Bordado a Mano: Testimonio de la Vida de un Maestro (Stitched by Hand: Testimonio of an Educator)

In the United States there is a shortage of teachers of color. The shortage is exasperated through a lack of funding in education, racism in K-12 classrooms, and through non-inclusive traditional teacher preparation programs. One of the methods thought to increase recruitment, improve teacher training, and increase retention of teachers of color is through the creation of Grow You Own teacher preparation programs. Grow Your Own programs were created as alternative to traditional teacher preparation programs as they are in community colleges, placed in rural communities, and have a focus on culturally responsive pedagogy. There is a lack of research on the effectiveness of Grow Your Own programs and their retention of teachers of color. Therefore, this study explored how a Latinx teacher candidate experienced his education at a Grow Your Own teacher preparation program. Through using testimonio and counterstory single case study, I used in depth plática to best understand how a Latinx teacher candidate used bi-cultural acculturation strategies to navigate his educational journey. The findings showed that to recruit and retain teacher candidates of color, Grow Your Own programs must ensure that teacher candidates feel connected to the faculty, staff, cohort, curriculum, and community. If teacher candidates do not feel a sense of connection they will be forced to move into using survival mode bi-cultural acculturation strategies which in turn lead to lower retention rates, lowered academic success, and a decrease of institutional connection. Finally, the implications of the study suggested that Grow Your Own programs need to first create connection with the community to best understand the population needs. Second, programs must ensure that staff and faculty are trained in culturally responsive pedagogy to best serve teacher candidates. And third, programs must create a culture of acceptance and inclusion so that teacher candidates of color feel safe enough to learn and succeed in their program

Recruitment limitation in three large‐seeded plant species in a tropical moist forest

Recruitment limitation—the failure of a species to establish recruits at an available site—is a potential determinant of plant communities’ structure, causing local communities to be a limited subset of the regional species pool. Recruitment limitation results from three mechanisms: (i) lack of seed sources (i.e., source limitation), (ii) failure of available seeds to reach recruitment sites (i.e., dispersal limitation), and (iii) failure of arrived seeds to establish at a location (i.e., establishment limitation). Here, we evaluated the relative importance of these mechanisms in three co-occurring tree species (Dipteryx oleifera, Attalea butyracea, and Astrocaryum standleyanum) that share seed dispersers/predators. The study was set up on Barro Colorado Island (Panama) at 62 one-ha sites with varying tree densities. Source limitation was estimated as the proportion of sites that would be reached by seeds if seeds were distributed uniformly. Dispersal limitation was estimated from the number of sites with seeds in the soil bank. Establishment limitation was evaluated by measuring germination and 1-year survival in seed addition experiments. The effect of conspecific and heterospecific densities on the mechanisms was evaluated at three spatial scales (1, 5, and 9 ha). For all species, seed predation was the most important recruitment component (~80% decrease in seed survival). Establishment varied among species and was affected by conspecific and heterospecific species densities across spatial scales. Given that species identity, distribution, and seed dispersal/predation affect recruitment at multiple scales, multiscale studies are required to understand how recruitment limitation determines community structure in tropical forests

Estimation of the Distribution of Tabebuia guayacan (Bignoniaceae) Using High-Resolution Remote Sensing Imagery

Species identification and characterization in tropical environments is an emerging field in tropical remote sensing. Significant efforts are currently aimed at the detection of tree species, of levels of forest successional stages, and the extent of liana occurrence at the top of canopies. In this paper we describe our use of high resolution imagery from the Quickbird Satellite to estimate the flowering population of Tabebuia guayacan trees at Barro Colorado Island (BCI), in Panama. The imagery was acquired on 29 April 2002 and 21 March 2004. Spectral Angle Mapping via a One-Class Support Vector machine was used to detect the presence of 422 and 557 flowering tress in the April 2002 and March 2004 imagery. Of these, 273 flowering trees are common to both dates. This study presents a new perspective on the effectiveness of high resolution remote sensing for monitoring a phenological response and its use as a tool for potential conservation and management of natural resources in tropical environments

Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests

The theory of metabolic ecology predicts specific relationships among tree stem diameter, biomass, height, growth and mortality. As demographic rates are important to estimates of carbon fluxes in forests, this theory might offer important insights into the global carbon budget, and deserves careful assessment. We assembled data from 10 old-growth tropical forests encompassing censuses of 367 ha and > 1.7 million trees to test the theory's predictions. We also developed a set of alternative predictions that retained some assumptions of metabolic ecology while also considering how availability of a key limiting resource, light, changes with tree size. Our results show that there are no universal scaling relationships of growth or mortality with size among trees in tropical forests. Observed patterns were consistent with our alternative model in the one site where we had the data necessary to evaluate it, and were inconsistent with the predictions of metabolic ecology in all forests

A data science challenge for converting airborne remote sensing data into ecological information

Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to converting images into information on individual trees: (1) crown segmentation, for identifying the location and size of individual trees; (2) alignment, to match ground truthed trees with remote sensing; and (3) species classification of individual trees. Six teams (composed of 16 individual participants) submitted predictions for one or more tasks. The crown segmentation task proved to be the most challenging, with the highest-performing algorithm yielding only 34% overlap between remotely sensed crowns and the ground truthed trees. However, most algorithms performed better on large trees. For the alignment task, an algorithm based on minimizing the difference, in terms of both position and tree size, between ground truthed and remotely sensed crowns yielded a perfect alignment. In hindsight, this task was over simplified by only including targeted trees instead of all possible remotely sensed crowns. Several algorithms performed well for species classification, with the highest-performing algorithm correctly classifying 92% of individuals and performing well on both common and rare species. Comparisons of results across algorithms provided a number of insights for improving the overall accuracy in extracting ecological information from remote sensing. Our experience suggests that this kind of competition can benefit methods development in ecology and biology more broadly

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o