Aurélie Coulon

Maxime Dahirel

Andrea Griffin

Can context changes improve behavioral flexibility? Towards a better understanding of species adaptability to environmental changes

Behavioral flexibility is a key for species adaptation to new environments. Predicting species responses to new contexts hence requires knowledge on the amount to and conditions in which behavior can be flexible. This is what Logan and collaborators propose to assess in a series of experiments on the great-tailed

grackles, in a context of rapid range expansion. This pre-registration is integrated into this large research project and concerns more specifically the manipulability of the cognitive aspects of behavioral flexibility. Logan and collaborators will use reversal learning tests to test whether (i) behavioral flexibility is manipulatable, (ii) manipulating flexibility improves flexibility and problem solving in a new context, (iii) flexibility is repeatable within individuals, (iv) individuals are faster at problem solving as they progress through serial reversals. The pre-registration carefully details the hypotheses, their associated predictions and alternatives, and the plan of statistical analyses, including power tests. The ambitious program presented in this pre-registration has the potential to provide important pieces to better understand the mechanisms of species adaptability to new environments.

Revision round #1

2018-09-13

Dear authors, I have now received two reviews of your pre-registration. It took longer time than we wished to get reviews, because of the (summer) timing and also because of the novelty of the pre-registration process. I apologize about this. Both reviewers have interesting comments and suggestions about your hypotheses/predictions and protocol. I suggest revising your pre-registration accordingly, alongside writing a detailed response to each reviewer's comment. Reviewed by Andrea Griffin, 2018-09-13 06:03

The overall aim of this project is stated to be to "determine how behavioural flexibility works and how we can make predictions about a species' ability to adapt their behavior to new environments". Its aims are "to manipulate grackle behavioral flexibility … to determine whether their flexibility is generalizable across contexts, whether it is repeatable within individuals and across contexts, and what learning strategies they employ. Although I find these specific questions divorced from the background of invasive spread, and hence, do not particularly buy into the advantage of using an invasive species undergoing a current range expansion (in fact, I explain below how I find some predictions inherently contradictory with this background), the questions are worthwhile asking. Detailed comments are as follows: Please clarify: "they generally get faster rather than getting faster with each reversal" and how the learning criterion was altered to accommodate this P1: Although I find it interesting to compare the extent to which rule-learning generalizes across contexts as a function of experience with rule learning, the question seems to contradict the notion that behavioural flexibility (measured here as rule learning) can be a target of selection during a range expansion, meaning that individuals would need to differ in some inherent way in their capacity to rule learn. Hence, for behavioural flexibility to be a target of selection, behavioural flexibility should not be flexible, if that makes sense. Put differently, invasive birds should not become broader-context rule-learners as a consequence of experience with rule learning. In fact, learning this capacity would be predicted to delay selection on the trait. Hence, H3a seems the more logical prediction and test, given the larger context of the project.

P1 alternative: "If the number of trials to reverse a preference does not correlate with or positively correlates with reversal number"; this contradicts the general pattern of finding of an SDR (number of trials to criterion decreases with increased reversal number) and also the authors' own statement under P1: "Individuals improve their flexibility on a serial reversal learning task using colored tubes by generally requiring fewer trials to reverse a preference as the number of reversals increases". Is this a typo?

Methods:

Learning criterion: is the sequence re-started at each testing session? Ie what is planned if a bird is willing to do 10 choices on one day and then satiates. Is the trial number started again at each testing session? Or do the, for example, correct trials yesterday count towards today's? ie does the sliding window for scoring carry across testing sessions?

IVs: What is 'batch'? test cohort? How many birds are tested simultaneously?

"we should expect due to the lack of data on this species for these experiments": ok, but there are several published comparative data sets on SDR that you could use (e.g. Tebbich et al.).

"Analysis": N=32: does that mean 16 experimental and 16 controls?

In measuring the latencies to switch to new options on the multi-access box: how can 'work-time' be disentangled from 'non-work time' in a latency? I.e. a bird that tries lots of options and interacts with the box might have the same latency as a bird that does mostly other things but then tries once and by chance solves the box immediately. How can these two seemingly very different birds be differentiated in a latency? I guess this is equivalent to asking whether multiaccess box testing yields any motivation variables, similar to number of beak-totask contacts one can obtain from an innovative problem-solving task. I would predict that motivation variables, which end up providing some measure of persistence, will be associated with exploitation vs. exploration strategies. I could not find an answer to this question in the protocol.

"Learning strategies": The authors might find the following research and analysis strategy useful as it disentangles exploration from exploitation phases within each reversal. Federspiel, I. G., Garland, A., Guez, D., Bugnyar, T., Healy, S. D., Güntürkün, O., & Griffin, A. S. (2017). Adjusting foraging strategies: a comparison of rural and urban common mynas (Acridotheres tristis). Animal Cognition, 20, 65-74. Protocol_flexibility: Why will birds only undergo 5 reversals on the touch screen? Is this enough to establish a significant slope in learning speed that can be compared across tasks? I am also confused by not testing the control group. Was the suggestion not to train birds on the tube task (experimental and control) and then to compare the transfer of both these groups to each of the two additional tasks (multi-access and touch screen)? Why would the controls not participate in the reversals?

Reviewed by Andrea S. Griffin Author's reply: Download author's reply (PDF file)

I

  look forward to receiving a revised version of your pre-registration. Yours sincerely, Aurélie Coulon. Preprint DOI: 10.5281/zenodo.1303263 Reviewed by Maxime Dahirel, 2018-07-29 13:56 Download the review (PDF file)


Philippe Jacquet
email: philippe.jacquet@inria.fr

The Ariadne String against Covid-19 pandemic propagation part 2: oudoor path selection after lock-downs

 we have presented the Ariadne String against Covid application, whose aim was to recommend safe outdoor path inside cities in order to limit the exposure to virus propagation during aimless outdoor leisure excursion. The main idea was to make a load balancing between streets via spacetime diversity via a random walk. The application was shown to be efficient at the very first user. The present work is an extension of this previous work and can be applied after lockdown where outdoor excursions have a aim. We use drifted random walks which under the condition of uniform distribution of initial starting points and destination locations gives a perfect load balancing of the streets, thus minimizing the exposure to virus (by a factor around 3).

I. INTRODUCTION

The Covid-19 pandemie has forced more than half of mankind into lock-down situation. During lock-down and in some countries, outdoor excursion were authorized under strict restriction; in France, no more than 1 hour less than 1km from home. These restrictions had aim to reduce the exposure rate to virus through outdoor contact with other persons. This problem is of course crucial in urban places, since in country places the distanciation are more easy to achieve. In [START_REF] Jacquet | The Ariadne String against Covid-19 pandemic propagation during lock-downs[END_REF] we have described an application, called Ariadne String against Covid, which reducte the contact rate thanks to a better load balancing the streets while avoiding crowded areas. The fundamental tool in Ariadne Covid is the use of random walk which naturally load balance edges in a graph. The application is shown to give a benefit to the first user, although to have an impact on the pandemie, it must be used by a majority of users. The average outdoor exposure rate reduction is around 3, but it is difficult to verify this claim since it is based on pre lock-down partial data on some cities.

In the present work we present Ariadne Covid2 as a followup application whose aim is to limit outdoor exposure to virus after lock-downs. The lock-downs aim is to "flatten the curve" in order to limit the congestion in hospitals. It is equivalent to the graphite bars used to slow down and reverse the reactions in the kernel of a nuclear plant. If you remove the graphite bars, the reaction will restart. Therefore the social distancing and other ways to limit exposure will need to be continued after lock-down before either a vaccine or a herd-immunity is developed. Indeed the situation is even more dangerous than before lock-down, since the infected population ratio is larger. In particular there would need be some care on our outdoor excursion.

But contrary to lock-down outdoor excursions which were set-up for healthy consideration and therefore were aimless (walking, jogging), the outdoor excursions after lock-down will have a aim, most likely in order to commute between home and work place. The public transportation is considered to be unsafe since people will packed in small areas, and it should be restricted in order to achieve a sufficient social distances. The city of Paris envisions to help people to rely on biking and other surface transportation by increasing the number of streets with biking lanes. However the biking lanes are narrow and sometimes very busy because people commute around the same hours. Our work is to introduce a policy which helps the user to find a biking route from home to work which limit the exposure rate by achieving a load balancing between lanes.

In this condition a simple random walk cannot work since it will take an eternity for a random walk to connect the home address with the work place, if the latter is a random but fixed location in the city. The shortest path will not be good, since it is likely to take the main streets and create a gathering on those streets. Our approach will be based on drifted random walks so that the penality with the shortest path will be limited, while the aggregation of path from all users will give an optimal load balancing over the streets and therefore minimize the exposure rate.

II. DESCRIPTION OF THE ALGORITHM

The user sends its GPS coordinate z 0 = (x 0 , y 0 ) of its home address or initial position. She/he also sends the coordinate of the final destination z f = (x f , y f ).

The algorithm operates on an abstract data set which is a set of street intersection linked by segment of a street. The intersection I is given by its GPS coordinates (x(I), y(I)). Two intersections I and J are connected if there exist a segment of street which connect the two intersections. Let V the set of intersections and E the set of street segments, The pair (V, E) forms a graph. We also have the set S of streets, A street is a set of contiguous street segments.

The neighbors of an intersection I are the list of the intersections to which I is connected. We use a number > 0 fixed for the protocol.

The initial position of the user is on a segment (I U , I D ) ∈ E. The path will take the intersection among I U and I D which lies ahead of destination, i.e if z f -z 0 |I U -I D ≥ 0 then I U is selected:

z 1 = I U , otherwise z 1 = I D .
At step number k, let z k be the intersection were the path is currently ending. Let d be the degree of the intersection z k . If d = 1, then the path backtracks. If d > 1 then with probability the path proceeds with the non backtracking random walk, i.e. the path take any other neighbor edge distinct of (z k-1 , z k ) with equal probability. Otherwise, with probability 1 -, the path take one the two the best sectored edge as defined as follow. Assuming the angle of the edge (z k , z k-1 ) is θ 0 , and we enumerate θ 1 , θ 2 , . . . θ d-1 the angle in increasing order of the other edges of intersection z k . Let θ be the angle of the vector (z k , z f ) toward the destination.

Let j such that j 2π d < θ ≤ (j + 1) 2π d . Of course j + 1 must be considered modulo d. Let α d (θ) and β d (θ) such that α + β = 1 and αe 2ijπ/d + βe 2i(j+1)π/d be proportional to e iθ . Numerically we have

α d (θ) = sin(2(j+1)π/d-θ) sin(θ-2jπ/d)+sin(2(j+1)π/d-θ) β d (θ) = sin(θ-2jπ/d) sin(θ-2jπ/d)+sin(2(j+1)π/d-θ) . (1)
The selection of the next step z k+1 is done as follow: with probability α it selects the edge corresponding to angle θ j , and with probability β the edge corresponding to the angle θ j+1 .

We notice that there is no reason that the selected edge actually heads toward the destination (in fact it will never do), but in average it will do, under mild conditions on the actual street angles distribution in the city.

Notice that when θ 0 is the actual angle selected by the path algorithm selection, then the path backtracks. In this case the loop removal should be applied to the actual path, this will even more reduce the actual weight of the path.

The algorithm is much simpler than the actual Dijskstra shortest path algorithm, indeed the shortest algorithm leads to at least an average quadratic complexity in terms of the number of vertices, while the randomized algorithm is at most linear, in fact proportional to the diameter of the graph. This will greatly help the computational power required to have a server capable of serving several millions of requests. However we shall not expect the algorithm to provide a shortest path, but we expect that the randomized algorithm will provide a reasonable penalty for having non optimal path.

We can show that under the isotropic walk condition the algorithm leads to a uniform distribution.

Definition 1 (Isotropic walk condition).

A walk is isotropic at a given intersection I, when reaching intersection I, the difference of the angle θ toward the destination with the angle θ 0 of the arriving edge, satisfies a fixed distribution P I (θ-θ 0 ).

Notice that the walk arriving at a destination has randomness assuming the randomness of the initial and destination co-ordinates. Notice that the isotropic condition does not implies that θ -θ 0 must always be close to π (most direct path) and when θ -θ 0 is small the path will most likely backtrack.

Theorem II.1. Under the isotropic walk condition, and assuming same constant speed v of the travellers, the aggregation of path leads to a uniform densities on the streets.

Proof. We use the classic proof of stationary random walks in undirected graphs. Let assume that at time t every street in city has the same exit rate ρ(t) on each of its end points. We will prove that all streets have the same entrance rate. And consequently the same exit rate on the other end. Thus the uniform distribution is the stationary distribution of the entrance rates.

In the following we assume that there is no loss between entrance and exit rates, assuming for example that path initial points and destination points exactly balance in each streets. Or equivalently that an arrival point coincides with a departure point like in a random way point mobility model.

Let consider a traveller arriving at an intersection I which has d arriving streets. According to the uniformization hypothesis, the traveller has an equal probability to arrive on any of the d intersecting edges. With probability it selects any of the d-1 other streets. With probability 1it select one of the best sectored edge. Enumerating the edges in counter clockwise way, initialising with the entrance edge, the isotropic walk conditions leads to the following expression of the probability p d (j) that the edge j is selected is

p d (j) = 2(j+1)π/d 2jπ/d P (θ)α d (θ)+ 2jπ/d 2(j-1)π/d P (θ)β d (θ). (2)
Therefore the probability that a edge is selected, independently of the entrance edge is

d -1 d + (1 -) j=d j=0 p d (j). (3)
Thus the exit rates are uniform, and have value ρ(t) and consequently the stationary rate distribution is uniform with some value ρ. Since the speed is considered to be the same on each street the density of traveller on each street is ρ/v per unit length.

As an intermediate step, there is the randomized geo-routing algorithm which is very close to the isotropic walk with the difference that instead of assuming equal angular sectors j 2π d for the exit streets at each intersection, we take the actual angle of the streets. The consequence is that (i) the average exit path is now well aligned with the angle toward the destination, but (ii) we lose the isotropic property, since the densities on the exit street will now vary with the variation of the angles between the streets (which are null in the grid model but tend to be large in the Delaunay model as we will see in the next sections).

Arriving street

Angle toward destination

𝛼 𝛽

Average exit heading

III. SIMULATION OF THE ALGORITHM

A. Simulation on a grid

We have chosen an abstraction of Paris map via a 100x100 map. Each grid point is an intersection in Paris. Each segment represents a street segment of one unit length. From North to South the streets represents 100 length units, and the total cumulative street length length is 20,000 length units. This compares well with the actual diameter of Paris (8km) and its cumulative street length of 1500 km (thus 2900 km of street sides).

The mayor of Paris have decided to create bike lanes parallel to the 14 subway lines, in order to foster the use of bikes instead of public transportation after lock-down. To simulate those bike lanes we have highlighted 14 paths (seven paths West-East, seven paths North South) on the grid map.

We have run N 0 = 8, 000 sources and destination pair on the two algorithms. One algorithm is the randomized algorithm, the second algorithm is the preferential path algorithm. In order to simulate the attraction effect of the highlighted path, we have artificially distorted the graph by decreasing the segment path weight by 20% and run a shortest path Dijskstra algorithm. This a moderate ratio but it is sufficient to create a significant attraction effect, otherwise the difference would be not visible due to the large diversity of shortest paths in a grid structure. We simulate the isotropic randomized algorithm with = 0.

Figure 3 and4 show the histogram of the segment density loads consequence of the application of the algorithms. For each segment, we collect the traffic for both ways, but for the figures we add the two traffic per segment to display the histogram. We notice that the preferential path algorithm shows that the preferential streets are drastically more busy than the other streets. The randomized algorithm shows a more balanced distribution of traffics. There are not perfectly uniform since the isotropic condition fails on the borders of the map and holds in the large central part of the map. Figure 5 shows the map of the traffic of street segments with the preferential path algorithm. In green are the streets with load larger than 1 but smaller than 15, in blue, traffic smaller than 25, in red, smaller than 50, in black, smaller than 200. The preferential paths are clearly visible and marked as very busy (black and red) as expected. The figure 6 shows the map of empty streets (lined in grey) which is a dense network. Figure 7 and figure 8 show the same data for the randomized algorithm, but the picture are now different, since the segment load are very balanced and the empty street seldom. Now our aim is to derive the average exposure time of the travellers in Grid Paris. As in [START_REF] Jacquet | The Ariadne String against Covid-19 pandemic propagation during lock-downs[END_REF] we denote by S the set of street segment, with the difference, that the segment are directed and we differentiate a segment with its reverse segment. We denote (s) the segment length, thus the cumulative length is L = s∈S (s). We denote λ(s) the traffic load after N 0 initial-destination random pairs. The average path length is

L G = 1 N0 s∈S λ(s) (s). The average travel time is L G /v.
If the simulated time is T , on segment s the entrance frequency rate is λ(s) T and the density on the segment is λ(s) vT , assumed to be Poisson. If the number of traveller is N then the density on the segment is λ(s) vT N N0 where N 0 is the number of travellers needed to simulate the estimate λ(s). Given this Poisson density, the probability that a random point at a random time on the segment does not have a traveller at distance within R 0 is exp -λ(s) 2R0 vT N N0 . If R 0 is the safe distance against virus, for biking R 0 = 10m, for a random traveller the average cumulative exposure time E(N ) is

E(N ) = s∈S λ(s) (s) vN 0 1 -exp -λ(s) 2R 0 vT N N 0 . (4)
If we want to know the exposure time E 12 (N ) for a single traveller of the randomized algorithm when all other travellers use the preferential paths, we get the expression

E 12 (N ) = s∈S λ 2 (s) (s) vN 0 1 -exp -λ 1 (s) 2R 0 vT N N 0
(5) where λ 1 (s) is the density of segment s for the preferential algorithm, and λ 2 (s) is for the randomized algorithm.

The figures 9 and 10 show the average cumulative exposure time versus the travelling population, when all travellers are on preferential path, when all travellers are on the isotropic randomized algorithm, and the average cumulative exposure time when a single traveller is on randomized algorithm, and the other are on preferential paths. We display for a peak traffic period duration of 2 hours, and for a peak duration of 4 hours. For one day these quantities should be multiplied by two, since the travellers commute twice a day. For the traveller speed we have opted for v = 12km per hour, which is the average speed of bike commuting in Paris.

B. Simulation on a Voronoi triangulation

We have created a map of 4,000 random points on a 10kmx10km square and connected them through the Delaunay triangulation. In this simulation the streets are the edges of the triangulation and the nodes are the intersections. With 4,000 nodes we get a total street length of the order of 200 times the diameter of the map, thus showing a similar street density than Paris street map. As in the previous simulation we have connected 14 pairs of points, 7 North-South, seven West-East to simulate the subway network. The bike lane supposed to follow the subway lines is made of the path obtained via shortest path algorithm between the points of each pair.

We have simulated four algorithm:

1) The preferential path algorithm; 2) the shortest path algorithm; 3) the isotropic walk algorithm; 4) the geo-routing algorithm The three last algorithms perform the same in a grid network, this is why we did not distinguish them in the previous section. The isotropic walk algorithm is the algorithm described in the paper. Notice that the shortest path algorithm is the most expensive of all three since its quadratic in the number of nodes and therefore maybe expensive in term of server complexity.

In the preferential path algorithm we still use the shortest path algorithm but now we reduce the weight of the edges in the preferred path by 90%. This is kind of a drastic reduction but it simulates well the use of subway where the commuter takes the path to the closest subway station and enlights on the subway station closest to his/her destination location.

We have run N 0 = 5, 000 pairs of initial point and destination. Figure 11 and 12 show the histogram of the segment density loads consequence of the application of the algorithms. In red the preferential algorithm, in brown the isotropic walk algorithm, in blue the geo-routing algorithm, in green the shortest path algorithm. As expected the isotropic walk algorithm shows the best balance (better look at the logarithmic scale). Figure 13 shows the map of the traffic of street segments with the preferential path algorithm. In green are the streets with load larger than 1 but smaller than 15, in blue, traffic smaller than 25, in red, smaller than 50, in black, smaller than 200. The preferential paths are clearly visible and marked as very busy (black and red) as expected. The figure 14 shows the map of empty streets (lined in grey) which forms a dense Figure 12: Histogram of segment densities in Delaunay Paris, in logarithmic scale network. Figure 15 and figure 16 show the same data for the shortest path algorithm, but the picture are now different, since the segment load are better balanced and the empty street much less dense. Figure 17 and figure 18 show the same data for the isotropic walk path algorithm, since the segment load are very well balanced and the empty street very seldom. As expected the empty streets are on the border and the density balance more in the central part. Figure 19 and figure 21 show the same data for the geo-routing path algorithm, since the segment load are a little less well balanced and the empty street less seldom. Figure 28 shows the cumulative exposure time experienced by the travellers in the different routing algorithms during a peak of 2 hours versus the commuting population size. The shortest path algorithm provides the smallest exposure because the average path length is shorter despite the path density is larger. Indeed the exposure rate discrepancy diminishes when the commuting population diminishes. But the shortest path algorithm is too expensive in terms of complexity to answer to millions of request. The georouting and isotropic walk algorithms show similar performance. Although the isotropic algorithm benefits from its more balanced street loads at lower traffic. Figure 29 shows the respective average path length for each of the algorithms.

Since the preferential algorithm shows terrible performance, we investigate the possibility to multiply the parallel lanes to the preferential path in order to reduce the exposure time via a reduced density. The figure 23 shows the average exposure time versus the multiplicative factor of the parallel lanes. It turns out that the preferential lanes must be multiplied by at least ten in order to get closer to the performance of the isotropic algorithm.

C. Single pair simulation

In this section we evaluate the performance of the algorithms when we consider a single pair of initial point and destination point. We have simulated 1,000 travellers commuting between these two points. Of course the preferential path and shortest path algorithm are blocked on a single path because there a unique solution to the Dijkstra algorithm. But for the geo-routing algorithm and the isotropic walk algorithms have a random component and provide a diversity in the path. That way the two later algorithms offer a lower exposure thanks to the path diversity. The figures 24, 25 26,and 27, shows the traffic of the segment for the four algorithms. yellow is for a traffic between 1 and 15 passage, green between 15 and 25, blue between 25 and 50, red between 50 and 200, black above 200. We notice that the path network of the geo-routing algorithm is more vascular and therefore uses less segments. Figure 28 shows the cumulative exposure time of the four algorithm under this situation.

Figure 29 shows the average path length for the various algorithms under the condition of travel between a single pair.

D. Single destination point or single initial point simulation

In this section we evaluate the performance of the algorithms when we consider a single destination or a single initial point. We have simulated 4,000 travellers commuting from or toward this point. Of course the preferential path and shortest path algorithm show the same paths because there a unique solution to the Dijkstra algorithm and the solution is symmetric on both ways. But for the geo-routing algorithm and the isotropic walk algorithms have a random component and are asymmetric with respect to the order in the pair made by the initial point and the destination point. The figures 30, 31, 32,and 34, shows the traffic on street segments for the four algorithms when diverging from the same initial point, and figures 33,and 35, shows the traffic on street segments for the two last algorithms when converging on the same destination point. Figure 37 shows the cumulative exposure time of the four algorithm under this situation.

Figure 36 shows the average path length for the various algorithms under the condition of travel diverging from a fixed initial point.

Figure 1 :Figure 2 :

 12 Figure 1: Illustration of the functioning of the randomized georouting algorithm. The traveller enters the intersection via the large blue arrow.

Figure 3 :

 3 Figure 3: Histogram of segment traffic load in Grid Paris, in red the preferential path algorithm, in blue the randomized algorithm

Figure 5 :

 5 Figure 5: Map of segment densities in Grid Paris for the preferential path algorithm.

Figure 6 :

 6 Figure 6: Map of empty streets in Grid Paris for the preferential path algorithm.

Figure 7 :

 7 Figure 7: Map of segment densities in Grid Paris for the randomized algorithm.

Figure 8 :

 8 Figure 8: Map of empty streets in Grid Paris for the randomized algorithm.

Figure 9 :

 9 Figure 9: Simulated average cumulative exposure time in Grid Paris during a peak time of 2 hours versus total number of travellers: red: all traveller on preferential paths, blue: all travellers on randomized algorithm, dashed: one traveller on randomized algorithm.

Figure 10 :

 10 Figure 10: Simulated average Cumulative time in Grid Paris during a peak time of 4 hours versus total number of travellers: red: all traveller on preferential path, blue: all travellers on randomized algorithm, dashed: one traveller on randomized algorithm.

Figure 11 :

 11 Figure 11: Histogram of segment traffic load in Delaunay Paris, in red the preferential path algorithm, in blue the randomized algorithm

Figure 13 :

 13 Figure 13: Map of segment densities in Delaunay Paris for the preferential path algorithm.

Figure 14 :

 14 Figure 14: Map of empty streets in Delaunay Paris for the preferential path algorithm.

Figure 15 :

 15 Figure 15: Map of segment densities in Delaunay Paris for the shortest path algorithm.

Figure 16 :

 16 Figure 16: Map of empty streets in Delaunay Paris for the shortest path algorithm.

Figure 17 :

 17 Figure 17: Map of segment densities in Delaunay Paris for the isotropic walk path algorithm.

Figure 18 :

 18 Figure 18: Map of empty streets in Delaunay Paris for the isotropic walk path algorithm.

Figure 19 :

 19 Figure 19: Map of segment densities in Delaunay Paris for the geo-routing path algorithm.

Figure 20 :

 20 Figure 20: Average path length for the four algorithms, in km, from top to bottom: preferential algorithm, shortest path algorithm, isotropic walk algorithm, georouting algorithm.

Figure 21 :

 21 Figure 21: Map of empty streets in Delaunay Paris for the geo-routing path algorithm.

Figure 22 :

 22 Figure 22: Simulated average cumulative exposure time in Delaunay Paris during a peak time of 2 hours versus total number of travellers: red: all traveller on preferential paths, green: all travellers on shortest path, brown the isotropic walk algorithm, blue the geo-routing algorithm.

Figure 23 :

 23 Figure 23: Simulated average cumulative exposure time in preferential path algorithm. From top to bottom: one lane, two parallel lanes, three parallel lanes, five parallel lanes, 10 parallel lanes.

Figure 24 :

 24 Figure 24: Map of segment densities in Delaunay Paris for the preferential path algorithm on a single pair.

Figure 25 :

 25 Figure 25: Map of segment densities in Delaunay Paris for the shortest path algorithm on a single pair.

Figure 26 :

 26 Figure 26: Map of segment densities in Delaunay Paris for the geo-routing path algorithm on a single pair.

Figure 27 :

 27 Figure 27: Map of segment densities in Delaunay Paris for the isotropic walk path algorithm on a single pair.

Figure 28 :

 28 Figure 28: Simulated average cumulative exposure time in Delaunay Paris during a peak time of 2 hours versus total number of travellers on a single pair initial point and destination: red: all traveller on preferential paths, green: all travellers on shortest path, brown the isotropic walk algorithm, blue the geo-routing algorithm.

Figure 29 :

 29 Figure29: Average path length for a single pair: red: all traveller on preferential paths, green: all travellers on shortest path, brown the isotropic walk algorithm, blue the geo-routing algorithm.

Figure 30 :

 30 Figure 30: Map of segment densities in Delaunay Paris for the preferential path algorithm diverging on a single initial point.

Figure 31 :

 31 Figure 31: Map of segment densities in Delaunay Paris for the preferential path algorithm diverging on a single initial point.

Figure 32 :

 32 Figure 32: Map of segment densities in Delaunay Paris for the geo-routing path algorithm diverging from a single initial point.

Figure 33 :

 33 Figure 33: Map of segment densities in Delaunay Paris for the geo-routing path algorithm converging on a single destination point.

Figure 34 :

 34 Figure 34: Map of segment densities in Delaunay Paris for the isotropic walk path algorithm diverging from a single initial point.

Figure 35 :

 35 Figure 35: Map of segment densities in Delaunay Paris for the isotropic walk path algorithm converging on a single destination point.

Figure 36 :

 36 Figure36: Average path length for a single initial point: red: all traveller on preferential paths, green: all travellers on shortest path, brown the isotropic walk algorithm, blue the geo-routing algorithm.

Figure 37 :

 37 Figure 37: Simulated average cumulative exposure time in Delaunay Paris during a peak time of 2 hours versus total number of travellers on a single initial point: red: all traveller on preferential paths, green: all travellers on shortest path, brown the isotropic walk algorithm, blue the geo-routing algorithm.


Staffan Jacob

Mar Sobral Samuel Pichon

Transcriptomics of thermal stress response in corals

Climate change presents a challenge to many life forms and the resulting loss of biodiversity will critically depend on the ability of organisms to timely respond to a changing environment. Shifts in ecological parameters have repeatedly been attributed to global warming, with the effectiveness of these responses varying among species [1, 2]. Organisms do not only have to face a global increase in mean temperatures, but a complex interplay with another crucial but largely understudied aspect of climate change: thermal fluctuations. Understanding the mechanisms underlying adaptation to thermal fluctuations is thus a timely and critical

challenge. Coral reefs are among the most threaten ecosystems in the context of current global changes [START_REF] Bellwood | Confronting the coral reef crisis[END_REF]. Brener-Raffalli and colleagues [START_REF] Brener-Raffalli | Gene expression plasticity and frontloading promote thermotolerance in Pocillopora corals[END_REF] provided a very complete study digging into the physiological, symbiont-based and transcriptomic mechanisms underlying response of corals to temperature changes. They used an experimental approach, following the heat stress response of coral colonies from different species of the genus Pocillopora. While the symbiont community composition did not significantly change facing exposure to warmer temperatures, the authors provided evidence for transcriptomic changes especially linked to stress response genes that may underlie plastic responses to heat stress. The authors furthermore investigated the thermal stress response of corals originating from two sites differing in their natural thermal regimes, and found that they differ in the extent and nature of plastic response, including the expression of gene regulation factors and the basal expression level of some genes. These two sites also differ in a variety of aspects, including the focal coral species, which precludes from concluding about the role of thermal regime adaptation into the differences observed. However, these results still highlight a very interesting and important direction deserving further investigation [5], and point out the importance of variability in thermal stress response among localities [6] that might potentially mediate global warming consequences on coral reefs. Revision round #2

2019-05-17

Dear Eve Toulza, following the submissions of your revisions, the two reviewers and myself agree to acknowledge helpful clarifications of several aspects of your manuscript. The reviewers still pointed out a number issues that should be dealt with, especially regarding the introduced concepts on the link between plasticity and adaptation and the way analyses were performed. I thus invite you to carefully use the reviewers' comments to revise your manuscript.

All the best, Staffan.

Additional requirements of the managing board:

As indicated in the 'How does it work?' section and in the code of conduct, please make sure that: -Data are available to readers, either in the text or through an open data repository such as Zenodo (free), Dryad (to pay) or some other institutional repository. Data must be reusable, thus metadata or accompanying text must carefully describe the data.

-Details on quantitative analyses (e.g., data treatment and statistical scripts in R, bioinformatic pipeline scripts, etc.) and details concerning simulations (scripts, codes) are available to readers in the text, as appendices, or through an open data repository, such as Zenodo, Dryad or some other institutional repository. The scripts or codes must be carefully described so that they can be reused. -Details on experimental procedures are available to readers in the text or as appendices.

-Authors have no financial conflict of interest relating to the article. The article must contain a "Conflict of interest disclosure" paragraph before the reference section containing this sentence: "The authors of this preprint declare that they have no financial conflict of interest with the content of this article." If appropriate, this disclosure may be completed by a sentence indicating that some of the authors are PCI recommenders: "XXX is one of the PCI XXX recommenders."

Preprint DOI: https://doi.org/10.1101/398602

Reviewed by Samuel Pichon, 2019-05-13 11:35

First, I am grateful to Kelly Brener-Raffalli and colleagues who submitted a revised version carefully considering all comments made by Dr. Jacob and the reviewers. They largely contributed to the clarification of the experimental design, reworked at the scales of species and primarily of genotypes for both corals and symbionts, refined the scope and importance of this study by nuancing the link between thermal regime and response to experimental stress in these different coral species. They also provided supplemental data that are important and helpful. I now found that the scientific community would benefit from reading this work.

Minor comments or typos: l. 57 a role for the phosphorylation of histone and DNA methylation e.g. l. 86, l. 279, l. 464, l.669 (and throughout the manuscript) may delete ";" before references and referencing could be improved l. 133 "hyacinthus" instead of "Hyacinthus" l. 141 can tolerate "symbionts" instead of "partners (bionts)" l. 224 unit is missing for salinity l. 284 space before comma l. 408 missing space after "PSH05" l. 434 "sign" instead of "signs" l. 448 missing space after "explained" l. 460 double space l. 477 missing spaces l. 507 place the second "genes after the figure l. 542 "BLASTX" instead of "blastx" l. 550 missing space after "272" l. 615 missing space after the comma l. 683 missing space between "a" and "more" l. 857 "DESeq2" instead of "DEseq2", missing space between "fold" and "changes", space between "a" and "nd" l. 860 missing space between "fold" and "changes" Major comments: Microbiota I agree with the authors that the study on symbionts do not represent the main scope and results of this study. But in their Microbiome study published last year, they actually show that host genotypes and temperatures differently influenced Symbiodinium and bacterial microbiota. To my point of view, the authors in the present study could test the effect of host clonal line, Symbiodinium genotype, acclimation temperature and their interactions on the differential abundances of each OTU. The question behind this are: Is the host regulates its microbiota when "stressed"? What is the proportion of symbionts transmitted vertically? Microbiota can participate as genetic and non-genetic element in the host phenotypic plasticity.

Discussion I acknowledge the authors who streamlined the discussion, it helps to focus on the originality of the data. However, I think we now need a longer paragraph emphasizing on the functional aspects. Some aspects of the discussion, relative to other coral species could be expected. This would help to put these results in a wider picture.

Reviewed by Mar Sobral, 2019-04-16 17:47 I already pointed out in my previous revision that this work is very interesting and important. The writing is also very good. But, although improvement has been made to the manuscript in comparison to previous version, I still disagree with a couple of important conceptual as well as analytical issues (that I had already pointed out in my previous revision). So, my recommendation is again a major revision. This I because I believe there is conceptual confusion that wont help understanding the implications of the work. Second, the analytical limitations preclude the exploitation of results to their maximum potential. CONCEPTUAL ISSUES Line 43-44. It is not possible to interpret this work in the context of differences between localities, and I , the other referee and the editor explicitly said in previous version. So, line 40-41 is not what is tested in this research. Same for lines 79-80. Line 83-94. In my opinion this is wrong, as I already explained in my previous revision. Refocuse it more in line of what you say in lines 94-97. Line 98-100. No, you cannot discriminate between both processes with molecular approaches. And in any case, both would be entangled. Also, you have not data to test whether local adaptation is going on etc. Line 114-117. That is right, and that explains my two previous comments. Line 191-196. This is a good prediction to make, but a different story is to say that testing that is the purpose of the research (because in that case design would be not ok). ANALYTICAL ISSUES Line 334, performing one-way anovas for alpha diversity is not correct here, as I said in my previous revision. You have 42 alpha values right? Therefore, including site, colony within site, treatment and treatment*site should be possible and they need to be factors explaining alpha diversity at the colony level. Maybe you can assess how stress affects beta diversity whether you asses beta diversity within colonies (among replicates) and then you can analyze it as a response variable including treatment, site and their interaction in the model (if I don't misunderstand u can have n=12 values of beta diversity, because you can asses it among replicates within colonies and different betas for different teratments.). If I am wrong, please explain why and make it clear in the manuscript that no such an analyses are possible to run. MINOR COMMENTS Line 160-161. You do not test the role of microorganisms for this, is misleading mentioning it here? L 238 and 244. You say 8 tanks per colony first, and later 4. I understand is 4. Line 388 and 392, change condition for "treatment" . Line 414. Then, what is the name of this species? Again, this kind of means that design mixes species with localities, that is yet another reason NOT to interpret results in function of localities differences, but rather only in function of treatment differences. Line 417. Given this result is would make more sense to analyze either NC2 or NC3 all throughout the paper. It doesn't make a lot of sense to have a replicated genotype but no others. It is likely that differences between NC2 and NC3 can support some interpretations, in comparison with differences among other colonies (I am not thinking about anything in particular right now). Lines 443-445. This needs to be tested trough stats. I had already pointed this out in my previous revision. Line 449-455. This analysis is not correct, as I pointed out in a previous comment. Line 462-468. Why haven't you analyzed this at the OUT level? And just used "types"? Figure 7. I believe it is best to display it by colony. In the same colors and shades but making the differences between colonies. Line 536-538. Cool! Line 736-737. I remain unsure about these results as in previous versions. Line 749-751. Empty sentences as it is. Remove or develop if important. Line 7454-757. This is not necessary to be evolutionary meaningful. As I had already pointed out in my previous revision with references included (non-genetic inheritance affecting evolutionary dinamics). Line 819 Change line for row. Fig 6. Isn't it misleading? Shouldn't be all genes plotted and later, differences in density between quadrants could tell us whether there are more genes which behave similarly or differently between localities etc? *I think it is necessary to explain how DEseQ2 works Author's reply: Download author's reply (PDF file)

Revision round #1

2018-10-26

Dear authors, two reviewers have read your manuscript entitled "Gene expression plasticity and frontloading promote thermotolerance in Pocilloporid corals" and provided detailed and constructive reviews. As you will see, they both appreciated the topic, the experimental approach used and the impressive diversity of measures performed. However, they also raised a number of important concerns and requests, from the theory concepts to clarification of experimental design and important changes into the way analyses were performed. The authors should also modify throughout the manuscript the statements made about the link between thermal sensitivity and the traits quantified to make clear that the study consist in contrasting two populations (and even species), that differ in thermal regime but certainly not only. I need to make clear that, although your manuscript potentially represent an interesting contribution to the literature, that the conclusions hold on a comparison between two populations/species is a critical specificity of this study that should be outlined and made clear throughout the manuscript.

I encourage the authors to consider these detailed reviews to carefully revise their manuscript. Please keep in mind that the correct integration of the reviewers' requests is compulsory for the acceptance of this manuscript, but that I am uncertain at this step whether all these serious objections can be adequately addressed.

Thank you for submitting your work to PCI Ecology. I look forward to see the revised version of your manuscript soon.

Sincerely Staffan

Preprint DOI: https://doi.org/10.1101/398602

Reviewed by Mar Sobral, 2018-10-19 10:51

Comments by Mar Sobral on the manuscript submitted to PCI "Gene expression plasticity and frontloading promote thermotolerance in Pocilloporid corals" by Brener-Raffalli et al. and submitted by Eve Toulza I believe that studying gene expression plasticity and frontloading in face of a realistic and important environmental change (heat stress), for corals (which sustain a big amount of marine diversity) is a wonderful task to undertake. Both, because of the fundamental implications of this research (advances on the knowledge of evolutionary processes) and because of the potential practical use of this information. Even more, the fact that these organisms are holobionts and that bacterial and algae communities associated to the cnidarian hosts were investigated is a wonderful characteristic of this study. I also commend the authors for using so many alternative molecular approaches for ascribing the hosts to the species level, studying gene expression via transcriptomes, and studying bacterial and algae communities' compositions. Not only that, they used bioinformatics to search the proteins and function for each gene with a differential expression in the experiment. Additionally, I agree with the sampling and experimental design of the study. Because of all the previous reasons I believe this work has a huge potential. However, there are other reasons -which I believe are very important-to make me think that, before publication, this work should go trough a major revision. Particularly regarding data analyses and result interpretation. In summary; I believe that the work is really good but the manuscript is very immature yet. Here I explain some of my concerns.

Line 39 (and affecting the whole manuscript): With only 2 populations, each belonging to one of contrasting environments, this hypothesis is not tested. To test whether differences among populations from contrasting environments are due to environmental characteristics at the population level, it would be necessary to have several populations per contrasting environment or several populations along an environmental gradient (so to test a statistical relationship between environment and gene expression at the population level). Additionally, 3 different coral species were studied (one in Oman, with 3 colonies), another in New Caledonia (with one colony) and another in NC (with two colonies). These means that colony is not the same level of organization in OM and in NC, and that the comparison between NC and OM is not ok, because different coral species are being compared.

Lines 76-78 (and affecting the whole paper): The dilemma is not between acclimatization via intra generational plasticity and intergenerational Darwinian adaptation. As you say later, both processes can occur at the same time and complement each-other. But even more important is that there is also transgenerational plasticity, which is the clearer link between acclimatization and Darwinian microevolution. This is because natural selection acts on phenotypes, therefore transgenerational plasticity will change phenotypes available for natural selection to act upon, changing the evolutionary course of a population (see for example Day, Troy, and Russell Bonduriansky. "A unified approach to the evolutionary consequences of genetic and nongenetic inheritance." The American Naturalist 178.2 (2011): E18-E36, and other works by these authors). Additionally, the frontloading discussion (all over the manuscript) should have into account the "priming" processes explained in epigenetics (see works by Eva Jablonka). Regarding analyses of gene expression (L 393-400), I believe that expression differences between before and after the stress, should be the response variable in a model with locality, colony (nested within locality) and treatment and interaction between treatment and locality as factors. Another possibility is substitute localities and colonies by species, regrouping data in a different manner but probably the balance won't be ok to do that. I am not convinced that there were not differences between bacterial communities from hosts from different treatments. First, I believe that Fig. 2 needs to be changed in such a way that it is easier to understand. The legend and combination of colors and shapes makes it difficult to read. In any case, I can clearly see that for the first four genotypes in the legend there's always one of the stressed samples with a very different bacterial community than others in same genotype. I believe that an additional analysis should be made to test that. I believe that it is also needed a statistical procedure linking distances among bacterial communities with gene expression differences in hosts from control and stressed samples. That result (if there is a relationship) would prove that plastic and epigenetic effects not only affect evolution of involved populations but shape entire communities (in an analogous manner of works about community genetics by Thomas G. Whittam but with epigenetics) which is a very important potential results that goes overlooked in the current version of the manuscript. Additionally, (L 260-262) I believe this analysis is wrong. Alfa and Beta diversity should be response variables in a model including simultaneously locality, colony nested within locality, treatment (and if power enough the interaction between locality and treatment). I don't understand why one-way ANOVAS were chosen. Some doubts about design: All the nubbins bleached at the same time? It would have been necessary to use survival rates as a fitness measure at a point during the experiment to measure the costs of frontloading and plasticity to fitness (as you say in L 578). Why didn´t you do that? Do you have the data to test that idea? In L 193-194 I see that four nubbins per colony were placed in each tank, right? That would mean there were 12 nubbins per tank (8 tanks total). So, there were 96 nubbins, why later only 36 were studied? (L. 208). Explanation about this is needed. From the nubbins remaining in the experiment, were the 3 stressed ones per colony and population belonging to different tanks? same tank? etc? I believe it is necessary to include a figure explaining the experimental design. (It is possible that some of my comments reflect a lack of perfect understanding of what exactly was done with samples and data. That would mean that the writing should be much clearer). MINOR COMMENTS -I believe that a better explanation on how the Go analysis works is necessary, and also, that too much detail is given on that section, especially given that those results are partly speculative. I would move the function result section to supplementary materials (leaving only a general paragraph about patterns found) and the same is true for the functional section in the discussion. It makes the discussion unnecessarily long and takes space for potentially more interesting discussion on the evolution of plasticity (see works by Kathleen Donohue). For example, I would discuss a bit differences between predictable, variable and predictably variable environments and which strategies could be expected in each case.

  reviewed and recommended by PCI Ecology. doi: 10.1101/398602 [5] Kenkel, Carly D., and Matz, M. V. (2017). Gene expression plasticity as a mechanism of coral adaptation to a variable environment. Nature Ecology and Evolution, 1(1), 0014. doi: 10.1038/s41559-016-0014 [6] Kenkel, C. D., Meyer, E., and Matz, M. V. (2013). Gene expression under chronic heat stress in populations of the mustard hill coral (Porites astreoides) from different thermal environments. Molecular Ecology, 22(16), 4322-4334. doi: 10.1111/mec.12390

  -Line 52: What do you mean by highly enriched? -Line 53: Advance which insights. -Line 99-100, I believe you mean via transgenerational epigenetics processes, right? -Line 86-87, typo? Something lacking? Sentence is not understandable. -Often, specially between text and figures you mix the term colony and genotype, please use the same throughout the manuscript. Same occurs for population and locality (Locality is changed for population in the supplementary materials, and supplementary materials are refereed to as additional materials). -L. 166: With this aim. -L. 181: How many clones? -L 186. As I said, no implications can be made from environmental differences because only two localities are studied, but even more important because different species are studied per locality and in NC ,2 different species are mixed. -L 45 and 203 seem contradictory. -L 295. I believe the use of a posteriori is wrong in this context -L 264. The comparison should be made per colony so that we avoid the problems of mixing different species and localities. -L 296. As I said, comparing localities with different species is not ok. -L414-415. From these lines I don´t see what the analysis was about. It seems wrong, unless I miss something. L 415-417. Having the result of the GLM why you would need to perform Wilcoxon tests. Again, I am not sure if I miss something. L 479. Which analysis? L504. I disagree, the experimental design doesn't allow to focus results this way as I comment previously. Same for line 525. L 520. Remove to. L 556. This comparison should me made within genotype, not possible to mix the responses of different genotypes and specially such in the case of NC if they belong to different species. L568: Which stats were used for this comparison? L 586, Very few what? L 600. Eliminate also. L 628. I don't understand what you mean, explain where it comes from please. L741-742. That is great, I would focus this entire section on this idea making it less descriptive and shorter. -Fig 6. In the text it is said that there are 24 genes which were overexpressed in OM and underexpressed in NC (L 406-407), why they aren´t show in Fig 6? Am I missing anything? -Fig 7. Interestingly the transcriptomes from stressed colonies were more like another than non-stressed transcriptomes, I believe that result is very relevant and I didn´t find anything about it in the text. Reviewed by anonymous reviewer, 2018-10-24 11:32 Download the review (PDF file) Author's reply: Download author's reply (PDF file)


Sébastien Barot

Vincent Maire

Nitrate or not nitrate. That is the question

The article by Legay et al. [START_REF] Legay | Studies of NH4+ and NO3-uptake ability of subalpine plants and resource-use strategy identified by their functional traits. bioRxiv, 372235, ver. 4 peer[END_REF] addresses two main issues: the links between belowground and aboveground plant traits and the links between plant strategies (as defined by these traits) and the capacity to absorb nitrate and ammonium. I recommend this work because these are important and current issues. The literature on plant traits is extremely rich and the existence of a leaf economic spectrum linked to a gradient between conservative and acquisitive plants is now extremely well established [START_REF] Shipley | Fundamental trade-offs generating the worldwide leaf economics spectrum[END_REF][START_REF] Reich | The world-wide 'fast-slow' plant economics spectrum: a traits manifesto[END_REF]. Many teams are now working on belowground traits and possible links with the aboveground gradients [START_REF] Maire | Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species[END_REF][START_REF] Roumet | Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy[END_REF]. It seems indeed that there is a root economic spectrum but this spectrum is apparently less pronounced than the leaf economic spectrum. The existence of links between the two spectrums are still controversial and are likely not universal as suggested by discrepant results and after all a plant could have a conservative strategy aboveground and an acquisitive strategy belowground (or vice-versa) because, indeed, constraints are different belowground and aboveground (for example because in given ecosystem/vegetation type light may be abundant but not water or mineral nutrients). The various results obtained also suggest that we do not full understand the diversity of belowground strategies, what is at stake with these strategies, and the links with root characteristics. Each time I give a conference on the work we are carrying out on African grasses that likely absorb ammonium preferentially because they inhibit nitrification [START_REF] Lata | Grass populations control nitrification in savanna soils[END_REF][START_REF] Srikanthasamy | Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna[END_REF], somebody asks me a question about the fact that plant essentially absorb nitrate because ammonium is toxic and nitrate more available in the soil. The present article confirms that this is not the case and that, though there are currently some teams working on the subject, we do not really know for the moment whether plants absorb nitrate or ammonium, in which proportion, how plastic this proportion is within individuals and within species. This subject seems to me crucial because it is linked to (1) the capacity of ecosystems to conserve nitrogen [START_REF] Boudsocq | Modelling approach to analyze the effects of nitrification inhibition on primary production[END_REF], because nitrate, much more than ammonium, goes out of ecosystems through leaching and denitrification, (2) to carbon cycling and plant energy budget because absorbing nitrate requires spending mucho more energy than absorbing ammonium because nitrate must be reduced before being incorporated in plant biomass, which is very energy costly. These two issues are naturally very relevant to develop efficient cropping systems in terms of carbon and nitrogen. Interestingly, the present article, comparing three grass species in different sites, suggests that there is no trade-off between the absorption of nitrate and ammonium: more acquisitive individuals tend to absorb more ammonium and nitrate. This is contrary to hypotheses we made to predict the outcome of competition between plants absorbing nitrate and ammonium in different proportions [9] but should be tested in the future comparing many different types of plants. The results also suggest that more conservative plants absorb relatively more ammonium, which makes sense because this allows them to spare the energy necessary to reduce nitrate. This leads to the question of the effect of these strategies on nitrogen retention within the ecosystem. If nitrification is high (low), absorbing ammonium is not efficient and likely leads to high (low) nitrogen losses. This should be tested in the future. Moreover, the authors have measured the absorption of nitrate and ammonium through measurements at the root scale on cut roots. This should be complemented by measurements at the whole plant scale.

Plant preference for ammonium versus nitrate: a neglected determinant of ecosystem functioning? Am. Nat., 180, 60-69. doi: 10.1086/665997

Revision round #2 2019-12-15 I am satisfied with the way the manuscript has been improved and the reviewers' comments addressed. I would be ready to recommend the manuscript but have a few more comments. The abstract could mention the fact that the preference for ammonium vs. nitrate is different between species and higher for conservative species. I like the discussion however: 1) It should explicitly mention the fact that the interpretation is limited by the fact that only three species are studies. 2) I think the way nitrate and ammonium uptake rates are measured is very useful but I think the discussion/conclusion should mention that it would also be interesting to measure the absorption of nitrate and ammonium at the whole plant scale. For example, through 15N pulses. This could give a different image of N uptake. 3) I like the discussion about the differences between the relative nitrate and ammonium rates and the link with the plant strategy. However, I am surprised it is never mentioned that assimilating ammonium is less costly than assimilating nitrate (that has to be reduced). This could be in line with a more conservative strategy? Similarly the influence, of the ammonium vs. nitrate preference likely has consequences on ecosystem functioning and the N budget of the ecosystem (because nitrate is more prone to losses) (see [START_REF] Boudsocq | Modelling approach to analyze the effects of nitrification inhibition on primary production[END_REF] and 2012, OK I am co-author of these articles). 4) Ammonium is more absorbed during autumn. Could that just be due to the fact that ammonium is less mobile than nitrate within the soil so that it requires more humid soils to be absorbed? There are still some writing glitches. I have listed some of them (see below) but the manuscript should be carefully proofread. Line 55. It is awkward to start the sentence with "And". I think the "plant ecology, " should be deleted Line 60. I suggest "the significance of root traits is less understood than the one of leaf traits" Line 66. "is both influenced by anatomical …. and by physiological adjustments such as …" Line 69. "Nitrogen is one of the best studied mineral nutrients and its uptake by plants under both the ammonium and nitrate forms is influential for plant and ecosystem functioning" Line 72 "some information" à la place de "supports" Line 100. Could the first hypothesis be expressed more precisely? What does that mean "contributing to the economic spectrum"? Does that mean that there is a root economic spectrum fully correlated (positively) to the leaf spectrum? Line 105. I do not understand the "both in quantity and quality" Line 130. "managements" Line 146. "during the day" Line 151 "kept in ice"? Line 152 "5.6 mm mesh" Line 164 "living young roots" Line 174 "root 15N natural" Line 183 "at the cost of losing relevant ecological information" Line 210 "Hanes's relations were used" or ''Hanes's relation was used" Line 269 I do not understand this sentence because obviously the paragraph is comparing different sites Line 287 I find that "resource use " is too vague and not related enough to the previous sentence Line 288 "despite relatively weak relationships" Line 289 "different selective pressures" "specializations" Line 304 "indeed" seems to me inappropriate here Line 326 "opposite response" is for me to vague.

Response to what? Response of what? Line 359 "could depend on" Line 364 The sentence is in my opinion awkward. Should the plural be used? Not clear whether this is a result of the manuscript or a general thought coming from the reference. Line 379 "remain" Line 397 "grassland N cycling rate" Preprint DOI: https://doi.org/10.1101/372235 plants may be selected to optimise Km to ensure a sufficient influx of nutrients under conditions of low availability. While Vmax is potentially important (especially in cases of clear nutrient pulses, e.g. immediately after snow melt or after sufficient moisture at the end of the summer), I think the authors should have presented both parameters and should give a rationale why maximum uptake capacity rather than Km would fit better with a plant economics spectrum.

The authors also report to have measured δ15N at natural abundance (l. 169) but do not report them. While there has been substantial debate to what extent these data relate to differential uptake from separate sources (peoples have overconfidently used such data to link these results to mycorrhizal preferences for various N sources) and / or to isotopic discrimination during uptake, I think it would have been helpful if the authors has measured the 15N signature of both ammonium and nitrate in their soils. Such data could also increase the ecological significance. The authors decided not to supply both nutrients at the same time, but I did not read a rationale why this would have been important. Considering that N-uptake has a major effect on the proton balance in the rhizosphere, may plants would likely take up both with a mixed supply to minimise pH-changes in the rhizosphere. In terms of functionality, such a mixed uptake system may be very relevant. A view that looks at these as independent (and synergistic -l. 298l; how was this tested?), misses functionality of uptake systems.

The design is pretty minimalistic (three grass species; one grassland in which all three species occurred; and three grasslands where only one species was found). And disentangling species effects from site effects is only possible with n = 2. In order to increase significance of their data, the others sampled more plants per site. At a distance of a few meters, one could differ in the opinion whether these constitute 'true' replicates or pseudoreplicates (which increase the degrees of freedom and hence the significance of statistical tests; only Fig. 2 seems to aggregate the individual root samples into one average value with 12 data points). The other sampled during two seasons and described the roots sampled (l. 160) as young fine roots. There is little detail and one wonders whether root age and root nutritional status (rather than seasonality) contributed to seasonal differences. (There could also have been differences in mycorrhizal colonisation in both seasons, and even though these three species show only limited growth responses to mycorrhiza, it does not follow that differences in uptake patterns are related to difference in mycorrhizal fungal mycelium surrounding the roots).

Author's reply: Download author's reply (PDF file)

Author's reply: Download author's reply (PDF file) Revision round #1

2018-10-16

Dear authors Your manuscript is interesting. However, the two reviews are pointing at potential problems that should be addressed before any final decision is made. I am looking forward reading a new version of the manuscript together with answers to the reviewers. I apologize for delay in sending my decision. It has indeed been difficult to find reviewers during the summer period. Reviewed by anonymous reviewer, 2018-08-14 09:41

The ms compared for three grasses in four different grasslands (but only one grassland contained all three species!) patterns of ammonium and nitrate uptake capacity in relation to several aboveground and belowground functional traits. When reading the ms I noted that very little literature post-2010 was cited. I found this curious, as the field of root traits (and their possible coordination with leaf traits) is a flourishing research field. However, the explanation is simple: the ms is just around four years old; and rather than let it rest in peace the authors decided to submit it. However, they cited a paper by Grassein et al. in press (l. 467; note that in the text, but not in the references there are papers by Grassein et al. 2010, 2015 & in press). But the paper in press (in Ann. Bot.) was published in January 2015 (with on-line availability at the end of 2014). As I do not think it is the duty of reviewers to come up with suggestions of important literature, when the authors could easily have done so themselves, I will not go in details where the paper could be improved. The paper is also sloppy in other respects. The description on functional traits is partly repetitive (SRL is mentioned twice), while the paper makes inconsistent claims how long excised roots were stored before measurements (l. 161 mentions less than 2 hours, l. 177 less than sixty minutes). Again, these mistakes should have been seen by at least one of the six authors! I will only give a few examples where I think that more careful ecological considerations would have been important.

The authors decided to measure Vmax rather than Km (although the text in l. 211 suggests that the latter parameter was also measured but not reported). However, they did not provide a rationale for it. As they studied the high-affinity uptake systems they looked at uptake at low concentrations. Under such conditions