Human land use legacies have significant and long-lasting ecological impacts across landscapes. Investigating ancient (>400 years) legacy effects can be problematic due to the difficulty in detecting specific, historic land uses, especially those hidden beneath dense canopies. Caracol, the largest (~200 km 2 ) Maya archaeological site in Belize, was abandoned ca. A.D. 900, leaving behind myriad structures, causeways, and an extensive network of agricultural terraces that persist beneath the architecturally complex tropical forest canopy. Airborne LiDAR enables the detection of these below-canopy archaeological features while simultaneously providing a detailed record of the aboveground 3-dimensional canopy organization, which is indicative of a forest's ecological function. Here, this remote sensing technology is used to determine the effects of ancient land use legacies on contemporary forest structure. Canopy morphology was assessed by extracting LiDAR point clouds (0.25 ha plots) from LiDAR-identified terraced (n = 150) and non-terraced (n = 150) areas on low (0°-10°), medium (10°-20°), and high (>20°) slopes. We calculated the average canopy height, canopy openness, and vertical diversity from the LiDAR returns, with topographic features (i.e., slope, elevation, and aspect) as covariates. Using a PerMANOVA procedure, we determined that forests growing on agricultural terraces exhibited significantly different canopy structure from those growing on non-terraced land. Terraces appear to mediate the effect of slope, resulting in less structural variation between slope and non-sloped land and yielding taller, OPEN ACCESS

Locating caves can be difficult, as their entranceways are often obscured below vegetation. Recently, active remote-sensing technologies, in particular laser-based sensor systems (LiDARs), have demonstrated the ability to penetrate dense forest canopies to reveal the underlying ground topography. An airborne LiDAR system was used to generate a 1 m resolution, bare-earth digital elevation model (DEM) from an archaeologically-and speleologically-rich area of western Belize near the ancient Maya site of Caracol. Using a simple index to detect elevation gradients in the DEM, we identified depressions with at least a 10 m change within a circular area of no more than 25 m radius. Across 200 km 2 of the karst landscape, we located 61 depressions. Sixty of these had not been previously documented; the other was a cave opening known from a previous expedition. The morphologies of the depressions were characterized based on the LiDAR-derived DEM parameters, e.g., depth, opening area, and perimeter. We also investigated how the measurements change as a function of spatial resolution. Though there was a range of morphologies, most depressions were clustered around an average maximum depth of 21 m and average opening diameter of 15 m. Five depression sites in the general vicinity of the Caracol epicenter were visited; two of these were massive, with opening diameters of ,50 m, two could not be explored for lack of climbing gear, and one site was a cave opening into several chambers with speleothems and Maya artifacts. Though further investigation is warranted to determine the archaeological and geological significance of the remaining depressions, the general methodology represents an important advancement in cave detection.

Tropical rainforest clearing and degradation significantly reduces carbon sequestration and increases the rate of biodiversity loss. There has been a concerted international effort to develop remote sensing techniques to monitor broad-scale patterns of forest canopy disturbance. In addition to loss of natural resources, recent deforestation in Mesoamerica threatens historic cultural resources that for centuries lay hidden below the protective canopy. Here, we compare satellite-derived measures of canopy disturbance that occurred over a three decade period since 1980 to those derived from a 2009 airborne LiDAR campaign over the Caracol Archaeological Reserve in western Belize. Scaling up fine-resolution canopy height measures to the 30 m resolution of Landsat Thematic Mapper, we found LiDAR revealed a >58% increase in the extent of canopy disturbance where there was an overlap of the remotely sensed data sources. For the entire archaeological reserve, with the addition of LiDAR, there was a 2.5% increase of degraded canopy than estimated with Landsat alone, indicating that 11.3% of the reserve has been subjected to illegal selective logging and deforestation. Incursions into the reserve from the Guatemala border, represented by LiDAR-detected canopy disturbance, extended 1 km deeper (to 3.5 km) into Belize than were derived with Landsat. Thus, while LiDAR enables a synoptic, never-seenbefore, below-canopy view of the Maya city of Caracol, it also reveals the degree of canopy disturbance and potential looting of areas yet to be documented by archaeologists on the ground.Keywords: Canopy degradation, Deforestation, Edge detection, Landsat, LiDAR, Maya archaeology, REDD+, Selective logging, Wombling ResumenLa tala y el deterioro de los bosques húmedos tropicales reducen significativamente la habilidad de este ecosistema para capturar carbono, y aumentan la tasa de pérdida de biodiversidad. Por lo tanto, existe un esfuerzo internacional para desarrollar técnicas de sensores remotos con el fin de monitorear los patrones a gran escala de las perturbaciones en el dosel del bosque. Adicional a la perdida de recursos naturales, la deforestación reciente en Mesoamérica amenaza los recursos históricos culturales que por siglos han permanecido escondidos bajo la protección del dosel. En este proyecto comparamos algunas medidas de perturbación del dosel derivadas de imágenes satelitales durante un periodo de tres décadas a partir de 1980, con aquellas derivadas de una campaña de vuelos con LiDAR llevada a cabo en 2009 sobre la Reserva Arqueológica Caracol en el oeste de Belice. Ampliando las medidas de altura de dosel de resolución fina a la resolución de 30 m del Landsat Thematic Mapper, encontramos que LiDAR reveló un aumento de más de 58% en la extensión de perturbaciones del dosel para aquellas áreas en donde se tenían datos de ambas fuentes de sensores remotos. Para la totalidad de la reserva arqueológica, con la adición de LiDAR hubo un aumento de 2.5% del área perturbada del dosel sobre la estimada utilizando ú...

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Fragmentation and scale Although habitat loss has well‐known impacts on biodiversity, the effects of habitat fragmentation remain intensely debated. It is often argued that the effects of habitat fragmentation, or the breaking apart of habitat for a given habitat amount, can be understood only at the scale of entire landscapes composed of multiple habitat patches. Yet, fragmentation also impacts the size, isolation and habitat edge for individual patches within landscapes. Addressing the problem of scale on fragmentation effects is crucial for resolving how fragmentation impacts biodiversity. Scaling framework We build upon scaling concepts in ecology to describe a framework that emphasizes three “dimensions” of scale in habitat fragmentation research: the scales of phenomena (or mechanisms), sampling and analysis. Using this framework, we identify ongoing challenges and provide guidance for advancing the science of fragmentation. Implications We show that patch‐ and landscape‐scale patterns arising from habitat fragmentation for a given amount of habitat are fundamentally related, leading to interdependencies among expected patterns arising from different scales of phenomena. Aggregation of information when increasing the grain of sampling (e.g., from patch to landscape) creates challenges owing to biases created from the modifiable areal unit problem. Consequently, we recommend that sampling strategies use the finest grain that captures potential underlying mechanisms (e.g., plot or patch). Study designs that can capture phenomena operating at multiple spatial extents offer the most promise for understanding the effects of fragmentation and its underlying mechanisms. By embracing the interrelationships among scales, we expect more rapid advances in our understanding of habitat fragmentation.