Community-based participatory research helps farmers and scientists to manage invasive pests in the Ecuadorian Andes

Economic costs of biological invasions in Ecuador: the importance of the Galapagos Islands

Biological invasions, as a result of human intervention through trade and mobility, are the second biggest cause of biodiversity loss. The impacts of invasive alien species (IAS) on the environment are well known, however, economic impacts are poorly estimated, especially in mega-diverse countries where both economic and ecological consequences of these effects can be catastrophic. Ecuador, one of the smallest mega-diverse countries, lacks a comprehensive description of the economic costs of IAS within its territory. Here, using "InvaCost", a public database that compiles all recorded monetary costs associated with IAS from English and Non-English sources, we investigated the economic costs of biological invasions. We found that between 1983 and 2017, the reported costs associated with biological invasions ranged between US$86.17 million (when considering only the most robust data) and US$626 million (when including all cost data) belonging to 37 species and 27 genera. Furthermore, 99% of the recorded cost entries were from the Galapagos Islands. From only robust data, the costliest identified taxonomic group was feral goats (Capra hircus; US$20 million), followed by Aedes mosquitoes (US$2.14 million) while organisms like plant species from the genus Rubus, a parasitic fly (Philornis downsi), black rats (Rattus rattus) and terrestrial gastropods (Achatina fulica) represented less than US$2 million each. Costs of "mixed-taxa" (i.e. plants and animals) represented the highest (61% of total robust costs; US$52.44 million). The most impacted activity sector was the national park authorities, which spent about US$84 million. Results from robust data also revealed that management expenditures were the major type of costs recorded in the Galapagos Islands; however, costs reported for medical losses related to Aedes mosquitoes causing dengue fever in mainland Ecuador would have ranked first if more detailed information had allowed us to categorize them as robust data. Over 70% of the IAS reported for Ecuador did not have reported costs. These results suggest that costs reported here are a massive underestimate of the actual economic toll of invasions in the country.

Survey on Using Ethical Principles in Environmental Field Research with Place-Based Communities

Researchers of the Northeast Ethics Education Partnership (NEEP) at Brown University sought to improve an understanding of the ethical challenges of field researchers with place-based communities in environmental studies/sciences and environmental health by disseminating a questionnaire which requested information about their ethical approaches to these researched communities. NEEP faculty sought to gain actual field guidance to improve research ethics and cultural competence training for graduate students and faculty in environmental sciences/studies. Some aspects of the ethical challenges in field studies are not well-covered in the literature. More training and information resources are needed on the bioethical challenges in environmental field research relating to maximizing benefits/reducing risks to local inhabitants and ecosystems from research; appropriate and effective group consent and individual consent processes for many diverse communities in the United States and abroad; and justice considerations of ensuring fair benefits and protections against exploitation through community-based approaches, and cultural appropriateness and competence in researcher relationships.

Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species abundances. In conclusion, keeping in mind that the mismatch between the size of organisms and the scale at which climate data are collected and modeled remains a key issue, temperature dataset selection should be balanced by the desired output spatiotemporal scale for better predicting pest dynamics and developing efficient pest management strategies.

A New Method for Post-introduction Risk Assessment of Biological Invasions Among Introduced Shrubs in Developing Countries

Risk-assessment methods are useful in collecting data that can help decision making to prevent the introduction of new species that have the potential of invading as well as in management of established taxa. Not only the complexity and unaffordability of available pre-introduction risk-assessment models make them rarely or inconsistently applied in the least-developed countries, but also there is lack of tools to assess the status of already introduced plant species. In this study, an affordable and rapid method of assessment of invasiveness among introduced plant species was developed and tested in Rwanda. This method defines three invasion stages (potential, effective, and suppressive invaders) and four levels of risk assessment: post-introduction assessment of species inherent invasive potential (Level 1), post-establishment assessment of species capacity of regeneration (Level 2), post-naturalization assessment of species range of occurrence and ability for long-distance dispersal (Level 3), and post-naturalization assessment of species ability to outcompete other plants in the community and transform the landscape (Level 4). A review of invasive species in Rwanda was developed through desk review, examination of herbarium records, and vegetation surveys. This method should be applicable in other countries that lack the means for a more conventional scientific investigation or under any circumstance where a quick and inexpensive assessment is needed. The method could be useful to environmental managers for timely intervention with strategies specific to different stages of invasion (post-introduction, post-establishment, or post-naturalization) and allocate resources accordingly.

Stakeholder perceptions and practices regarding Prosopis (mesquite) invasions and management in South Africa

Invasive alien trees impact the environment and human livelihoods. The human dimensions of such invasions are less well understood than the ecological aspects, and this is hindering the development of effective management strategies. Semi-structured interviews were undertaken to investigate the knowledge and perceptions of Prosopis between different stakeholder groups. Chi-squared tests, Welch ANOVAs, and Principle Component Analyses were run. Factors such as land tenure and proximity to invasions were especially important for explaining differences in perceptions and practices relating to Prosopis among different stakeholder groups. Most respondents were aware of Prosopis and considered it to be invasive (i.e., spreading). Costs associated with Prosopis were perceived to exceed benefits, and most stakeholders wanted to see a reduction in the abundance of Prosopis stands. The mean total cost for the management of Prosopis was US$ 1914 year(-1) per farm, where costs ranged from under US$ 10 to over UD$ 500 per ha based on invasion densities and objectives for control. The findings highlight the need for more effective management interventions.

Promoting human subjects training for place-based communities and cultural groups in environmental research: curriculum approaches for graduate student/faculty training

A collaborative team of environmental sociologists, community psychologists, religious studies scholars, environmental studies/science researchers and engineers has been working together to design and implement new training in research ethics, culture and community-based approaches for place-based communities and cultural groups. The training is designed for short and semester-long graduate courses at several universities in the northeastern US. The team received a 3 year grant from the US National Science Foundation's Ethics Education in Science and Engineering in 2010. This manuscript details the curriculum topics developed that incorporate ethical principles, particularly for group protections/benefits within the field practices of environmental/engineering researchers.

Changes in the distribution of multispecies pest assemblages affect levels of crop damage in warming tropical Andes

Climate induced species range shifts might create novel interactions among species that may outweigh direct climatic effects. In an agricultural context, climate change might alter the intensity of competition or facilitation interactions among pests with, potentially, negative consequences on the levels of damage to crop. This could threaten the productivity of agricultural systems and have negative impacts on food security, but has yet been poorly considered in studies. In this contribution, we constructed and evaluated process-based species distribution models for three invasive potato pests in the Tropical Andean Region. These three species have been found to co-occur and interact within the same potato tuber, causing different levels of damage to crop. Our models allowed us to predict the current and future distribution of the species and therefore, to assess how damage to crop might change in the future due to novel interactions. In general, our study revealed the main challenges related to distribution modeling of invasive pests in highly heterogeneous regions. It yielded different results for the three species, both in terms of accuracy and distribution, with one species surviving best at lower altitudes and the other two performing better at higher altitudes. As to future distributions our results suggested that the three species will show different responses to climate change, with one of them expanding to higher altitudes, another contracting its range and the other shifting its distribution to higher altitudes. These changes will result in novel areas of co-occurrence and hence, interactions of the pests, which will cause different levels of damage to crop. Combining population dynamics and species distribution models that incorporate interspecific trade-off relationships in different environments revealed a powerful approach to provide predictions about the response of an assemblage of interacting species to future environmental changes and their impact on process rates.

Strong discrepancies between local temperature mapping and interpolated climatic grids in tropical mountainous agricultural landscapes

Bridging the gap between the predictions of coarse-scale climate models and the fine-scale climatic reality of species is a key issue of climate change biology research. While it is now well known that most organisms do not experience the climatic conditions recorded at weather stations, there is little information on the discrepancies between microclimates and global interpolated temperatures used in species distribution models, and their consequences for organisms' performance. To address this issue, we examined the fine-scale spatiotemporal heterogeneity in air, crop canopy and soil temperatures of agricultural landscapes in the Ecuadorian Andes and compared them to predictions of global interpolated climatic grids. Temperature time-series were measured in air, canopy and soil for 108 localities at three altitudes and analysed using Fourier transform. Discrepancies between local temperatures vs. global interpolated grids and their implications for pest performance were then mapped and analysed using GIS statistical toolbox. Our results showed that global interpolated predictions over-estimate by 77.5 ± 10% and under-estimate by 82.1 ± 12% local minimum and maximum air temperatures recorded in the studied grid. Additional modifications of local air temperatures were due to the thermal buffering of plant canopies (from -2.7 °K during daytime to 1.3 °K during night-time) and soils (from -4.9 °K during daytime to 6.7 °K during night-time) with a significant effect of crop phenology on the buffer effect. This discrepancies between interpolated and local temperatures strongly affected predictions of the performance of an ectothermic crop pest as interpolated temperatures predicted pest growth rates 2.3-4.3 times lower than those predicted by local temperatures. This study provides quantitative information on the limitation of coarse-scale climate data to capture the reality of the climatic environment experienced by living organisms. In highly heterogeneous region such as tropical mountains, caution should therefore be taken when using global models to infer local-scale biological processes.

Context and group dynamics in a CBPR-developed HIV prevention intervention

This paper will explore in detail the effects of context and group dynamics on the development of a multi-level community-based HIV prevention intervention for crack cocaine users in the San Salvador Metropolitan Area, El Salvador. Community partners included residents from marginal communities, service providers from the historic center of San Salvador and research staff from a non-profit organization. The community contexts from which partners came varied considerably and affected structural group dynamics, i.e. who was identified as community partners, their research and organizational capacity, and their ability to represent their communities, with participants from marginal communities most likely to hold community leadership positions and be residents, and those from the center of San Salvador most likely to work in religious organizations dedicated to HIV prevention or feeding indigent drug users. These differences also affected the intervention priorities of different partners. The context of communities changed over time, particularly levels of violence, and affected group dynamics and the intervention developed. Finally, strategies were needed to elicit input from stakeholders under-represented in the community advisory board, in particular active crack users, in order to check the feasibility of the proposed intervention and revise it as necessary. Because El Salvador is a very different context than that in which most CBPR studies have been conducted, our results reveal important contextual factors and their effects on partnerships not often considered in the literature.

Modeling temperature-dependent survival with small datasets: insights from tropical mountain agricultural pests

Many regions are increasingly threatened by agricultural pests but suffer from a lack of data that hampers the development of adequate population dynamics models that could contribute to pest management strategies. Here, we present a new model relating pest survival to temperature and compare its performance with two published models. We were particularly interested in their ability to simulate the deleterious effect of extreme temperatures even when adjusted to datasets that did not include extreme temperature conditions. We adjusted the models to survival data of three species of potato tuber moth (PTM), some major pests in the Tropical Andes. To evaluate model performance, we considered both goodness-of-fit and robustness. The latter consisted in evaluating their ability to predict the actual altitudinal limits of the species in the Ecuadorian Andes. We found that even though our model did not always provide the best fit to data, it predicted extreme temperature mortality and altitudinal limits accurately and better than the other two models. Our study shows that the ability to accurately represent the physiological limits of species is important to provide robust predictions of invasive pests' potential distribution, particularly in places where temperatures approach lethal extremes. The value of our model lies in its ability to simulate accurate thermal tolerance curves even with small datasets, which is useful in places where adequate pest management is urgent but data are scarce.

A socio-ecological investigation of options to manage groundwater degradation in the Western Desert, Egypt

Under increasing water scarcity, collective groundwater management is a global concern. This article presents an interdisciplinary analysis of this challenge drawing on a survey including 50 large and small farms and gardens in a village in an agricultural land reclamation area on the edge of the Western Desert of Egypt. Findings revealed that smallholders rely on a practice of shallow groundwater use, through which drainage water from adjacent irrigation areas is effectively recycled within the surface aquifer. Expanding agroindustrial activities in the surrounding area are socio-economically important, but by mining non-renewable water in the surrounding area, they set in motion a degradation process with social and ecological consequences for all users in the multi-layered aquifer system. Based on the findings of our investigation, we identify opportunities for local authorities to more systematically connect available environmental information sources and common pool resource management precedents, to counterbalance the degradation threat.

Coupled information diffusion--pest dynamics models predict delayed benefits of farmer cooperation in pest management programs

Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' “diffusion of innovation theory”. In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.

Food security of millions of people in the third world has faced a growing number of challenges in recent years including risks associated with emergent agricultural pests. Worldwide, the promotion of integrated pest management practices has been heavily promoted through participative methodologies relying on farmer cooperation to share pest control information. Recent studies have put into doubt the efficiency of such methodologies evoking our poor knowledge of farmers' perceptions, behavioral heterogeneity, and complex interaction with pest dynamics. While pest management programs have a larger place than ever on the international policy agenda, the debate concerning their efficiency at large scales has remained unresolved. Here, we developed an innovative modeling approach coupling pest control information diffusion and pest population dynamics to study the role of cooperation among farmers to share the information. We found that the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in pest control diffusion and applications. However, our model also predicts that if individuals learn from others about the benefits of early prevention of invasive pests, then a temporary educational effort may have a sustainable long-run impact.