Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Alpha and beta diversity indices were assessed through the visual annotation of underwater images, where all organisms were identified to the highest taxonomic resolution possible and distinct morphospecies were assigned an Unit (OTU), as standard taxonomic approaches are not often applicable to image data. A morphospecies may then correspond to species, genus, family or higher taxonomic levels. Whilst images were annotated by the same observer (who also re-annotated 5% of the images for quality assurance), this method lacks taxonomic resolution, which may consequently have had a negative effect on the diversity results presented here and led to the grouping of several species within one morphospecies, or on the contrary, separation of one species into several colour morphs. During the current study, it was not possible to collect the physical samples typically required to enable traditional taxonomic investigation. Taxon differentiation was thus missing at the fine scale, molecular and genetic levels, likely leading to lower (or higher) observed diversity values and differences in diversity than actually occurs in reality. MCEs are still relatively poorly understood in taxonomic terms, thus, high-resolution images with close-ups in addition to physical sample collection and taxonomic expertise are crucial to resolve their true diversity and the variation in taxa along the depth gradient. This study investigated alpha and beta diversities for benthic communities, along a large depth gradient, for the first time in the central Indian Ocean. These indices are crucial indicators to provide evidence-based information for management and conservation actions. Indeed, despite meeting the international criteria used to identify priority areas for conservation policies (Soares et al. 2020), MCEs are still considered under-protected and under-represented in marine spatial planning (Stefanoudis et al. 2022), and they are usually incidentally included in MPAs due to geopolitical boundaries, rather than purposefully (Turner et al. 2019; Stefanoudis et al. 2022). MCEs, while encompassed within the fully protected Chagos MPA since 2010, have not been included in research and specific protection until 2018, where an objective to improve their research and protection by 2023 was mentioned in the conservation management planning workshop (Programme 2018). However, the authors are not aware of any specific management steps being taken regarding the protection of MCEs within the Chagos MPA, other than the research presented here.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Thus, enhanced resonance behavior after learning observed experimentally may suggest that changes in synaptic connections strengthen positive feedback in the circuit and affect the response dynamics by interacting with a slow negative feedback mechanism. Also, the reduced response to successive stimulus presentation of novel stimuli (Meyer et al. , 2014) can be caused by the slow recovery from negative feedback. For generating a damped oscillatory response after learning, we found that specific negative feedback such as firing rate adaptation is required (Figure 3). Similar to previous works investigating the effect of adaptation on the network activity in a mean-field approach (Fuhrmann et al. , 2002; Laing and Chow, 2002; Tabak et al. , 2006; Treves, 1993; van Vreeswijk and Hansel, 2001), we considered a linear mechanism for adaptation where the adaptation current is a low-pass filtered firing rate represented by the variable ai with time constant τa and strength k. Then the dynamics of network activity is described by the following equations: (3) τrdridt=−ri+Φ(∑ WijRrj−kai+∑ WijFIjX) τadaidt=−ai+ri Figure 3 with 2 supplements see all Download asset Open asset Mechanism of generating damped oscillations after learning. (A) Schematics of the dynamics after learning. The overlap variable m is similar to activities of high rate neurons represented as r1, and n represents adaptation in m. These high rate neurons drive a damped oscillation in the remaining population whose strength is proportional to the post-synaptic dependence of recurrent synaptic plasticity fR(ξi). (B) Interactions between potentiation of recurrent inputs and a slow adaptation mechanism. The strength of potentiation is proportional to fg¯R (Equation 4) which is 0 before learning. The separatrix dividing overshoot and damped oscillations is shown as a parabola defined by fg¯R, the strength of adaptation k and time constants τR and τA. Intuitively, interactions between recurrent synaptic plasticity and adaptation-like negative feedback in Equations (2) and (3) can reproduce two effects of visual learning, increase in maximal response and stronger oscillatory response after learning.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: 28 (DF = 3) p < 0. 001 Table 4. values for each spoor measurement (mm; Fig. 3) for three leopard hind left spoor sets taken in the field. None of the interaction terms was significant. DF F p Full spoor length (A) animal 2, 48 37. 06 0. 001 substrate 1, 48 5. 36 0. 025 Full spoor width (B) animal 2, 51 5. 06 0. 010 substrate 1, 51 13. 50 0. 001 Hind pad length (C) animal 2, 49 17. 51 0. 001 substrate 1, 49 9. 37 0. 004 Hind pad width(D) animal 2, 49 1. 46 0. 244 substrate 1, 49 4. 68 0. 036 In contrast, camera traps readily allow identification of species and individuals when variable pelage markings are evident, and often their general size or sex can be determined. Increasing the likelihood of detecting focal species is extremely important to avoid under-recording (Maputla et al. 2013). Our work suggests that this could be a more significant factor to consider when utilising camera traps than perhaps previously thought. Trolle and Kery (2005) found dirt roads to be more effective than game trails in capturing carnivores on camera, so we are likely to have maximised our capture rate, but evidently many individuals were not recorded by the camera traps. While the results for leopard are based on a small sample, results from our long term study (Pirie, Thomas and Fellowes unpubl. ) also suggest camera traps record the presence of this species approximately twice as often as spoor. All four sites were picked partly because of the ideal substrate conditions, although these can alter between days due to changing temperatures, humidity, rainfall and wind strength (Alibhai et al. 2008, Lyra-Jorge et al. 2008). On two occasions, leopard spoor was registered outside of the camera trap zone and the leopard was photographed by the camera trap, but no complete leopard spore was detected within the camera trap zone. This is likely due to slight variations in the substrate within the camera trap zone. Partial spoor was not recorded to avoid misidentification, so was not recorded as being inside the trap zone. Overall, under-recording appears to occur more frequently with smaller species. Previous studies (Kelly 2008, Lyra-Jorge et al.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: AbstractLow-altitude high-resolution aerial photographs allow for the reconstruction of structural properties of shallow coral reefs and the quantification of their topographic complexity. This study shows the scope and limitations of two-media (air/water) Structure from Motion—Multi-reconstruction method using drone aerial photographs to reconstruct coral height. We apply this method in nine different sites covering a total area of about 7000 m2, and we examine the suitability of the method to obtain topographic complexity estimates (i. e. , seafloor rugosity). A simple refraction correction and survey design allowed reaching a root mean square error of 0. 1 m for the generated digital models of the seafloor (without the refraction correction the root mean square error was 0. 2 m). We find that the complexity of the seafloor extracted from the drone digital models is slightly underestimated compared to the one measured with a traditional in situ survey method. Similar content being viewed by others Detecting change in coral reef 3D structure using underwater photogrammetry: critical issues and performance metrics 2. 5D) mapping of very shallow (< 3 m depth) coral reefs is a challenge. Large corals reach up to mean sea level, thus preventing the navigation of vessels carrying ship-borne echo sounders and limiting divers’ access to continuous top-view data. Airborne bathymetric active light detection and ranging (LiDAR) can overcome these limitations and provide continuous sub-meter resolution data with a vertical accuracy in the range of 1–2 dm for shallow-water coral reefs (Collin et al. 2018). surveys are costly and likely unjustified for small areas, and they allow for minimal flexibility in the survey design. In the last years, System (UAS, also called drones) started to be regarded as a third-generation source of remote sensing data (et al. 2018), providing scientists new and accessible tools to explore the Earth surface (e. g. , Casella et al. 2020; Dugdale et al. 2019; Castellanos-Galindo et al. 2019; Mlambo et al. 2017) and allowing significant scientific advancement (e. g. , Ramanathan et al. 2007). UAS regulation that has hindered early scientific uses of UASs (Coops et al. 2019) is now moving forward.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Hebbian-type synaptic plasticity in recurrent connections provides strong potentiation in the connections among high firing rate neurons, and thus, generates a cell assembly with stronger positive feedback after learning (Figure 3A). This leads to not only an increase in the response of this cell assembly but also the emergence of oscillation under the interplay with slow adaptation currents. The strength of oscillation in the rest of the population may depend on the synaptic strengths from these high firing rate neurons. To show this analytically, we investigated mean-field dynamics that summarize network activity with fewer variables (Materials and methods). To facilitate the analysis, we made two assumptions, linear dynamics with transfer function Φ(x) = x, and homogeneous connectivity before learning that reflects no correlation between novel stimuli and network structure. Under these assumptions, the dynamics before learning is described by average activity and adaptation, r¯=1N∑iri and a¯=1N∑iai. After learning, with synaptic plasticity in recurrent connections following Equation (2), recurrent connections become correlated with activity pattern they learned. Increased correlation between the learned pattern and network structure can be captured by additional variables m and n, defined as m=1N∑igR(ξi)ri and n=1N∑igR(ξi)ai, which is a variation of the pattern overlap 1N∑iξiri utilized previously to describe changes in dynamics with learning (Tsodyks and Feigel'man, 1988). The variables m and n can approximately represent the activities and adaptation of high firing rate neurons as the activities and adaptation of high firing rate neurons contribute more to m and n variables with monotonically increasing pre-synaptic dependence gR(ξi) (Figure 3A). Thus, potentiation of recurrent inputs in high firing rate neurons provides strong positive feedback in m, while slow adaptation mechanisms represented by n variables provide negative feedback. As the variables m and n are only present in the dynamics after learning, qualitative changes of the response dynamics in the network should be mainly led by their dynamics with strong potentiation in high rate neurons (Figure 3B). Such strong potentiation and generation of damped oscillation in high rate neurons are consistent with the observation that the rebound is strongest in those neurons (Figure 1D).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: 2008, but see Negroes et al. 2012) support this view. In contrast, Urlus et al. (2014) found that larger Australian mammals were more likely to be under-recorded by camera traps. It is likely that this is as a result of the much greater size difference in their study, with smaller mammals having a more restricted home range around the traps, and their use of bait stations to attract smaller species (Urlus et al. 2014). Trigger time, the interval between sensors detecting movement and an image being taken, may also play a role in under recording given that small animals may not trigger the sensors or move more rapidly out of the capture zone once the sensors have been activated. Negroes et al. (2012) found having two cameras per station was on average 29% more effective than a single camera based on photographic rate. In addition, camera traps can vary greatly in their likelihood of capturing different species (Urlus et al. 2014, Swan et al. 2014) and understanding how equipment varies is of considerable importance. Table 5. Mean and range (mm) of spoor measurements (Fig. 3) for three leopards hind left spoor, recorded under two substrate conditions in the field. Hind left: substrate < 2 mm Hind left: substrate > 2 mm 1 Min. 75 61 36 44 73 55 37 45 Mean 78 62 38 46 81 63 44 48 Max. 80 62 40 50 88 67 50 52 n 4 4 3 3 8 9 8 7 Leopard 2 Min. 85 55 45 45 89 58 45 45 Mean 87 60 47 47 93 63 52 51 Max. 90 63 49 49 97 70 58 60 n 3 3 2 2 16 15 16 16 Leopard 3 Min. 82 60 41 43 80 61 40 42 Mean 87 62 45 46 88 69 47 50 Max. 95 67 49 51 95 76 55 60 n 13 14 14 14 5 7 7 8 Assessing predator abundance and distribution in savannah remains a challenge. We argue that the traditional approach of using spoor and the skills associated with tracking in the field still have a place in monitoring the larger mammalian predators of savannah habitat in two key ways. First, spoor allows us to evaluate how effective camera traps are at recording the study species; our study species were 37% more likely to be recorded by spoor than by our camera traps. This study also supports the view that camera trap studies should be calibrated against other methods (Gompper et al.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Union represents an example where the different UAS regulations of each EU country are now unified under a common and simplified regulation (EU 2018/1139 and implementing acts). A review of worldwide UAS regulations is presented by Stöcker et al. (2017). Concurrently, advances in computer vision algorithms (Anderson et al. 2019) and hardware (e. g. , GPU) facilitated the use of photogrammetry through Structure from Motion (SfM) (Ullman 1979) and Multi-reconstruction (MVS) methods (Scharstein and Szeliski 2002). Today, SfM-MVS methods represent a core data capture and analysis approach widely used by earth and environmental scientists (Anderson et al. 2019; James et al. 2019). These technological and scientific advances facilitate the collection of centimeter-resolution continuous top-view data of shallow reefs at relatively low cost with more flexibility in the survey plan or experimental design (e. g. , Casella et al. , 2017). Although these are clear advantages for coral reef mapping and research, few studies surveying coral reefs with UASs and SfM-MVS exist compared to studies on terrestrial ecosystems (David et al. 2021; Fallati et al. 2020; Levy et al. 2018; Casella et al. 2017). The refraction of light by water, which causes features on the seafloor to appear shallower than they are may have led to this discrepancy because it introduces more significant errors than on-land environments. In addition, turbidity, water surface roughness, and the maximum depth for light penetration represent additional error sources (Joyce et al. 2018; Woodget et al. 2015). Some possible solutions to reduce the effect of the refraction of light on UAS SfM-MVS derived data exist or are being developed (Agrafiotis et al. 2020; Shintani and Fonstad 2017; Dietrich 2017; Ye et al. 2016; Woodget et al. 2015; Maas 2015). This study aims to investigate the relative accuracy of coral height reconstruction of two-media (air/water) SfM-MVS datasets derived from low-altitude UAS flights on shallow coral reefs (< 3 m depth). Rather then focusing on the geographic accuracy, our goal is to answer the question: “how accurately (relative accuracy) can we reconstruct coral height? ”.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: The recurrent input from high rate neurons can lead to a damped oscillatory response in the rest of the population (Figure 3A). The mean-field analysis shows that the strength of the damped oscillatory response is proportional to the strength of postsynaptic synaptic plasticity fR(ξi) in the case of linear dynamics. If fR for neuron i is positive (negative) corresponding to potentiation (depression) in recurrent inputs, an oscillation in neuron i would be in phase (out of phase) with that of high rate neurons. Previously, we proposed Hebbian-type but overall depression-dominant synaptic plasticity in recurrent connections to minimally account for the decrease in time-averaged responses (Lim et al. , 2015). However, this would lead to out of phase oscillation in the mean and maximum response, inconsistent with the data (Figure 1A,B). Instead, overall potentiation in recurrent inputs with f¯R >0 is required to generate in-phase oscillation in the mean and maximum response in linear dynamics (Figure 3—figure supplement 1). Additional synaptic plasticity for reduction in average response We showed that recurrent synaptic plasticity could account for the emergence of damped oscillation and sharpening neural activities by increasing the maximal response after learning. Furthermore, synchronous oscillations in the mean and maximum response observed experimentally suggest overall potentiation in recurrent inputs. However, potentiation-dominant synaptic plasticity in recurrent connections would increase overall synaptic input and cannot reproduce a decrease in average activities with learning (Figure 3—figure supplement 1A,B). The same holds for recurrent synaptic plasticity with or without the assumption of the constant sum normalization which imposes a constraint on the pre-synaptic dependence (Figure 3—figure supplement 2). Instead, reduction in average response requires changes in external inputs or other recurrent inputs such as suppression in other excitatory inputs or enhanced inhibition. Enhanced recurrent inhibition can result from an increase in inhibitory activities after learning or potentiated inhibitory connections onto excitatory neurons. The former is inconsistent with the experimental observations showing a reduction in inhibitory firing rates across different stimuli (Figure 1—figure supplement 1).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: 2006, Balme et al. 2009) in order to gain more accurate data to determine actual density, relative abundance and movements of species. Camera traps are beneficial but their reliability in capturing each animal that triggers the sensors is uncertain and depends on the camera model, habitat and as we show, species. Second, while it is unlikely that simple direct spoor measurements can be used to reliably identify unknown leopards due to interobserver variation, such spoor measurements enable known individuals to be followed by experienced field trackers with some certainty, allowing researchers to link records at static camera trap locations with the wider movements of an individual. We therefore suggest that while camera traps are an exceptionally helpful addition to the ecologist's armoury, we should take care to ensure that the benefits of good field craft are not neglected. are very grateful to and who made significant contributions to data collection. A special thank you to the late Ronnie Watson, who championed Research efforts, and to Alan and Lynsey Watson, Will and Carol Fox, the share-holders and staff of and PAW for their support. 2008. A footprint technique to identify white rhino Ceratotherium simum at individual and species levels. —Res. 4: 205–218. 10. 3354/esr00067 2014. Camera traps, sand plots and known events: what do camera traps miss? —In: Meek, P. and Fleming, P. (eds), Camera trapping: wildlife management and research. —. , 202. 2009. Evaluating methods for counting cryptic carnivores. —J. Wildl. Manage. 73: 433–441. 10. 2193/2007-368 Web of Science®1996. Power of track surveys to detect changes in cougar populations. —Wildl. Soc. Bull. 24: 540–546. Web of Science®1984. Aspects of the ecology and the behaviour of the leopard Panthera pardus in the Kalahari desert. —Koedoe 27: 259–279. 10. 4102/koedoe. v27i2. 585 2010. An estimate of leopard population density in a private reserve in KwaZulu-Natal, South Africa, using camera-traps and capture—recapture models. —S. Afr. J. Wildl. Res. 40: 114–120. 10. 3957/056. 040. 0202 Web of Science®2010.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: The Phantom-4 Pro has an integrated RGB sensor 1’’ CMOS (effective pixel: 20 M), a focal length of 9 mm, and a resolution of 5472 × 3648 pixels (as per technical specifications: dji. com/phantom-4pro). Nine different flights were programmed to survey the sites at an altitude of 10 m (see Supplementary Table). app (dji. com/de/ground-station-pro) was used to program the UAS flights so that each flight resulted in a 90% forward and lateral overlap. Two types of markers were placed on the seafloor of each site before the flights (Fig. 1c, d): ground control points (GCPs) and scale bars (SBs). A total of 45 30 × 30 cm bright-colored towels and 29 50 cm-long steel bars covered by bright-colored tape were used as GCPs and SBs, respectively. The geographic position of GCPs was collected using a handheld GNSS receiver (Garmin eTrex® 10) with a horizontal accuracy in the order of meters, and their vertical position (local depth) was measured with a handheld Hondex PS-7 dive sonar with reference to the local water level at the time of measurement. The position of GCPs and the length of SBs were used to scale the point cloud generated during the SfM-MVS process. The position of GCPs was also used to georeference the point cloud, optimize the image alignment, and minimize the sum of the re‐projection error and the georeferencing error of the estimated internal camera parameters and point cloud in the SfM-MVS method. The acquired photographs, GCPs, and scale bars were used as inputs in the SfM-MVS method through 1. 6. 2 (agisoft. com) to reconstruct a 3D model of the scene captured by aerial photographs. Specifically, DSMs and orthomosaics of each reef were reconstructed (Fig. 1d, e). For a comprehensive description of the SfM-MVS method, the reader is referred to Westoby et al. (2012) and Carrivick et al. (2016). To validate the DSMs, IMs were collected at each site. Over the entire study area, the height of 51 corals was measured with a meter rod in situ to the nearest centimeter.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Also, potentiated inhibition with learning is less likely to account for a decrease of average excitatory activities - a temporal profile of inhibitory activities after learning shows a decrease of activity almost to the baseline in the late phase of the stimulus presentation (200–250 ms after the stimulus onset). This suggests that the effect of potentiated inhibition in the late phase is weaker than in the early phase while reduction of excitatory activities was observed in the late phase (Figure 1A,B). Another possibility is a depression in recurrent excitation through different types of synapses such as potentiation in fast AMPA-like currents and depression in slow NMDA-like currents. Depression in slow excitatory currents can lead to a decrease in excitatory activities in the late phase. However, different regulation of AMPA and NMDA currents is inconsistent with the experimental observations showing maintenance of a constant NMDA-to-AMPA ratio under the changes of AMPA receptors induced chemically or by an STDP protocol (Watt et al. , 2000; Watt et al. , 2004). Instead of additional changes of the recurrent synaptic inputs, we considered changes in external inputs with feedforward synaptic plasticity ΔWijF=fF(ξi)gF(ξj). Together with overall potentiation in the recurrent connections, dominant depression in the feedforward connections with f¯F< 0 can reproduce the reduction of average responses over the stimuli with learning. 4, an example network with Hebbian learning rule in recurrent connections, uniform depression in the feedforward connection, and spike adaptation mechanisms was shown to reproduce the effects of visual learning qualitatively. With learning, the average response decreases in particular in the late phase (Figure 4A), but maximal firing rates increased and oscillation becomes prominent especially in high rates (Figure 4B,C). Also, in the successive presentation of two stimuli, the average response shows stronger oscillation after learning (Figure 4D), while the rank of individual neuronal activities changes when a new stimulus arrives (Figure 4E,F). Figure 4 Download asset Open asset Example network reproducing the effects of visual learning in one stimulus presentation (A–C) and successive presentation of two stimuli (D–F). The network implements potentiation in the recurrent connections through Hebbian synaptic plasticity, depression in the feedforward connections through uniform scaling down of the external inputs, and spike-adaptation mechanisms.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Censusing and monitoring black rhino (Diceros bicornis) using an objective spoor (footprint) identication technique. —J. Zook 254: 1–16. 10. 1017/S0952836901000516 Web of Science®1995. Estimating tiger Panthera tigris populations from camera-trap data using capture—recapture models. —Biol. Conserv. 71: 333–338. 10. 1016/0006-3207(94)00057-W Web of Science®1998. Estimation of tiger densitites in India using photographic captures and recaptures. —Ecology 79: 2852–2862. 10. 1890/0012-9658(1998)079[2852:]2. 0. CO;2 Web of Science®2003. Science deficiency in conservation practice:the monitoring of tiger populations in India. —Anim. Conserv. 6: 141–146. 10. 1017/S1367943003003184 Web of Science®2008. Design, evaluate, refine: camera trap studies for elusive species. —Anim. Conserv. 11: 182–184. 10. 1111/j. 1469-1795. 2008. 00179. x Web of Science®1997. field guide to African mammals. —Academic Press. 10. 1111/j. 1744-7429. 1998. tb00369. x 2001. Validation of a rigorous track classification technique: identifying individual mountain lions. —Biol. Conserv. 99: 313–321. 10. 1016/S0006-3207(00)00197-X Web of Science®2005. A field guide to the animal tracks of southern Africa; and Johannesburg. —Publ. 2008. Comparing methods for sampling large- and medium-sized mammals: camera traps and track plots. —Eur. J. Wildl. Res. 54: 739–744. 10. 1007/s10344-008-0205-8 Web of Science®2013. Calibrating a camera trap—based biased mark—recapture sampling design to survey the leopard population in the N'wanetsi concession, Park, South Africa. —Afr. J. Ecol. 51: 422–430. 10. 1111/aje. 12047 Web of Science®2006.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Both in situ and 2D rugosity were calculated by dividing the length obtained following the shape of the terrain (i. e. , bottom profile) with the linear distance (for our case, it is 20 m for each transect) between starting and ending points of the transect (Fig. 3a). The 3D rugosity was calculated using the same method but buffering the digital transect line 0. 5 m on each side. In this case, the 3D surface (DSM) was divided by 20 m2 (as the transect swath is 20 m long and 1 m wide). The closer the rugosity is to zero, the flatter is the terrain. Fig. 3a Difference between in situ vs 2D rugosity; b Histograms representing reef rugosity as calculated in situ and from the DSMs (2D and 3D rugosity, see text); c linear relationships (fitted lines and confidence intervals) between the in situ rugosity and the DSM-derived rugosity (both 2D and 3D). The dotted line shows the 1:1 relationship for referenceFull size imageResults and discussionThe average resolution of the reconstructed orthomosaics and DSMs is 0. 3 cm pix−1 and 0. 6 cm pix−1, respectively. The average XY and Z errors on GCPs are 120 and 7 cm, respectively (see and Report). Comparing the coral heights measured in situ (IMs) with those estimated using corrected and uncorrected DSMs, we find that using refraction-corrected DSMs reduces the root-mean-square error (RMSE) from 21 to 10 cm (Fig. 2b). The variation across sites is reported in the Supplementary Table. It is noteworthy that coral height is still underestimated in the corrected DSMs, albeit slightly. Compared to uncorrected DSMs, which underestimate coral heights by 35% (this is due to the current limits of the method and the propagation of DSM errors, James et al. 2017), corrected DSMs underestimate them by 13%. We argue that such correction is effective when flying at a low altitude (e. g. 10 m) and collecting near-nadir images on very shallow areas. The incident and refracted angles of the light ray should be very small (< 15°) for the correction equations to hold true.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Mean responses reproduce the effects of visual learning predicted in the mean-field dynamics, showing average reduction and stronger oscillations (A, D). Representative individual activities before (B,E) and after (C,F) learning show that activities in neurons with high firing rates increase with strong oscillation after learning (E,F), but the rank of stimuli is shuffled with the arrival of a new stimulus. Figure 4—source code 1 code for Figure 4. Download elife-44098-fig4-code1-v2. m Note that the mean field dynamics was derived under the assumption of linear dynamics. With synaptic or neuronal nonlinearity, some conditions identified through our mean field dynamics can be mitigated such as less dominant potentiation in recurrent inputs with learning (Figure 6—figure supplement 1). However, a network simulation with example nonlinearity still shows that the core principles on the synaptic plasticity rule remain the same as strong potentiation in recurrent connections in high rate neurons, and average depression in feedforward inputs. Network simulation and comparison with data In this section, we validate that network models implementing the conditions identified through mean-field equations indeed reproduce the experimental observation and allow us to infer the post-synaptic dependence of synaptic plasticity. To illustrate this, we considered electrophysiological data obtained in a passive viewing task and dimming-detection task (Lim et al. , 2015; McKee et al. , 2013; Woloszyn and Sheinberg, 2012). In the dimming detection task, responses to fewer stimuli were measured, and we considered the response averaged over neurons and stimuli, which was fitted using mean-field dynamics (Figure 5). The external inputs and parameters of the r¯ and a¯ dynamics before learning were chosen to generate no oscillations (Figure 5A; Figure 5—figure supplement 1). Potentiation in high firing rate neurons, average potentiation of recurrent inputs and depression in feedforward inputs were found to mimic response to familiar stimuli (Figure 5B). Figure 5 with 3 supplements see all Download asset Open asset Comparison between network simulation and data obtained in a dimming-detection task. (A, B) Fitting response dynamics (red in A and blue in B) using mean-field equations (gray in A and black in B) for novel (A) and familiar (B) stimuli.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Figures AbstractThe conservation of gray wolf (Canis lupus) and its coexistence with humans presents a challenge and requires continuous monitoring and management efforts. One of the non-invasive methods that produces high-quality wolf monitoring datasets is camera trapping. We present a novel monitoring approach where camera traps are positioned on wildlife crossing structures that channel the animals, thereby increasing trapping success and increasing the cost-efficiency of the method. In this way we have followed abundance trends of five wolf packs whose home ranges are intersected by a motorway which spans throughout the wolf distribution range in Croatia. During the five-year monitoring of six green bridges we have recorded 28 250 camera-events, 132 with wolves. Four viaducts were monitored for two years, recording 4914 camera-events, 185 with wolves. We have detected a negative abundance trend of the monitored Croatian wolf packs since 2011, especially severe in the northern part of the study area. Further, we have pinpointed the legal cull as probable major negative influence on the wolf pack abundance trends (linear regression, r2 > 0. 75, P < 0. 05). Using the same approach we did not find evidence for a negative impact of wolves on the prey populations, both wild ungulates and livestock. We encourage strict protection of wolf in Croatia until there is more data proving population stability. In conclusion, quantitative methods, such as the one presented here, should be used as much as possible when assessing wolf abundance trends. Citation: Šver L, Bielen A, Križan J, Gužvica G (2016) on Structures as a Tool in (Canis lupus) Management - Five-of Trends in Croatia. 11(6): e0156748. Bi-: January 28, 2016; Accepted: May 19, 2016; Published: June 21, 2016Copyright: © 2016 Šver et al. This is an open access 2005. Between the years 2006 and 2010 wolf population seemed stable—estimated number was slightly higher than 200 individuals inhabiting the mountain areas of and Lika, and also a part of Dalmatia, southern Croatia [8]. The main problem of wolf management in this period was poaching and a negative attitude of livestock breeders and hunters toward wolves. Therefore, a legal cull of up to 10% of the estimated population in the areas with highest negative impact on livestock was allowed.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Javascript is disabled in your browser. Please enable Javascript to view PeerJ. Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs All reviews of published 2023. Peer reviewers are encouraged (but not required) to provide their names to the authors when submitting their peer review. If they agree to provide their name, then their personal profile page will reflect a public acknowledgment that they performed a review (even if the 2023. The first revision was submitted on August 3rd, 2023 and was reviewed by 1 reviewer and the Academic Editor. A further revision was submitted on October 2nd, 2023 and was reviewed by 1 reviewer and the Academic Editor. The 2023. Version 0. 3 (accepted) · Oct 9, 2023 · authors have given responses to all the queries of the reviewers. Hence, I accept this manuscript after some minor revisions. However, I advise the authors to follow an important suggestion of the reviewer to include the graphical representations of the sponge morphology as described in the discussion. [# PeerJ - this decision was reviewed and approved by Xavier Pochon, a PeerJ covering this Section #] · Oct 3, 2023 Basic reporting This is the second version. The changes have been made by the authors. Experimental design Refer previous comments. No further changes required. Validity of the findings Refer previous comments. No further changes required. Additional comments Refer previous comments. No further changes required. Cite this review as (2023) #4 of "Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (v0. 3)". PeerJ 0. 3 (PDF) Download author's response letter - submitted Oct 2, 2023 Version 0. 2 · Sep 14, 2023 · The authors have done substantial revision but it needs some more improvement for this manuscript to be published, hence I advise minor revision as per the reviewer's comments. · Sep 14, 2023 Basic reporting 1. The language is clear and comprehensible. 2. Literature cited is recent. 2022 (7), 2021(31) 3. The sources of the meta data have been cited. 4. 0. 2)". PeerJ 0. 2 (PDF) Download author's response letter - submitted Aug 3, 2023 Version 0.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: (C,D) Simulation for one stimulus presentation (C) and successive presentation of stimuli (D). The gray horizontal bar represents the visual stimulation period starting at 500 ms and x-axis is truncated to show activities from their onsets. In A-C, the stimulus was presented for a duration that was a sum of a fixed duration (650 ms shown in the dark gray) and a random duration (shown in the light gray). In D, different gray bars represent different stimuli shown alternatively for a duration of 150 ms. Figure 5—source code 1 Data for Figure 5. Download elife-44098-fig5-code1-v2. mat Figure 5—source code 2 code for Figure 5. Download elife-44098-fig5-code2-v2. m This mean-field dynamics reproduces prominent features of response dynamics before and after learning, showing damped oscillation and a decrease in average response to familiar stimuli after its peak (Figure 5C). Furthermore, we simulated the mean response to novel and familiar stimuli for a successive presentation of stimuli (Figure 5D). When novel stimuli are repeatedly shown, the peak response to the second stimuli is smaller than the response to the first, due to a slow recovery from the adaptation current. In contrast, for the serial presentation of familiar stimuli, the response to the first stimulus decays quickly and the response to the second stimulus is less affected by the adaptation current. Thus, the overall response becomes more oscillatory compared to the one for novel stimuli. In the experimental data obtained during the passive viewing task, the duration of stimulus presentation was shorter, but the distribution of response dynamics before and after learning could be obtained (Figure 1C; Materials and methods). As in the dimming detection task, the external inputs were obtained from the responses to novel stimuli. By comparing the response dynamics at each rank of the novel and familiar stimuli, we derived the post-synaptic dependence of synaptic plasticity in recurrent and feedforward connections. Note that the synaptic plasticity was inferred from normalized firing rates averaged over neurons under the assumption that the dependence of synaptic plasticity rules on normalized firing rates is the same across different neurons (for justification). Consistent with the fitting of the mean-field dynamics to the data obtained in a dimming detection task, the average post-synaptic dependence of synaptic plasticity leads to potentiation in recurrent inputs and depression in feedforward inputs (Figure 6A).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Main objectives of this study were (i) to test the cost-efficiency of camera traps on wildlife crossing structures in monitoring wolf population trends, and (ii) to evaluate the role of legal harvest in the decreasing wolf abundance trends. Thus, we have followed abundance trends of several Croatian wolf packs during a five year period using the camera trap monitoring data from six green bridges and four viaducts. We demonstrate the cost-efficiency of such approach and we have identified the cull quota as a probable major negative influence on wolf packs in southern Croatia. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 1. Investigated green bridges and viaducts. (A) Map of Croatia showing positions of the monitored green bridges and viaducts along the A1 motorway and wolf pack home ranges. Wolf range in Croatia is depicted in yellow. Total number of recorded photographs/movies with wolves on green bridges and viaducts is shown in blue and green, respectively. Map of Croatia representing motorway network was obtained from Administration (Republic of Croatia) and is used with their permission; (B) Night-time wolf pack photograph on the viaduct MP; (C) Daytime wolf photograph on the green bridge IB. Green bridges: IB—Ivačeno brdo, MG—Medina gora, VAR—Varošina, OSM—Osmakovac, RO—Rošca, KON—Konšćica; viaducts: GRABA—Graba, SUV—Suvaja, MP—Mandarića potok, —Grabara. Materials and area and monitored wolf packs The A1 motorway is a major north-south transportation corridor in Croatia (478. 9 km, Fig 1A). Both sides of the motorway are fenced with approximately 2 m high wire mesh along entire length. Numerous wildlife crossing structures channel the animals, enable their migration across the motorway and minimize habitat fragmentation [18]. Our study included 325 km of A1 passing through the wolf range (Fig 1) [9,19].

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: 1 (original submission) · Mar 22, 2023 · This study is relevant to understanding the structure of sponge communities and sponge host-guest interaction networks across tropical coral reefs. Three reviewers have given their comments and suggestions to improvise the manuscript. Reviewer 2 has given elaborate guidance on how to improvise this manuscript and pointed out that "the ecological context and the hypotheses to elucidate an overall pattern beyond what previous studies have found are not clearly stated". Hence, follow all reviewers' comments and suggestions carefully and revise the manuscript. [# PeerJ Staff Note: Please ensure that all review and editorial comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. #] [# PeerJ Staff Note: The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at copyediting@peerj. com for pricing (be sure to provide your manuscript number and title) #] · Mar 12, 2023 Basic reporting - The authors should improve English grammar and usage. - The authors should provide locations in Figure 1 - The authors should give clear hypotheses Experimental design - Provide clearer research questions - The authors should provide details of the methods. Validity of the findings - Provide clearer conclusion Additional comments - This manuscript should be improved for better understanding of the readers. Cite this review as (2023) #1 of "Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (v0. 1)". PeerJ Reviewer 2 · Mar 15, 2023 Basic reporting This manuscript evaluates through a meta-analysis (= a statistical analysis that combines the results of multiple scientific studies) the structural importance of sponge species in hos-guest interactions. The hosts' structural importance is based on two functional traits, sponge species' accumulated geographical area and sponge morphology. The meta-analysis is based on a filtrated version of the bibliographic database by Pérez-Botello and Simões, 2021( and includes records at the species level. An ecological network analysis, a Model (GLM), a Ordination (PCO), and an Analysis of Variance (ANOVA) were utilized to identify holistic properties within host-guest interactions. Overall this study is relevant to understanding how sponge communities structure and how much associated biodiversity they host.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Furthermore, the post-synaptic dependence in recurrent connections is an increasing function of the rank of stimuli, or equivalently, the post-synaptic activities. It is notable that such a tendency is similar to the dependence of the rebound magnitude to familiar stimuli on the rank of stimuli observed experimentally (Figure 1D). Network models implementing the derived synaptic plasticity reproduce the reduction of average activities (Figure 6B) and rebound in the late phase of stimulus presentation in both average and maximal responses, although the maximal response after the initial rise is less well fitted (Figure 6C). Figure 6 with 3 supplements see all Download asset Open asset Post-synaptic dependence of synaptic plasticity in recurrent (left) and feedforward (right) connections derived from a passive viewing task (A) and comparison between the data and network simulations for average (B) and maximal (C) responses. The external inputs were chosen so that the response to novel stimuli is the same in the experiment and simulation (red in B,C). With the derived post-synaptic dependence in the recurrent and feedforward connections (A), the response to familiar stimuli was simulated (black in B,C). Figure 6—source code 1 code for Figure 6. Download elife-44098-fig6-code1-v2. m We also checked whether the key conditions for synaptic plasticity change with example nonlinear input-output transfer function derived from the time-averaged response to novel stimuli (Figure 6—figure supplement 1A). The derived post-synaptic dependence in both recurrent and feedforward connections is similar to that obtained under linear dynamics with more balance between depression and potentiation in recurrent synaptic plasticity (Figure 6—figure supplement 1B). Although the rebound in the average activities is less well fitted compared to that with linear dynamics, the network simulations agree with the data qualitatively (Figure 6—figure supplement 1C,D). Alternative negative feedback mechanisms Our mean field analysis and model fit to the data suggest firing rate adaptation mechanisms as a good candidate for slow negative feedback to explain the familiarity effect on the dynamics. Here, we explored whether two alternative negative feedback mechanisms such as delayed global inhibition or short-term depression can replace adaptation. Delayed global inhibition may arise due to local inhibition with slow NMDA- or GABAB-like currents in inhibitory feedback pathways, or inhibitory feedback from other areas.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Wolf population trend is presented as a total number of events (photographs of wolf/wolves) recorded on Dalmatian green bridges. The data for the legal cull in the corresponding Split-during the monitoring period was extracted from the literature. of camera traps on green bridges and viaducts in wolf monitoring We used camera trapping for the five-year monitoring of wolves in Croatia. Camera trapping allows precise species identification and has often been used in monitoring of large carnivores [1,11,14–16,28]. In order to increase the trapping efficiency, cameras are usually positioned in a raster arrangement and either equipped with a bait [11,15] or placed in an area known to be used by target individuals [14,16]. Contrary to this, we positioned the camera traps linearly, i. e. on wildlife crossing structures along the major motorway passing through the wolf range in Croatia. We used this camera trapping design to follow wolf abundance trends. To confirm the efficiency of the method, it was important to include a positive control—namely, external data on the number of wolves living in the area of at least one crossing structure. In our case, possible source of such data are annual estimates of wolf abundance per pack published by for (SINP, Republic of Croatia) [9,22–26]. However, these assessments are, apart from harvest data and damage statistics, largely based on non-quantitative methods [such as collecting wolf presence signs, interviews with local people (non-experts), expert assessments and estimates in hunting grounds]. Therefore, we have used another line of evidence to choose which SINP pack census should be reliable: an unpublished telemetry dataset of male wolf that we monitored for 14 months during 2009 and 2010 (at the beginning of the monitoring period presented here). This GPS-collared wolf was captured in the vicinity of green bridge Osmakovac and our unpublished data show it crossing the green bridge. Thus, we have compared the sizes of wolf pack OSM (Vučevica) estimated by SINP over the monitoring period with our data and show that these two curves fit well (S3 Fig).

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: However, the ecological context and the hypotheses to elucidate an overall pattern beyond what previous studies have found are not clearly stated. In addition, the network analysis presentation disregards the hosts' functional traits and lacks ecological relevance. The assigned morphological characteristics of the species are not specified and could be biased. The PCO is not discriminated by functional traits (or factors), so observing grouping by sponge functional patterns is impossible. Overall, the discussion of the manuscript lacks the ecological context and background on sponge morphology (incorrect assignments for many species), sponge-host interactions and fails to support the conclusions. The discussion travels too far from the data. It does not focus on what the data prove or demonstrate how the obtained results expand previous knowledge or support and challenge previous paradigms. In addition, the manuscript's English language and writing style needs improvement. Experimental design The experimental design (how many studies and from which locations were finally used for this specific metanalysis? ) is not specified. How many records of host species were assessed per location? What is the bias in terms of replication? Please include this information in the methods. Also, the tables in the with associated fauna and records should be merged, and a column with the location for each study should be included. Validity of the findings PCO figure should be discriminated by functional traits (i. e. , morphology). The network, patterns, and major contributors to the network structure are poorly explained. Overall, the results do not clarify how host-guest interactions vary based on functional groups; what are the major patterns? And how it varies across species. Figure 1. This figure refers to all the records obtained by the network and is not specific to the records used in this study after filtration. I suggest correcting this figure and including only the records used in this study after the data was filtrated (many records come from the same authors, so that you could add numbers or color-code per author). Also, adding the replicates (n= the number of host-species interactions) per location can help to understand the contribution of the studies and the number of records per location. Figure 2- This figure, as it is, lacks the most relevant information related to the functional characteristics of sponges. To explicitly show the functional characteristics of sponges and how they connect to specific hosts, sponges should be divided by functional characteristics such as 1. generalists and specialists, 2.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: For instance, prefrontal cortex shows a familiarity effect with a long latency around 100 ms but with opposite sign (Rainer and Miller, 2000; Xiang and Brown, 2004), and thus, the top-down signals from this area can serve as slow negative feedback. We considered a model of global inhibition so that all excitatory neurons receive the same slow inhibition whose strength is proportional to the average activity of excitatory neurons (Materials and methods). Under the assumption of linearity, we could derive the mean field equations similar to that with adaptation mechanisms with variables r, a and m but without variable n that mainly represents the negative feedback in high firing rate neurons (Equation (6)). Without negative feedback, m cannot generate damped oscillations after learning in both high rate neurons and the overall population. This suggests that slow negative feedback private to individual neurons or sub-populations is required to generate qualitative changes in dynamics as interacting with synaptic plasticity. Short-term depression in synaptic connections has also been suggested as a mechanism for negative feedback and generating oscillations in cortical circuits (Laing and Chow, 2002; Loebel and Tsodyks, 2002; Tabak et al. , 2006; Wang, 2010). To see whether short-term depression can reproduce the damped oscillatory response after learning, we considered a phenomenological model mimicking the effect of depletion of a neurotransmitter such that when the pre-synaptic firing is high, the synaptic input from such neuron becomes weak due to the lack of resources (Materials and methods; Tsodyks and Markram, 1997). Under the assumption that the recurrent connection is weak before learning, and the damped oscillation in the network is led by that in the high rate neurons, we searched for a parameter set of the strength and timescale of short-term plasticity that provides the best fit to the experimental data. However, the network simulation with the best-fitted parameters cannot generate a strong rebound, unlike the adaptation mechanisms (Figure 6—figure supplement 2). Thus, a simple phenomenological model of short-term plasticity cannot explain the qualitative changes in response dynamics observed experimentally. this work, we provided a mechanistic understanding of how interactions between synaptic plasticity and a negative feedback mechanism implementing firing rate adaptation shape response dynamics with learning. The emergence of damped oscillations after learning requires strong positive feedback through potentiation in recurrent connections particularly among neurons with high firing rates.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Further, our results show a general negative abundance trend of the monitored wolf packs since 2011 and this is in agreement with the annual estimates of wolf abundance for the whole Croatia between 2009 and 2014: 215 individuals in 2009, 230 in 2010, 193 in 2011, 198 in 2012, 177 in 2013, and 168 in 2014, distributed in a2. 5 years before the beginning of the study and therefore we cannot exclude the possibility that low number of recorded events in the first two to three monitoring years is due to still ongoing habituation. Our approach should be well suited for wolf monitoring since wolf packs were shown to have stable home ranges for as much as 10 years [30–32]. Based on the available literature on wolf pack home ranges in Croatia and elsewhere, their size and the fact that they are not overlapping, we assumed that monitored green bridges were used throughout the five-year monitoring period by the same wolf packs [9,20,22–26,33]. Consequently, when we detected a significant decrease in number of crossings, we assumed that the cause was the decrease in pack size, and vice versa. Of course, it is possible that some wolves (e. g. dispersing individuals) migrated away from the crossing structure and therefore stopped appearing in recordings later on (due to altered behavior and not to death), but such events should be rare and should not significantly affect overall wolf pack abundance trends. Noteworthy, our monitoring setting can be applied to follow abundance trends, but not to make a quantitative estimate of wolf density (e. g. to estimate wolf abundance). Firstly, recognition of individuals, crucial for capture-recapture statistical modeling of population sizes, was not possible due to the absence of distinctive individual markings in wolves. Camera traps are mostly used to estimate the abundance of felids with coat patterns enabling individual recognition [34]. Further, external conditions (such as night-time, heavy rain or fog) often negatively affected the quality of recorded photographs/movies, and recognition of details was not possible. Although the method for density estimation without the need for individual recognition exists [35], it could not be applied here because cameras were not placed randomly with respect to animal movement. In conclusion, the method presented here has many advantages over the traditional camera monitoring setups, as summarized in Table 2. Most importantly, the long-term expenses of our setup are acceptable because the same dataset can be used in multiple monitoring studies.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: accumulated geographic area, and 3. morphology of host sponges. Figure 3. Add the species in colors or morphological characteristics to this figure to detect any pattern in species or morphology and in relation to accumulated geographic area. Figure 4- The photograph selected to represent encrusting species is from an “excavating” sponge, not from an encrusting species, and the spherical representative species is a common massive species; as their growth patterns vary, please select a typically spherical species. Checking the supplementary list, I found several errors related to the morphology assigned to the species. I recommend you include/collaborate with a sponge expert taxonomist or ecologist to re-organize this data. 284-287- Vague sentence “However, our findings have the potential to provide new insights into predicting the functional responses of faunal assemblages associated with sponges to potential species extinctions in endangered coral reef ecosystems. ” Please specifically state how the study results provide new insights into predicting the functional responses. Lines 292-301- This section in the discussion has interesting statements. However, it is vague and does not express why the results are important and how this knowledge contributes to the structure of interaction networks in sponge communities and associated fauna “Galiana et al. (2018) proposed a relationship between geographic area and the probability of establishing a species interaction. Especially they found that widespread species are more likely to interact with other species. Our results indicate that as the sponge's accumulated geographic area increases, so does the potential for interactions with other organisms” The authors mention that widespread sponge species (as sponge accumulated geographic area) tend to have more potential for interactions with other organisms. Still, it does not specify which species of sponges are those and with which organisms those interactions occur. Instead, keep generalizing “Widely distributed sponge species are found to be particularly important in shaping the structure of the interaction network". Please explain what significance you found in your results. The following sentence is general and does not expose the relevance of the results or why it is important in the context of this study “The positive relationship between the importance of a sponge species within the contribution to network organization and its accumulated geographic area is crucial to understanding the significance of these widely distributed sponge species and the vulnerability of specific geographically restricted interactions.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Such recurrent synaptic plasticity broadens the distribution of activities, while depression in feedforward inputs decreases average firing rates. Synaptic plasticity, therefore, enables the sparse and efficient representation of the learned stimuli. Furthermore, the strength of rebound of damped oscillation observed after learning can be a novel, graded measure for recurrent synaptic plasticity. On the other hand, adaptation-like mechanisms are critical for enhanced oscillatory responses after learning, and strongly suppresses the neural activities for the learned stimuli in particular in the late phase of the stimulus presentation. As such temporal sharpening prepares neurons to respond to the subsequent stimulus, our work suggests that the adaptation mechanisms together with synaptic plasticity may play an important role in the rapid processing of the learned stimuli. Here, we extended our previous work inferring recurrent synaptic plasticity rules from time-averaged data in a static model of a cortical network to time-course data and a dynamic model with additional spike adaptation mechanisms and feedforward synaptic plasticity (Lim et al. , 2015). Analyzing time-course data allows disentangling contributions of synaptic plasticity in different connections. However, similar to the previous work, only post-synaptic dependence of the synaptic plasticity rules can be inferred from single cell recordings under the assumption that the learning rules are a separable function of pre- and postsynaptic rates. Also, fitting the time course poses a limitation such that synaptic plasticity rules needed to be inferred from the data averaged over neurons due to noise. On the other hand, time-averaged data allows to infer recurrent synaptic plasticity in different neurons, which reveals a strong correlation between neural activity and the threshold separating depression and potentiation, but no correlation when the post-synaptic activity is normalized (Lim et al. , 2015). Inspired by this observation, we inferred synaptic plasticity rules from normalized firing rates under the assumption that synaptic plasticity rules are the same across different neurons when inputs and rates are normalized (Figures 1 and 6). Although a direct test of this assumption is not feasible, the relatively small variance of rebound strengths over neurons may support this assumption on the recurrent synaptic plasticity as the dependence of rebound strengths on the rank of stimuli alternatively represents learning rules in recurrent connections (Figure 6C).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Namely, crossing structures act as funnels that channel diverse animals, without the need to aim at a particular target species. Cost reduction should be especially significant when monitoring scarce animals with large home ranges such as wolves. To show the cost efficiency of our method, we have compared our setup with camera trapping designs from the literature (Table 3). In general, cost of the study lowers (i) with the reduction in the number of camera traps per km2 and (ii) with increasing intervals between field camera trap data collection. Both parameters are highly cost-effective in our case, compared to other monitoring designs (Table 3)—we have used only 0. 01 camera traps per km2 and frequency of field trips was only once a month. Despite these low costs, we were able to estimate abundance trends of five wolf packs. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 2. Benefits and limitations of camera traps on crossing structures used as a wildlife monitoring tool. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 3. Cost-efficiency of various camera trapping studies. Evaluating the role of legal cull in the descending wolf abundance trends Using described methodology we confirmed that northern and southern wolf packs lived in ecologically different situation, primarily because of differences in available prey. Most important wolf's natural prey in and Lika are wild ungulates [6,20,21]. We confirmed that prey of the northern packs are roe deer, wild boar and red deer. This is evident from the high number of events of natural prey on IB, MG and VAR and low percentage of domestic animals killed by wolves in Karlovac and Lika-Senj Counties. Further, the trend of an increase in the number of natural prey events (mostly roe deer) was observable in the last two monitoring years on IB, MG and VAR. This coincides with very small number of recorded wolves for these locations and period, and implies that small number of wolves could contribute to the increase in prey population size. The importance of wolf predation in limiting reindeer Rangifer tarandus population growth in Finland was reported previously [39]. However, in our case no statistically significant correlation between number of wolf events minimal wolf pack size and total number of natural prey events could be established. Low abundance of natural prey can stimulate wolves to prey on livestock [40].

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: ” Lines 328-329- The authors focus on functional characteristics of the sponge they did not measure, such as the physical structure of the sponges (volume, oscula size, number of tubes), but their never organized sponge species based on these characteristics for their analyses. The only morphological characteristic is general morphology, which seems biased, as not all photographs match the correct morphological characteristics for the representative species (i. e. , Figure 4). Lines 324-327- How do you verify that organisms inside the internal space were not excluded in encrusting species? Also, the internal space was not quantified, measured, or even supported by referenced research for each species. Therefore this statement is invalid “This sponge network importance, biological, translates to the fact that morphos that promote spatial micro-compartmentalization could support a more diverse community of associated fauna than morphos with less internal space”. What do you define as micro-compartmentalization? The limitations of this study are not clearly stated in the discussion. There is no clear context for the findings concerning previous literature and results. Lines 343-366- If you want to discuss the relevance of sponge-host interactions concerning chemical defenses, please categorize the species in your metanalyses based on chemical defenses and then evaluate directly in the network analyses your findings. I encourage the authors to include this hypothesis in their network analysis, make it part of this research, focus the network analysis, and develop a more substantial discussion. Additional comments Formatting and English language needs improvement to communicate ideas better so an international audience can understand your text. For example, the first line of the abstract, "Sponges have widely spread organisms in the tropical reefs", should be rephrased; sponges are organisms; they do not have organisms. Also, "behaving like ecosystem engineers" should be replaced by ecological terminology such as "they structure ecosystems". In addition, throughout the text, statements are placed without connecting ideas. For example, in the first paragraph of the introduction, the following three statements are three disconnected sentences of definitions that lack connective words between them "The ecology of a species or community can be studied based on the functional characteristics of organisms (Gagic et al. 2015; Schmitz et al. 2015; Pimiento et al. 2020).

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Furthermore, if the learning rule inferred from the time-averaged response is the combination of recurrent and feedforward synaptic plasticity, the same learning rules of this mixture and recurrent connections across different neurons would justify the assumption on the feedforward plasticity (Figure 6—figure supplement 3). Our work provides a reconciling perspective between two prominent classes of synaptic plasticity models suggested for familiarity detection and associative memory in ITC. Depression in the feedforward connections required to lower average response after learning reasserts the role of feedforward synaptic plasticity suggested for familiarity detection (Bogacz and Brown, 2003; Norman and O'Reilly, 2003; Sohal and Hasselmo, 2000). On the other hand, most theoretical works implementing synaptic plasticity in recurrent connections have focused on associative memory and the emergence of attractors with learning (Amit and Brunel, 1997; Pereira and Brunel, 2018; Sohal and Hasselmo, 2000). Unlike most of the previous works focusing on one-type of synaptic plasticity, our analysis proposed that both recurrent and feedforward synaptic plasticity are required to reproduce changes in spatial and temporal patterns underlying familiarity detection. A recent study investigated the memory capacity for associative memory under recurrent synaptic plasticity whose form was derived from neural activities related to familiarity detection (Pereira and Brunel, 2018). Similarly, it can be further investigated how the feedforward and recurrent synaptic plasticity rules derived from the data for familiarity detection contribute to other types of memory, and how a memory capacity changes dynamically during the stimulus presentation with slow spike adaptation mechanisms. As a substrate for slow negative feedback, firing rate adaptation mechanisms have been suggested to be critical in generating network oscillations and synchrony (Ermentrout et al. , 2001; Fuhrmann et al. , 2002; et al. , 2004; Laing and Chow, 2002; Tabak et al. , 2006; van Vreeswijk and Hansel, 2001; Wang, 2010), and in optimal information transmission under a particular form of synaptic plasticity (Hennequin et al. , 2010). The effect of synaptic plasticity on enhancing synchrony in the recurrent synaptic circuits also has been explored theoretically (Gilson et al. , 2010; Karbowski and Ermentrout, 2002; Morrison et al. , 2007).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: the face of global biodiversity loss that threatens social–ecological sustainability, we must improve our knowledge of species' behaviours, life histories and populations. Enhanced understanding is especially critical for taxa like seabirds that live in remote habitats where monitoring is logistically challenging, and technology-based approaches could lead to major advances. Considering conservation threats and breeding behaviours, penguins represent a promising taxon for further exploration of monitoring methods. Only five of 18 penguin species are currently considered species of by the IUCN, and the sensitivity of penguins to ecological disturbances makes them important indicators of ecosystem dynamics. Penguins regularly congregate in dense breeding colonies and are visually and aurally conspicuous animals, making them relatively easy to monitor in some respects. In situ observations and visual remote sensing monitoring methods (i. e. camera traps, uncrewed aerial vehicles and satellite imagery) currently provide highly valuable information on penguin behaviour and population dynamics, but these methods have a number of shortcomings. Several rely on human presence in remote areas, some require clean lines of sight with no visual obstructions, and some offer limited spatial and temporal resolution. In this study we explore the use of passive acoustic monitoring (PAM) as a complementary remote sensing method to monitor penguin behaviour and populations at high spatial and temporal resolution without visual constraints or the need for continuous human presence. We conducted observations of vocalization rates and placed automated acoustic recorders in colonies of Spheniscus magellanicus and chrysocome in conjunction with camera traps. We found positive relationships between acoustic activity and counts of in camera trap photos. We also identified clear diel patterns of acoustic activity that differed between breeding stages, and we found positive correlations between acoustic activity and estimates of colony density for various times of day and radii around recorders. While much work remains to improve this method and refine interpretation, PAM holds great promise as a complementary tool for monitoring the relative abundance and behavioural dynamics of penguins and other colonial animals, particularly those that burrow or nest in dense vegetation that impairs visual monitoring techniques.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: A functional trait is an organism's distinguishable and quantifiable attribute, typically evaluated at the individual level and compared across different species (Poff et al. 2006; Weiher 2011). Classifying biodiversity according to some trait or functional group emphasizes the phenotypic differences between taxa and breaks the species ancestor-descendent phylogenetic link (McGill et al. 2006; Weiher 2011; Gagic et al. 2015; Bagousse-Pinguet et al. 2019). " The connection between statements and ideas needs to be clarified throughout the document. Repetition of statements without explicitly mentioning how this study contributes and connects to previous work is found in the introduction and discussion. Format- Several mistakes, including misspellings of species names “ Aplisyna“ and words Line 503 “Graunds”, grammar Line 59 “2020). . ”, and scientific notation Line 222 “10m2”, are found throughout the text. Also, some 0. 1)". PeerJ Reviewer 3 · Mar 21, 2023 Basic reporting • language should be improved to ensure that an international audience can clearly understand your text. English grammar and punctuations to be thoroughly checked. • Spell checks to be done. • Spacing and alignment issues in manuscript to be looked into. • Introduction & background needs more elaboration, needs more detail. • Literature well referenced & relevant. • Discussion is not adequate, I felt. • Discussion should be focusing more on the results obtained. • Introduction portions are in Discussion, to be re framed. • Figures are relevant, quality needs to be improved in some figures, however, I have suggested some changes in legend colouring in the map. Experimental design • Research question well defined, relevant & meaningful. However, authors should clearly mention the knowledge gap their research fills. • Methodically explained the steps of conducting this research. The methodology looks good. • The text needs to be more seamless. It feels very disjointed as if each section is written by a different co-author. There is a dissonance in the writing, making it a little difficult for the reader to quickly comprehend. Validity of the findings • Conclusions are linked to the original research question & are supporting results. However, it does not link well with the discussion. It is advised to rework the discussion part for writing a better conclusion. • All underlying data have been provided.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Consistent with these previous works, our work suggests that the interplay between synaptic plasticity and adaptation with the time constant consistent with that of cellular adaptation mechanisms (Benda and Herz, 2003) generate synchronous damped oscillations after learning. Note that our analysis based on the data obtained from single cell physiology is limited to firing rate synchrony, and how spike-time correlation between neurons changes with visual learning needs to be further explored. Also, our work emphasizes the role of adaptation in different types of recognition memory. Previously, the adaptation mechanisms in the temporal cortex have been suggested to encode the recency of stimuli, which is typically measured by suppression of the response to the repetition of a stimulus (Meyer and Rust, 2018; Miller et al. , 1991; Vogels, 2016; Xiang and Brown, 1998). As the time scale of repetition suppression lasts up to seconds, it may require the adaptation mechanisms on the much longer time scale (Sanchez-Vives et al. , 2000). Thus, adaptation on various time scales (et al. , 2006; Pozzorini et al. , 2013) may be required for different types of recognition memory. In our work, we assumed that inhibition minimally contributes to shaping response dynamics with learning for the following reasons. First, no dependence of input changes on post-synaptic firing rates in inhibitory neurons observed experimentally suggests that changes in inhibitory activities with learning can reflect the reduction of average excitatory activities and thereafter, excitatory inputs to inhibitory neurons without synaptic plasticity in the excitatory (E)-to-inhibitory (I) connections (Lim et al. , 2015). On the other hand, anti-Hebbian synaptic plasticity in the I-to-E connections can have similar effects as Hebbian-synaptic plasticity in the E-to-E connections. Alternatively, overall potentiation in the I-to-E connections can provide stronger negative feedback or can replace the role of feedforward synaptic plasticity. However, as the dynamics of inhibitory neurons show strong suppression almost to the baseline in the late phase of the stimulus presentation after learning (Figure 1—figure supplement 1), neither anti-Hebbian synaptic plasticity nor potentiation can account for an increase of maximal response of excitatory neurons in the early phase and overall reduction in activities in the late phase (Figure 1).

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: grabación acústica complementa a las cámaras trampa para monitorear a las poblaciones sensibles de pingüinos Frente a la perdida global de la biodiversidad que amenaza la sostenibilidad socio-ecológico, necesitamos mejorar nuestro conocimiento de los comportamientos, las historias de vida y las poblaciones de las especies del mundo. Mejorar nuestro entendimiento es especialmente crucial para las taxa como aves marinas que viven en hábitats remotos donde el monitoreo es logísticamente complicado. Métodos basados en le tecnología pueden facilitar avances mayores. En consideración de las amenazas de conservación y el comportamiento de reproducción, los pingüinos representan un taxón para que vale más exploración de los métodos de monitoreo. Sólo cinco de las 18 especies de pingüinos están consideradas como de ‘menor preocupación’ por la UICN, y la sensibilidad de los pingüinos a los disturbios ecológicos los hace importantes indicadores de la dinámica de los ecosistemas. Los pingüinos regularmente se congregan en densas colonias de nidificación y son tanto, visual como auditivamente, animales conspicuos, de esta manera es de algún modo relativamente sencillo monitorearlos.

Output: contrast


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: • It would have made a stronger paper if there was also proper field collection collected and studied by the authors, to better support the dataset information. However, the outcome of this work seems to have potential in the future. Additional comments The manuscript PDF is annotated for authors to see and check. The manuscript needs to be restructured essentially in the Introduction and discussion part to convey the scientific potential of this research. In this context, I am recommending the manuscript for a major revisions to incorporate the suggestions mentioned in the PDF version of the Manuscript, which is attached here before the acceptance. Annotated reviews are not available for download in order to protect the identity of reviewers who chose to remain anonymous. Cite this review as (2023) #3 of "Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (v0. 1)". PeerJ Submission (PDF) - submitted Feb 6, 2023 All text and materials provided via this peer-review history page are made available under a Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Thus, we assumed that changes in the inhibitory pathway are less likely to induce oscillation or suppression in the excitatory neurons. It is notable that the interaction between synaptic plasticity in both recurrent excitatory and inhibitory connections was suggested to reproduce increased transient response with learning (Moldakarimov et al. , 2006). Although the homeostatic inhibitory plasticity proposed in this work cannot reproduce damped oscillatory response observed in ITC, we cannot rule out the role of inhibitory synaptic plasticity that can be complementary to the mechanisms proposed in our work. The enhanced oscillation for familiar stimuli investigated here was around 5 Hz, which is in the range of theta oscillations. Such a low-frequency oscillation has been discussed in visual search to characterize overt exploration or sampling behaviors such as saccadic or microsaccadic eye movements (Otero-Millan et al. , 2008; Buzsaki, 2011) and to underlie covert shift of attention that samples different stimuli rhythmically (Dugué et al. , 2015; Fiebelkorn et al. , 2013; Landau and Fries, 2012). In line with these studies, Rollenhagen and Olson (2005) observed that low-frequency oscillation became stronger when another stimulus was present together. Competitive interactions between populations representing different stimuli were suggested to generate oscillation with fatigue mechanism (Moldakarimov et al. , 2005; Rollenhagen and Olson, 2005). Based on the adaptation mechanisms proposed in the current work, competition between two different familiar stimuli can generate stronger oscillation at a similar frequency. In the mean-field dynamics with two mutually inhibitory populations each of which mimics the maximum response to a single familiar stimulus, stronger oscillation but with the similar frequency with that for the single stimulus presentation was reproduced in the presentation of two stimuli (Figure 7). This may indicate low-frequency damped oscillators for a single familiar stimulus can be a building block for a rhythmic sampling of multiple stimuli and covert attentional shift through competitive interactions. Figure 7 Download asset Open asset Enhanced oscillation through competitive interactions between different stimuli. (A) Two mutually inhibitory populations selectively responding to stimuli 1 and 2, respectively. The dynamics of each population follows the dynamics of m in the mean-field description for a single familiar stimulus in Figures 3A,5.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: Las observaciones in situ y los métodos visuales de monitoreo remoto (por ejemplo, cámaras trampa, vehículos aéreos no tripulados, e imágenes satelitales) proveen de información increíblemente valiosa sobre el comportamiento de los pingüinos y sus dinámicas poblacionales, pero estos métodos tienen algunas falencias. Algunos de estos métodos requieren la presencia humana en áreas remotas, algunos requieren que no haya interferencias visuales ni obstrucciones, y algunos otros ofrecen una limitada resolución temporal y/o espacial. En este estudio exploramos el uso de un monitoreo acústico pasivo (MAP) como método de sensor remoto complementario para el monitoreo del comportamiento de pingüinos y poblacional con una alta resolución temporal y espacial sin restricciones visuales ni la necesidad de la presencia humana continua. Realizamos observaciones de tasas de vocalización y colocamos grabadoras automáticas en colonias de Spheniscus magellanicus y Eudyptes chrysocome en conjunto con cámaras trampa. Encontramos una relación positiva entre la actividad acústica y el conteo de Spheniscus magellanicus en las cámaras trampa. Identificamos también claros patrones diarios de actividad acústica los cuales difirieron entre estadios reproductivos, y a su vez encontramos una correlación positiva entre la actividad acústica y los estimadores de densidad de la colonia para varios momentos del día y radios alrededor de las grabadoras.

Output: contrast


Input: Claim: Phytoplankton produce a significant portion of Earth's oxygen. [SEP] Text: But lab work shows that in gas-phase chemistry, other factors produce isotope variation. It turns out that sulfate, which forms when sulfur is oxidized, is a very complicated molecule in gas-phase reactions. In particular, reaction products that include the 33S isotope are anomalously large compared with those that contain 34S or 32S. Such anomalies are called mass-independent fractionation. On Mars, UV light photolyzes sulfate and leads to fractionation. Laboratory experiments revealed that sulfur isotopes in Martian rocks show a mass-independent distribution. If there were no oxygen in Earth's atmosphere, UV light would get through as well, and similar anomalies would appear in the sulfur isotope record. “We know that sulfur in today's atmosphere gets oxidized by peroxide in ozone,” explains Thiemens. Farquhar did indeed see this isotope variation in 2. 45 billion-year-old Earth rocks. “We realized that this variation existed and the only mechanism we knew of that could produce it was related to gas-phase reactions,” he says. All that remained was to figure out the atmospheric conditions. “The sulfur allows you to see at most how much oxygen there was at the time,” says Thiemens. During the period prior to 2. 45 billion years ago, the photolytic effect can be seen. Then, when there was sufficient oxygen in the atmosphere, normal mass-dependent chemistry appears in the isotope record. Models suggested that this oxygen threshold is about 10 ppm. “We have been able to show fine-scale differences between the [sulfur isotopes] that show up. They fall into bins in different places in Earth's early record, and might give insight to what's happening in the atmosphere and oceans at any given times,” summarizes Farquhar. The sulfur isotope study provided one of the first continuous records that could be used to demonstrate a long-advocated change in oxygen levels. Other studies have used metals to study reactions that might be related to air oxidation states and redox reactions that occur in oceans and during weathering. Earlier or later? “There are polarized views in the geochemical and early Earth community about when oxygenic photosynthesis evolved,” says of the University of British Columbia. One camp insists that oxygen appeared in the atmosphere 2.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: (B) Time course of visual responses of two populations with different stimulus onsets (black and gray bars below). Stimulus 2 was present 500 ms after the onset of stimulus 1, and the population two was assumed to be silent before the arrival of stimulus 2. After the onset of stimulus 2, visual response selective to stimulus one was transiently suppressed and showed stronger oscillation compared to that under the single stimulus presentation. Overall, our work resonates with perspectives emphasizing the importance of dynamics in understanding cognitive functions (Bargmann and Marder, 2013; Kopell et al. , 2014). As an extension of our previous work that inferred the synaptic plasticity rules from changes in spatial patterns, additional analysis of response dynamics revealed the role of slow adaptation currents in shaping response dynamics. Different contributions to activity changes of recurrent and feedforward synaptic plasticity suggested in our work can be further utilized to examine how each synaptic plasticity engages during the progress of learning. Also, although we suggested a local circuit model for visual learning, interactions with other areas might also be important – for instance, the interactions between ITC and perirhinal cortex may form positive feedback given the adjacency of these two areas and similar familiarity effects observed experimentally (Xiang and Brown, 1998). On the other hand, prefrontal cortex showing opposite effects of familiarity with a long latency may provide slow negative feedback (Xiang and Brown, 2004). To dissect the interaction between multiple regions, one can analyze time course data investigating latencies and qualitative changes in dynamics in these areas such as the emergence of oscillatory response after learning. Materials and methods Mean-field dynamics Request a detailed protocol To derive the mean field dynamics from Equation (3), we assumed linear dynamics with Φ(x) = x and uniform recurrent connectivity before learning WijR=wR/N. Note that uniform connection can be replaced by random connection, which is analogous to the state where the network connectivity is stabilized after learning of a large number of uncorrelated activity patterns, but not correlated with the stimulus of interest (Lim et al. , 2015). We also assumed ∑ gk(ξj)=0 so that the sum of synaptic weights over the presynaptic neurons is preserved with learning. The external input to neuron i before learning is defined as IiX with WijF=δij.

Output: corroborate


Input: Claim: eDNA technology will soon replace all traditional wildlife monitoring methods, such as camera traps or field surveys. [SEP] Text: You can make a stronger statement than ‘interactions between predators and prey’ here. I suggest indicating presence of potential predators near the artificial prey and their identification, evidence for detections that resulted in no attack, and improved identification by potential predators that did attack the prey. But some of these advantages also occur with still cameras and thus are not unique to video. L35-36. Here, I think you can briefly indicate the general type of prey (coral snakes and mimics, including scientific names of genera), habitat types, and locations (name of park and country only) which would add important details of your study and not add many more words. L35. Clarify that during three experiments on aposematism and mimicry you used video camera traps near some of the artificial prey to examine how much additional information videos would provide. The word ‘site’ could refer to study site (e. g. , a reserve in Ecuador), so you need less ambiguous terminology. L36-39. If you follow advice from me and the reviewer regarding statistical analysis and clarification of the research questions, the Abstract will become more specific here. L39-40. The reviewer is correct that ‘studies of predation’ is too broad. Try to come up with a more focused statement on your contribution to studies of artificial prey. Introduction L53. The explanation on L60-65 goes more logically here before the variety of research questions and taxa. L69. Not clear how a footprint is a disturbance. Do you mean actual marks on a clay model from it being stepped on? Is that very likely? L73. Since your approach allows specific identification of potential predators, shouldn’t you emphasize that marks on clay do not typically allow species identification but only broader groups of potential predators? L94-101. This section synthesizing previous work needs to be strengthened. Although you refer to the existence of several previous studies, you cite only one. It would be appropriate to cite the major recent studies and perhaps the first one. Furthermore, by saying that most used still images, the reader is lead to believe that there exist previous but uncited studies using videography. Such studies should be cited. Then, you should develop the knowledge gap to be filled by your study. Is this the first systematic attempt to quantify the benefits of videography or a repetition of previous studies in different habitats or artificial prey types or with a larger sample size?

Output: contrast


Input: Claim: Phytoplankton produce a significant portion of Earth's oxygen. [SEP] Text: 3 billion-years-ago event, but the big question is whether the late neoproterozoic rise 600 million years ago was necessary before the appearance of animals,” says geobiologist of Caltech. Fossils of sponges—the simplest animals, and indeed ones whose physiology has remained the same throughout history—exist from 635 million years ago, suggesting that the first animals did start to appear before the second major oxygen rise. Daniel Mills, also of Caltech, Ward, and colleagues created a small aquarium in which they could vary, measure, and control oxygen levels, and observe the survival of sponges and their respiration rates at different concentrations. They determined that modern sponges can survive for reasonably long timescales at 0. 5 to 4% of current oxygen levels. oxygen levels are not tightly constrained, general consensus is that most of the proterozoic had 1–10% of modern oxygen levels. That's enough to support sponge-grade animals. One of the Halichondria panicea sea sponges that and his collaborators used to investigate the likely oxygen demands of early animals. : D. Mills“We now think that oxygen was extremely low in the period before the appearance of sponges,” agrees of the University of California, Riverside. But metabolically active animals, which demand energy and oxygen to diversify and grow in size, appeared later. “Oxygen levels could have been high enough to allow metozoans to thrive, but evolution could have triggered the rise in oxygen,” adds Planovsky. The chicken-or-egg question thus prevails. One curious anomaly is the Lomagundi carbon isotope excursion at around 2 billion years ago. Oxygen from photosynthesis can combine with organic matter, and carbon isotopes get heavy when organic matter is buried. Thus a record of heavy carbon isotopes indicates a net gain of oxygen in the atmosphere. “That [excursion] followed a very dramatic fall [in oxygen levels]. It's a fascinating time,” adds Lyons. “What's interesting, as we construct more records from the time period, is that oxygen may have actually risen to significant levels during this time interval. This supports intervals of significant rise, then fall, in oxygen,” adds Planovsky.

Output: pass


Input: Claim: Memory formation involves the strengthening of neural connections, a process known as synaptic plasticity. [SEP] Text: Now based on the second assumption during the rising phase of the second stimulus presentation, the input becomes I0−a1k and the expression for the second peak becomes (I0−a1k)t0τR/(1−wR)+r1. Then the condition that the second peak is lower than the first peak gives (I0−a1k)t0τR/(1−wR)+r1<r0. Replacing I0 using r0=I0t0/τeff leads to the condition r1/r0⋅τR/t01−exp(−t1/τA)−(1−r1/r0)(τA/t0(exp(−t1/τA)−1)+1)<(1−wR)k (dotted curve in Figure 5—figure supplement 1). Network simulation in Figure 4 Request a detailed protocol 4, we illustrated the dynamics of an example network with synaptic plasticity in feedforward and recurrent connections, and spike adaptation mechanisms. The network dynamics follows Equation (3) and as in the mean-field dynamics, we assumed linear dynamics with Φ(x) = x and uniform recurrent connectivity before learning WijR=wR/N. The input was modeled as a sum of a constant input Iconst and time-varying one which is the sum of two exponential functions Idyn=exp(−t/t1)−exp(−t/t2) with its strength ξi varying across neurons as IiX=Iconst+ξiIdyn. For recurrent synaptic plasticity, Hebbian learning rule such as ΔWijR=αNvar(ξ)ξi(ξj−ξ¯) was considered where α is the strength of the plasticity. For feedforward synaptic plasticity, uniform scaling down of the time-varying input was considered such that IiX changes to IiX=Iconst+γξiIdyn after learning. For the successive presentation of two stimuli, the changes in the recurrent connection become WijR→WijR+ΔWijR,1+ΔWijR,2 with uncorrelated patterns ξi1 and ξi2.

Output: corroborate