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1. To understand time-­lag dynamics in the response of biodiversity to contem- porary environmental changes (e.g. macroclimate warming and atmospheric pollution), we need to consider former anthropogenic forcing factors such as past land uses and management practices that can have both compounding and confounding effects. This is especially true in European temperate forests, where legacies from past human activities have left strong imprints on today’s understorey plant species composition, generating long-­term lagging effects which can be mistakenly attributed to more recent macro-­environmental changes. 2. By combining the expertise of plant, soil and historical ecologists together with remote sensing scientists, we review the potential of light detection and ranging (LiDAR) to unveil ghosts from the past in terms of former land uses and manage- ment practices. 3. We show that imprints from past land uses and management practices can still be captured today through well-­chosen LiDAR-­derived variables describing, at sub-­decimetre scale, the vertical and horizontal micro-­variations of vegetation and terrain structure hidden below treetops. 4. Synthesis. We encourage plant and soil ecologists to use LiDAR data and to work with historians, archaeologists and remote sensing scientists in order to select meaningful LiDAR-­derived variables to account for time-­lagged biotic responses to long-­term macro-­environmental changes.

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

Forests will be critical to mitigate the effects of climate and global changes. Therefore, knowledge on the drivers of forest area changes are important. Although the drivers of deforestation are well known, drivers of afforestation are almost unexplored. Moreover, protected areas (PAs) effectively decrease deforestation, but other types of area-based conservation measures exist. Among these, sacred natural sites (SNS) deliver positive conservation out- comes while making up an extensive “shadow network” of conservation. How- ever, little is known on the capacity of SNS to regulate land-use changes. Here, we explored the role of SNS and PAs as drivers of forest loss and forest gain in Italy between 1936 and 2018. We performed a descriptive analysis and modeled forest gain and forest loss by means of spatial binomial generalized linear models with residual autocovariates. The main drivers of forest area changes were geographical position and elevation, nonetheless SNS and PAs significantly decreased forest loss and increased forest gain. Although the neg- ative relationship between SNS and forest loss is a desirable outcome, the posi- tive relationship with forest gain is concerning because it could point to abandonment of cultural landscapes with consequent loss of open habitats. We suggest a legal recognition of SNS and an active ecological monitoring and planning to help maintain their positive role in biodiversity conservation. As a novel conservation planning approach, SNS can be used as stepping stones between PAs increasing connectivity and also to conserve small habitat patches threatened by human activities.

Species occurrences inherently include positional error. Such error can be problematic for species distribution models (SDMs), especially those based on fine-resolution envi- ronmental data. It has been suggested that there could be a link between the influence of positional error and the width of the species ecological niche. Although positional errors in species occurrence data may imply serious limitations, especially for model- ling species with narrow ecological niche, it has never been thoroughly explored. We used a virtual species approach to assess the effects of the positional error on fine-scale SDMs for species with environmental niches of different widths. We simulated three virtual species with varying niche breadth, from specialist to generalist. The true dis- tribution of these virtual species was then altered by introducing different levels of positional error (from 5 to 500 m). We built generalized linear models and MaxEnt models using the distribution of the three virtual species (unaltered and altered) and a combination of environmental data at 5 m resolution. The models’ performance and niche overlap were compared to assess the effect of positional error with varying niche breadth in the geographical and environmental space. The positional error negatively impacted performance and niche overlap metrics. The amplitude of the influence of positional error depended on the species niche, with models for specialist species being more affected than those for generalist species. The positional error had the same effect on both modelling techniques. Finally, increasing sample size did not mitigate the negative influence of positional error. We showed that fine-scale SDMs are consider- ably affected by positional error, even when such error is low. Therefore, where new surveys are undertaken, we recommend paying attention to data collection techniques to minimize the positional error in occurrence data and thus to avoid its negative effect on SDMs, especially when studying specialist species.

In 2014, Wiley and the Zoological Society of London launched Remote Sensing in Ecology and Conservation, an open-access journal that aims to support communication and collaboration among experts in remote sensing, ecology and conservation science. Remote sensing was from the start understood as the acquisition of information about an object or phenomenon through a device that is not in physical contact with the object, thus including camera traps, field spectrometry, terrestrial and aquatic acoustic sensors, aerial and satellite monitoring as well as ship-borne automatic identification systems. The primary goals of this new journal were, and still are, to maximize the understanding and uptake of remote sensing-based techniques and products by the ecological and conservation communities, prioritizing findings that advance the scientific basis of, and applied outcomes from, ecology and conservation science; and to identify ecological challenges that might direct development of future remote sensors and data products. In October 2015, the first issue of the journal was published, with four other issues produced in 2016 and four to be published in 2017. As Remote Sensing in Ecology and Conservation is about to complete its second full year of publication and is working towards a first impact factor score in early 2019, the time has come to reflect on how the journal has done to date, what impact it has had, which niches it has successfully filled and where the journal is yet to meet its full potential. By sharing our successes and experiences so far with our contributors and readers, we hope to demonstrate how Remote Sensing in Ecology and Conservation has swiftly gained significant visibility and status among scientists and practitioners interested in natural resource management. Fil: Pettorelli, Nathalie. The Zoological Society Of London; Reino Unido Fil: Nagendra, Harini. Azim Premji University; India Fil: Rocchini, Duccio. Università Degli Studi Di Trento; Italia Fil: Rowcliffe, Marcus. The Zoological Society Of London; Reino Unido Fil: Williams, Rob. Oceans Initiative; Estados Unidos Fil: Ahumada, Jorge. Conservation International; Estados Unidos Fil: de Angelo, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Atzberger, Clement. Universitat Fur Bodenkultur Wien; Austria Fil: Boyd, Doreen. Science and Technology Facilities Council of Nottingham. Rutherford Appleton Laboratory; Reino Unido. University of Nottingham; Estados Unidos Fil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino Unido Fil: Chauvenet, Alienor. University of Queensland; Australia Fil: Disney, Mathias. Colegio Universitario de Londres; Reino Unido Fil: Duncan, Clare. Deakin University; Australia Fil: Fatoyinbo, Temilola. NASA Goddard Space Flight Center; Estados Unidos Fil: Fernandez, Nestor. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; España Fil: Haklay, Muki. Colegio Universitario de Londres; Reino Unido Fil: He, Kate. Murray State University Murray; Estados Unidos Fil: Horning, Ned. American Museum of Natural History; Estados Unidos Fil: Kelly, Natalie. Australian Antarctic Division; Australia Fil: de Klerk, Helen. Stellenbosch University; Sudáfrica Fil: Liu, Xuehua. Tsinghua University; China Fil: Merchant, Nathan. Centre for Environment, Fisheries and Aquaculture Science; Reino Unido Fil: Paruelo, José. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Roy, Helen. NERC Centre for Ecology & Hydrology; Reino Unido Fil: Roy, Shovonlal. University of Reading; Reino Unido Fil: Ryan, Sadie. University of Florida; Estados Unidos Fil: Sollmann, Rahel. University of California at Davis; Estados Unidos Fil: Swenson, Jennifer. University of Duke; Estados Unidos Fil: Wegmann, Martin. Universität Würzburg; Alemania

Question: How do canopy disturbance and soil properties structure vascular plant community species composition and resilience to encroachment by exotic species in a tropical montane wet forest? Location: Hawai'i Experimental Tropical Forest (HETF), a tropical montane wet forest, on Mauna Kea, Hawai'i Island, Hawai'i, USA. Methods: Previous studies employing airborne LiDAR were used to define three zones across an elevation gradient from 900 to 1500m. Within each zone, a ~1000-m block transect was selected to cross two different volcanic substrates: one derived from surface lava and one derived from thick ash deposits. Non-metric multidimensional scaling (NMS) scores of vegetation data were related to independently-derived environmental NMS scores and spatial location with generalized additive models (GAM). Results: Vascular plant species composition in all elevation zones consists of three NMS axes, which are best modelled by one of three possible environmental NMS axes or by location. The first NMS axis of species composition in the lowest elevation zone (40% variance explained (VE)) is a function of location on volcanic substrates (61% deviance explained (DE)). The second lowest elevation axis (27% VE) is a function of unexplained spatial heterogeneity (31% DE). The third lowest elevation NMS axis (24% VE) is a function of the spatial mosaic of canopy disturbance (16% DE). In the middle elevation zone, species composition most strongly relates to the interaction between volcanic substrate and the condition of the soil surface for all three NMS axes (41%, 27%, 24% VE; 70%, 16%, 24% DE). The primary axis of species composition in the highest elevation zone (41% VE) corresponds with substrate and soil condition (55% DE) but the second and third axes of species composition (27% and 25% VE) relate to canopy dieback disturbance (36%, 14% DE). Counts of exotic species and 0-2m height class native tree species respond to the type of volcanic substrate and soil surface condition in all three elevation zones. Lava-derived substrates have a higher incidence of exotic species and less native tree regeneration; whereas ash-derived substrates have higher numbers of native tree species regenerating and many fewer exotic species. Discussion: The tropical montane forests on Mauna Kea reflect a native-dominated plant community response to disturbance on both lava- and ash-derived volcanic substrates, and a higher propensity for exotic species to occur on the lava-derived substrate. Native plant communities on ash-derived soils may have higher resilience to exotic invasion than communities on lava-derived substrates. Our results indicate resource managers should explicitly account for variation in soils and substrate type when prioritizing, implementing and monitoring management interventions to foster native plant assemblages and control the spread of exotic and invasive species. © 2013 International Association for Vegetation Science.