Benthic and substrate cover data derived from a time series of photo-transect surveys for the Eastern Banks, Moreton Bay Australia, 2004-2015

This paper describes seagrass species and percentage cover point-based field data sets derived from georeferenced photo transects. Annually or biannually over a ten year period (2004-2015) data sets were collected using 30-50 transects, 500-800 m in length distributed across a 142 km**2 shallow, clear water seagrass habitat, the Eastern Banks, Moreton Bay, Australia. Each of the eight data sets include seagrass property information derived from approximately 3000 georeferenced, downward looking photographs captured at 2-4 m intervals along the transects. Photographs were manually interpreted to estimate seagrass species composition and percentage cover (Coral Point Count excel; CPCe). Understanding seagrass biology, ecology and dynamics for scientific and management purposes requires point-based data on species composition and cover. This data set, and the methods used to derive it are a globally unique example for seagrass ecological applications. It provides the basis for multiple further studies at this site, regional to global comparative studies, and, for the design of similar monitoring programs elsewhere.

Morphometric data for Globigerinoides sacculifer and Globorotalia tumida (size and Fourier coefficients) and temperature proxy reconstructions (UK37' and Tex86H) from samples from ODP sites 165-999/165-1000 and 202-1241 spanning the last 10Ma

Sediment samples from both Site 165-999/165-1000 (Atlantic) and Site 202-1241 (Pacific) were chosen at 1Ma intervals over the period 0.3-9.3Ma. Samples were washed and sieved <150µm. Splits of the sediment fraction were picked completely to obtain, where possible, at least 30 specimens each of planktic foraminifer species Globigerinoides sacculifer and Globorotalia tumida, on which outline analysis (Fourier) was performed. Sea surface and thermocline temperatures were reconstructed from palaeoenvironmental proxies (UK37' and Tex86H respectively).

Lesson from the habitat suitability models to evaluate the environmental of Pinus nigra Arnold and Pinus sylvesris L. in the Iberian Peninsula

PREDICT POTENTIAL DISTRIBUTION. Spatial and temporal evolution of the species under different climate scenarios. Generation of habitat suitability models (HSM)  high degree of uncertainty and limitations. The importance of their validation has been stressed. In this work we discuss the present potential distribution of P. sylvestris and P. nigra in the Iberian Peninsula by using MaxEnt, and evaluate the influence of the different environmental variables. Our intention is to select a set of environmental variables that explains better their current distribution, to achieve the most accurate and reliable models. Then we project them to the past climatic conditions (21 to 0 kyrs BP), to evaluate the outputs with existing palaeo-ecological data.

Refining predictions of iberian plant distribution: lessons from p. nigra and p. sylvestris palaeoecological-based habitat suitability models

In recent years, challenged by the climate scenarios put forward by the IPCC and its potential impact on plant distribution, numerous predictive techniques -including the so called habitat suitability models (HSM)- have been developed. Yet, as the output of the different methods produces different distribution areas, developing validation tools are strong needs to reduce uncertainties. Focused in the Iberian Peninsula, we propose a palaeo-based method to increase the robustness of the HSM, by developing an ecological approach to understand the mismatches between the palaeoecological information and the projections of the HSMs. Here, we present the result of (1) investigating causal relationships between environmental variables and presence of Pinus sylvestris L. and P. nigra Arn. available from the 3rd Spanish Forest Inventory, (2) developing present and past presence-predictions through the MaxEnt model for 6 and 21 kyr BP, and (3) assessing these models through comparisons with biomized palaeoecological data available from the European Pollen Database for the Iberian Peninsula.

Integrated methodology for assessing the effects of geomorphological river restoration on fish habitat and riparian vegetation

Changes in the geomorphology of rivers have serious repercussions, causing losses in the dynamics and naturalness of their forms, going in many cases, from a type of meandering channel, with constant erosion and sedimentation processes, to a channelized narrow river with rigid and stable margins, where the only possibility of movement occurs in the vertical, causing the only changes in channel geometry occur in the river bed. On the other hand, these changes seriously affect the naturalness of the banks, preventing the development of riparian vegetation and reducing the cross connectivity of the riparian corridor. Common canalizations and disconnections of meanders increase the slope, and therefore speed, resulting in processes of regressive erosion, effect increased as a result of the narrowing of the channel and the concentration of flows. This process of incision may turn the flood plain to be "hung", being completely disconnected from the water table, with important consequences for vegetation. As an example of the effects of these changes, it has been chosen the case of the Arga River The Arga river has been channelized and rectified, as it passes along the meander RamalHondo and Soto Gil (Funes, Navarra). The effects on fish habitat and riparian vegetation by remeandering the Arga River are presented. and Ttwo very contrasting situationsrestoration hypothesis, in terms of geomorphology concerns, have been established to assess the effects these changes have on the habitat of one of the major fish species in the area (Luciobabus graellsii) and on the riparian vegetation. To accomplish this goal, it has been necessary to used the a digital elevation model provided by LIDAR flight, bathymetric data, flow data, as inputs, and a hydraulic simulation model 2D (Infoworks RS). The results obtained not only helped to evaluate the effects of the past alterations of geomorphologic characteristics, but also to predict fish and vegetation habitat responses to this type of changes.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.