Modelling the conversion of Colombian lowland ecosystems since 1940: Drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/- 9.2) ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation. (c) 2005 Elsevier Ltd. All rights reserved.

VGI quality control

This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i.e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future.

Forecasting enrollment in differential assessment programs using cellular automata

Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellular-automata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban growth but also other forms of land-use and land-cover change, but like other models must be fed important information about which particular lands in the modeled area are available for development. Some of these lands are in categories for the purpose of excluding urban growth that are difficult to quantify since their function is dictated by policy. One such category includes voluntary differential assessment programs, whereby farmers agree not to develop their lands in exchange for significant tax breaks. Since they are voluntary, today’s excluded lands may be available for development at some point in the future. Mapping the shifting mosaic of parcels that are enrolled in such programs allows this information to be used in modeling and forecasting. In this study, we added information about California’s Williamson Act into SLEUTH’s excluded layer for Tulare County. Assumptions about the voluntary differential assessments were used to create a sophisticated excluded layer that was fed into SLEUTH’s urban growth forecasting routine. The results demonstrate not only a successful execution of this method but also yielded high goodness-of-fit metrics for both the calibration of enrollment termination as well as the urban growth modeling itself.

Ecological Homogenization of Urban USA

A visually apparent but scientifically untested outcome of land-use change is homogenization across urban areas, where neighborhoods in different parts of the country have similar patterns of roads, residential lots, commercial areas, and aquatic features. We hypothesize that this homogenization extends to ecological structure and also to ecosystem functions such as carbon dynamics and microclimate, with continental-scale implications. Further, we suggest that understanding urban homogenization will provide the basis for understanding the impacts of urban land-use change from local to continental scales. Here, we show how multi-scale, multi-disciplinary datasets from six metropolitan areas that cover the major climatic regions of the US (Phoenix, AZ; Miami, FL; Baltimore, MD; Boston, MA; Minneapolis–St Paul, MN; and Los Angeles, CA) can be used to determine how household and neighborhood characteristics correlate with land-management practices, land-cover composition, and landscape structure and ecosystem functions at local, regional, and continental scales.

Connectivity of fragmented amphibian populations in a neotropical landscape

A high proportion of amphibian species are threatened with extinction globally, and habitat loss and degradation are the most frequently implicated causes. Rapid deforestation for the establishment of agricultural production is a primary driver of habitat loss in tropical zones where amphibian diversity is highest. Land-cover change affects native assemblages, in part, through the reduction of habitat area and the reduction of movement among remnant populations. Decreased gene flow contributes to loss of genetic diversity, which limits the ability of local populations to respond to further environmental changes. The focus of this dissertation is on the degree to which common land uses in Sarapiquí, Costa Rica impede the movement of two common amphibian species. First, I used field experiments, including displacement trials, and a behavioral landscape ecology framework to investigate the resistance of pastures to movement of Oophaga pumilio. Results from experiments demonstrate that pastures do impede movement of O. pumilio relative to forest. Microclimatic effects on movement performance as well as limited perceptual ranges likely contribute to reduced return rates through pastures. Next, I linked local processes to landscape scale estimates of resistance. I conducted experiments to measure habitat-specific costs to movement for O. pumilio and Craugastor bransfodrii, and then used experimental results to parameterize connectivity models. Model validation indicated highest support for resistance estimates generated from responses to land-use specific microclimates for both species and to predator encounters for O. pumilio. Finally, I used abundance and experiment-derived resistance estimates to analyze the effects of prevalent land uses on population genetic structure of the two focal species. While O. pumilio did not exhibit a strong response to landscape heterogeneity and was primarily structured by distances among sites, C. bransfordii genetic variation was explained by resistance estimates from abundance and experiment data. Collectivity, this work demonstrates that common land uses can offer different levels of resistance to amphibian movements in Sarapiquí and illustrates the value of investigating local scales processes to inform interpretation of landscape-scale patterns.^

Geochemical data and radiocarbon ages of organic matter fractions and bacteriohopanepolyol data of sediment core GeoB6518-1 from the Congo River basin

The age of organic material discharged by rivers provides information about its sources and carbon cycling processes within watersheds. While elevated ages in fluvially-transported organic matter are usually explained by erosion of soils and sediments, it is commonly assumed that mainly young organic material is discharged from flat tropical watersheds due to their extensive plant cover and high carbon turnover. Here we present compound-specific radiocarbon data of terrigenous organic fractions from a sedimentary archive offshore the Congo River in conjunction with molecular markers for methane-producing land cover reflecting wetland extent in the watershed. We find that the Congo River has been discharging aged organic matter for several thousand years with increasing ages from the mid- to the Late Holocene. This suggests that aged organic matter in modern samples is concealed by radiocarbon from nuclear weapons testing. By comparison to indicators for past rainfall changes we detect a systematic control of organic matter sequestration and release by continental hydrology mediating temporary carbon storage in wetlands. As aridification also leads to exposure and rapid remineralization of large amounts of previously stored labile organic matter we infer that this process may cause a profound direct climate feedback currently underestimated in carbon cycle assessments.

Estudo de viabilidade técnico-ambiental para implantação de parques eólicos: um estudo de caso em um fragmento do litoral setentrional do Rio Grande do Norte/Brasil

The use of energy from renewable sources is increasingly demanded by society, especially aeolian - whose raw material is wind. Investments in wind power have become significant in Brazil with emphasis on the Northeast and in particular the Rio Grande do Norte state. According to the Empresa de Pesquisa Energética (Energy Research Company) (2012 ) , investments in the state grew significantly since 2002 with a total accumulated power, by 2013, of approximately 3,400 MW . Even with the early experiences of exploitation of wind energy in 2002, it is still considered new and requires further study referring to the likely changes in the environment and society. In this case, it is of growing and urgent importance to deeply study the wind still in the survey phase of the project, ie , at the beginning of decision making on the most feasible to implement these parks site. Given the above, the question is: from a technical and environmental analysis, how to identify viable areas to install Aeolian parks, taking into account the factors of the environmental dynamics that are relevant to minimize the negative results to the environment and the society? Thus, this study conducted a study on technical and environmental feasibility, proposing a methodology of exploration of feasible wind farms in coastal areas. The study area was a fragment of the northern coast of Rio Grande do Norte and its natural landscape units were identified through the environmental characterization of the area, as well as it was elaborated the map of the land cover, restriction homes and urban areas and Permanent Preservation Areas - PPAs. The environmental fragility was subdivided in the fragility of the natural dynamic, mapped through relief, soils and geology of natural units, and the fragility of the ecosystem, originated by the land cover map. In addition to these maps, it was generated the wind resource for an area from a height of 50 and 100 meters. The intersection between the fragility maps, PPAs and Restriction of homes superimposed on maps of wind potential, provided the map of feasibility of Aeolian parks, resulting in the most favorable areas for its facilities in a technical and environmental point of view. From this study, the entrepreneur can evaluate whether or not to proceed with the studies in this area and especially decrease potential conflicts with society.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

Projected responses of North American grassland songbirds to climate change and habitat availability at their northern range limits in Alberta, Canada

Across North America, grassland songbirds have undergone steep population declines over recent decades, commonly attributed to agricultural intensification. Understanding the potential interactions between the impacts of climate change on the future distributions of these species and the availability of suitable vegetation for nesting can support improved risk assessments and conservation planning for this group of species. We used North American bioclimatic niche models to examine future changes in suitable breeding climate for 15 grassland songbird species at their current northern range limits along the boreal forest–prairie ecotone in Alberta, Canada. Our climate suitability projections, combined with the current distribution of native and tame pasture and cropland in Alberta, suggest that some climate-mediated range expansion of grassland songbirds in Alberta is possible. For six of the eight species projected to experience expansions of suitable climate area in Alberta, this suitable climate partly overlaps the current distribution of suitable land cover. Additionally, for more than half of the species examined, most of the area of currently suitable climate was projected to remain suitable to the end of the century, highlighting the importance of Alberta for the long-term persistence of these species. Some northern prairie-endemic species exhibited substantial projected northward shifts of both the northern and southern edges of the area of suitable climate. Baird’s Sparrow (Ammodramus bairdii) and Sprague’s Pipit (Anthus spragueii), both at-risk grassland specialists, are predicted to have limited climate stability within their current ranges, and their expansion into new areas of suitable climate may be limited by the availability of suitable land cover. Our results highlight the importance of the preservation and restoration of remaining suitable grassland habitat within areas of projected climate stability and beyond current northern range limits for the long-term persistence of many grassland songbird species in the face of climate change.

Elucidating the Space-Time Structure of Low Level Warm Season Precipitation Processes in the Southern Appalachian Mountains Using Models and Observations

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

Theory and Practice in Sustainability Science: Influence of Urban Form on the Urban Heat Island and Implications for Urban Systems

As the world population continues to grow past seven billion people and global challenges continue to persist including resource availability, biodiversity loss, climate change and human well-being, a new science is required that can address the integrated nature of these challenges and the multiple scales on which they are manifest. Sustainability science has emerged to fill this role. In the fifteen years since it was first called for in the pages of Science, it has rapidly matured, however its place in the history of science and the way it is practiced today must be continually evaluated. In Part I, two chapters address this theoretical and practical grounding. Part II transitions to the applied practice of sustainability science in addressing the urban heat island (UHI) challenge wherein the climate of urban areas are warmer than their surrounding rural environs. The UHI has become increasingly important within the study of earth sciences given the increased focus on climate change and as the balance of humans now live in urban areas.

In Chapter 2 a novel contribution to the historical context of sustainability is argued. Sustainability as a concept characterizing the relationship between humans and nature emerged in the mid to late 20th century as a response to findings used to also characterize the Anthropocene. Emerging from the human-nature relationships that came before it, evidence is provided that suggests Sustainability was enabled by technology and a reorientation of world-view and is unique in its global boundary, systematic approach and ambition for both well being and the continued availability of resources and Earth system function. Sustainability is further an ambition that has wide appeal, making it one of the first normative concepts of the Anthropocene.

Despite its widespread emergence and adoption, sustainability science continues to suffer from definitional ambiguity within the academe. In Chapter 3, a review of efforts to provide direction and structure to the science reveals a continuum of approaches anchored at either end by differing visions of how the science interfaces with practice (solutions). At one end, basic science of societally defined problems informs decisions about possible solutions and their application. At the other end, applied research directly affects the options available to decision makers. While clear from the literature, survey data further suggests that the dichotomy does not appear to be as apparent in the minds of practitioners.

In Chapter 4, the UHI is first addressed at the synoptic, mesoscale. Urban climate is the most immediate manifestation of the warming global climate for the majority of people on earth. Nearly half of those people live in small to medium sized cities, an understudied scale in urban climate research. Widespread characterization would be useful to decision makers in planning and design. Using a multi-method approach, the mesoscale UHI in the study region is characterized and the secular trend over the last sixty years evaluated. Under isolated ideal conditions the findings indicate a UHI of 5.3 ± 0.97 °C to be present in the study area, the magnitude of which is growing over time.

Although urban heat islands (UHI) are well studied, there remain no panaceas for local scale mitigation and adaptation methods, therefore continued attention to characterization of the phenomenon in urban centers of different scales around the globe is required. In Chapter 5, a local scale analysis of the canopy layer and surface UHI in a medium sized city in North Carolina, USA is conducted using multiple methods including stationary urban sensors, mobile transects and remote sensing. Focusing on the ideal conditions for UHI development during an anticyclonic summer heat event, the study observes a range of UHI intensity depending on the method of observation: 8.7 °C from the stationary urban sensors; 6.9 °C from mobile transects; and, 2.2 °C from remote sensing. Additional attention is paid to the diurnal dynamics of the UHI and its correlation with vegetation indices, dewpoint and albedo. Evapotranspiration is shown to drive dynamics in the study region.

Finally, recognizing that a bridge must be established between the physical science community studying the Urban Heat Island (UHI) effect, and the planning community and decision makers implementing urban form and development policies, Chapter 6 evaluates multiple urban form characterization methods. Methods evaluated include local climate zones (LCZ), national land cover database (NCLD) classes and urban cluster analysis (UCA) to determine their utility in describing the distribution of the UHI based on three standard observation types 1) fixed urban temperature sensors, 2) mobile transects and, 3) remote sensing. Bivariate, regression and ANOVA tests are used to conduct the analyses. Findings indicate that the NLCD classes are best correlated to the UHI intensity and distribution in the study area. Further, while the UCA method is not useful directly, the variables included in the method are predictive based on regression analysis so the potential for better model design exists. Land cover variables including albedo, impervious surface fraction and pervious surface fraction are found to dominate the distribution of the UHI in the study area regardless of observation method.

Chapter 7 provides a summary of findings, and offers a brief analysis of their implications for both the scientific discourse generally, and the study area specifically. In general, the work undertaken does not achieve the full ambition of sustainability science, additional work is required to translate findings to practice and more fully evaluate adoption. The implications for planning and development in the local region are addressed in the context of a major light-rail infrastructure project including several systems level considerations like human health and development. Finally, several avenues for future work are outlined. Within the theoretical development of sustainability science, these pathways include more robust evaluations of the theoretical and actual practice. Within the UHI context, these include development of an integrated urban form characterization model, application of study methodology in other geographic areas and at different scales, and use of novel experimental methods including distributed sensor networks and citizen science.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.

Connectivity of fragmented amphibian populations in a Neotropical landscape

A high proportion of amphibian species are threatened with extinction globally, and habitat loss and degradation are the most frequently implicated causes. Rapid deforestation for the establishment of agricultural production is a primary driver of habitat loss in tropical zones where amphibian diversity is highest. Land-cover change affects native assemblages, in part, through the reduction of habitat area and the reduction of movement among remnant populations. Decreased gene flow contributes to loss of genetic diversity, which limits the ability of local populations to respond to further environmental changes. The focus of this dissertation is on the degree to which common land uses in Sarapiquí, Costa Rica impede the movement of two common amphibian species. First, I used field experiments, including displacement trials, and a behavioral landscape ecology framework to investigate the resistance of pastures to movement of Oophaga pumilio. Results from experiments demonstrate that pastures do impede movement of O. pumilio relative to forest. Microclimatic effects on movement performance as well as limited perceptual ranges likely contribute to reduced return rates through pastures. Next, I linked local processes to landscape scale estimates of resistance. I conducted experiments to measure habitat-specific costs to movement for O. pumilio and Craugastor bransfodrii, and then used experimental results to parameterize connectivity models. Model validation indicated highest support for resistance estimates generated from responses to land-use specific microclimates for both species and to predator encounters for O. pumilio. Finally, I used abundance and experiment-derived resistance estimates to analyze the effects of prevalent land uses on population genetic structure of the two focal species. While O. pumilio did not exhibit a strong response to landscape heterogeneity and was primarily structured by distances among sites, C. bransfordii genetic variation was explained by resistance estimates from abundance and experiment data. Collectivity, this work demonstrates that common land uses can offer different levels of resistance to amphibian movements in Sarapiquí and illustrates the value of investigating local scales processes to inform interpretation of landscape-scale patterns.