Land Cover Classification of Complex Agroecosystems in the Non-Protected Highlands of the Galapagos Islands

The humid highlands of the Galapagos are the islands’ most biologically productive regions and a key habitat for endemic animal and plant species. These areas are crucial for the region’s food security and for the control of invasive plants, but little is known about the spatial distribution of its land cover. We generated a baseline high-resolution land cover map of the agricultural zones and their surrounding protected areas. We combined the high spatial resolution of PlanetScope images with the high spectral resolution of Sentinel-2 images in an object-based classification using a RandomForest algorithm. We used images collected with an unmanned aerial vehicle (UAV) to verify and validate our classified map. Despite the astounding diversity and heterogeneity of the highland landscape, our classification yielded useful results (overall Kappa: 0.7, R2: 0.69) and revealed that across all four inhabited islands, invasive plants cover the largest fraction (28.5%) of the agricultural area, followed by pastures (22.3%), native vegetation (18.6%), food crops (18.3%), and mixed forest and pioneer plants (11.6%). Our results are consistent with historical trajectories of colonization and abandonment of the highlands. The produced dataset is designed to suit the needs of practitioners of both conservation and agriculture and aims to foster collaboration between the two areas

Human Ecology of a Species Introduction: Interactions Between Humans and Introduced Green Iguanas in a Puerto Rican Urban Estuary

This paper reports results of interdisciplinary research between anthropologists and wildlife ecologists about the interactions between people and introduced green iguanas (Iguana iguana) in the San Juan Bay Estuary in Puerto Rico. Non-indigenous, introduced species and their impact on invaded ecosystems, including humans, are a worldwide environmental concern. Humans are the dominant species in most world ecosystems, and, thus, studying an introduced species\u27 interactions with people is of utmost importance to understand its impacts, make predictions, and inform environmental policy. Here, we detail some remarkable findings of our ongoing research in this topic, including (1) the spatial distribution of introduced green iguanas with respect to people\u27s activities and land uses, (2) the intracultural variation in attitudes and values regarding introduced iguanas and other introduced species in the study region, (3) local people\u27s knowledge about iguana diets in the estuary, and (4) the interactions between green iguanas and the tourism industry in Puerto Rico

Perceptional and socio-demographic factors associated with household drinking water management strategies in rural Puerto Rico.

Identifying which factors influence household water management can help policy makers target interventions to improve drinking water quality for communities that may not receive adequate water quality at the tap. We assessed which perceptional and socio-demographic factors are associated with household drinking water management strategies in rural Puerto Rico. Specifically, we examined which factors were associated with household decisions to boil or filter tap water before drinking, or to obtain drinking water from multiple sources. We find that households differ in their management strategies depending on the institution that distributes water (i.e. government PRASA vs community-managed non-PRASA), perceptions of institutional efficacy, and perceptions of water quality. Specifically, households in PRASA communities are more likely to boil and filter their tap water due to perceptions of low water quality. Households in non-PRASA communities are more likely to procure water from multiple sources due to perceptions of institutional inefficacy. Based on informal discussions with community members, we suggest that water quality may be improved if PRASA systems improve the taste and odor of tap water, possibly by allowing for dechlorination prior to distribution, and if non-PRASA systems reduce the turbidity of water at the tap, possibly by increasing the degree of chlorination and filtering prior to distribution. Future studies should examine objective water quality standards to identify whether current management strategies are effective at improving water quality prior to consumption

Land Cover Classification of Complex Agroecosystems in the Non-Protected Highlands of the Galapagos Islands

The humid highlands of the Galapagos are the islands’ most biologically productive regions and a key habitat for endemic animal and plant species. These areas are crucial for the region’s food security and for the control of invasive plants, but little is known about the spatial distribution of its land cover. We generated a baseline high-resolution land cover map of the agricultural zones and their surrounding protected areas. We combined the high spatial resolution of PlanetScope images with the high spectral resolution of Sentinel-2 images in an object-based classification using a RandomForest algorithm. We used images collected with an unmanned aerial vehicle (UAV) to verify and validate our classified map. Despite the astounding diversity and heterogeneity of the highland landscape, our classification yielded useful results (overall Kappa: 0.7, R2: 0.69) and revealed that across all four inhabited islands, invasive plants cover the largest fraction (28.5%) of the agricultural area, followed by pastures (22.3%), native vegetation (18.6%), food crops (18.3%), and mixed forest and pioneer plants (11.6%). Our results are consistent with historical trajectories of colonization and abandonment of the highlands. The produced dataset is designed to suit the needs of practitioners of both conservation and agriculture and aims to foster collaboration between the two areas

Importance of Each Covariate for Model Fit in the Two Models that Predict Household Water Management Strategies.

<p>Change in AIC_c for each of the covariates considered in the full logit model for the number of drinking water sources (A) and whether households treat or do not treat water (B). Larger changes in AIC_c values suggest that the variable contributed more to overall model fit. In both analyses (A and B), the institutional variable Water System (i.e. PRASA, non-PRASA) is the variable that contributes most to overall model fit. In the analysis of whether households treat water (B), water quality perceptions were also an important variable.</p

Comparison of each variable considered in our statistical models by institution type (PRASA vs non-PRASA).

<p>Mean value by institution (i.e. PRASA, Non-PRASA) and ANOVA results (degrees of freedom, F-statistic, p-value) are reported for each variable. * indicates p<0.05.</p

Map of Study Region in Puerto Rico.

<p>Municipalities where surveys were conducted are highlighted in gray. We did not list specific communities that we visited to keep the communities we surveyed anonymous.</p

Description and hypothesized relationship for each of the variables considered in our statistical models.

<p>Variable, coding method, description, and the hypothesized relationship with the likelihood of adopting coping strategies for all covariates considered in both statistical models. A positive relationship indicates that the variable would lead to increased coping, as defined by a higher likelihood of treating water and obtaining water from multiple sources.</p