterized environmental governance since time immemorial. They are particularly evident in the area of water policy and raise important questions over the democratic legitimacy, economic efficiency and effectiveness of allocating (or “scaling”) tasks to some administrative levels as opposed to others. This article adopts a comparative federalism perspective to assess the “optimality” of scaling—either upward or downward—in one issue area, namely coastal recreational water quality. It does so by comparing the scaling of recreational water quality tasks in the European Union (EU) and Australia. It reveals that the two systems have adopted rather different approaches to scaling and that this difference can partly be accounted for in federal theoretical terms. However, a much greater awareness of the inescapably political nature of scaling processes is nonetheless required. Finally, some words of caution are offered with regard to transferring policy lessons between these two jurisdictions.     

Using Multiple Watershed Models to Predict Water,Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

Boomer, Kathleen M.B., Donald E. Weller, Thomas E. Jordan, Lewis Linker, Zhi‐Jun Liu, James Reilly, Gary Shenk, and Alexey A. Voinov, 2012. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary. Journal of the American Water Resources Association (JAWRA) 1‐25. DOI: 10.1111/j.1752‐1688.2012.00689.x Abstract: We analyzed an ensemble of watershed models that predict flow, nitrogen, and phosphorus discharges. The models differed in scope and complexity and used different input data, but all had been applied to evaluate human impacts on discharges to the Patuxent River or to the Chesapeake Bay. We compared predictions to observations of average annual, annual time series, and monthly discharge leaving three basins. No model consistently matched observed discharges better than the others, and predictions differed as much as 150% for every basin. Models that agreed best with the observations in one basin often were among the worst models for another material or basin. Combining model predictions into a model average improved overall reliability in matching observations, and the range of predictions helped describe uncertainty. The model average was not the closest to the observed discharge for every material, basin, and time frame, but the model average had the highest Nash–Sutcliffe performance across all combinations. Consistently poor performance in predicting phosphorus loads suggests that none of the models capture major controls. Differences among model predictions came from differences in model structures, input data, and the time period considered, and also to errors in the observed discharge. Ensemble watershed modeling helped identify research needs and quantify the uncertainties that should be considered when using the models in management decisions.