DOI: 10.5061/dryad.931zcrjw4
title: Ecosystem engineers alter the evolution of seed size by impacting fertility and the understory light environment

description: The extinction of the dinosaurs and later, the Pleistocene Megafauna, has
 been hypothesized to have created a darker forest subcanopy benefiting
 large-seeded plants. Larger seeds and their fruit, in turn, opened a
 dietary niche space for animals thus strongly shaping the ecology of the
 Cenozoic, including our fruit-eating primate ancestors. In this paper, we
 develop a mechanistic model where we replicate the conditions of tropical
 forests of the early Paleocene, with small animal body and small seed
 size, and the Holocene, with small animal body and large seed
 size.  We first calibrate light levels in our model using stable
 carbon isotope ratios from fossil leaves and estimate a decrease of
 understory light of ~90 µmol m-2 s-1 (a 19% decrease) from the Cretaceous
 to the Paleocene. Our model predicts a rapid increase in seed size during
 the Paleocene that eventually plateaued or declined slightly.
 Specifically, we find a dynamic feedback where increased animal sizes
 opened the understory causing a negative feedback by increasing subcanopy
 light penetration that limited maximum seed size which matched the actual
 trend in angiosperm seed sizes in mid/high latitude ecosystems. 
 Adding that larger animals can increase ecosystem fertility to the model,
 further increased mean animal body size by 17% and mean seed size by 90%.
 Our model is a drastic simplification and there are many remaining
 uncertainties, but we show that ecological dynamics can explain seed size
 trends without adding external factors like climate changes.
description: <strong>Model: </strong>To understand the long-term
 interactions between angiosperm seed size, animal size and the understory
 light environment, we created an individual based model using Matlab
 (Mathworks) with a grid size of 50 by 50 cells (also tested at 100 by
 100). Each grid cell was assigned an initial animal bodyweight of 1kg and
 a seed size of 0.038g to simulate the small seeds and animals present in
 the aftermath of the dinosaur extinction event (Eriksson, 2016; Smith et
 al., 2010). We focus on angiosperm not gymnosperm seeds because the fruit
 surrounding angiosperm seeds will attract dispersers.  At each timestep,
 animal/seed mass is assigned based on randomly choosing a value within a
 distribution with a mean based on the animal/seed size from the prior
 timestep and a normally distributed standard deviation of 2/3 for
 plants/animals (also as 1% percent of body weight in a sensitivity study)
 with lower mass truncated at 0.038g for seeds and 0.03kg for animals (but
 no upper threshold). Trees can produce more small seeds than big ones, but
 seedling survival is a linear function of seed size (Baraloto et al
 2005).  Therefore, assuming the same energy input per tree into seed mass
 regardless of seed size, increased numbers of seeds do not increase
 survivability (or vice versa) and we do not change number of seeds in each
 grid cell at each iteration.  Based on the seed size for each grid cell,
 we calculate how tall the seedling (between 1cm and no upper limit) will
 become based on the following equation based on eight tropical trees
 species: Eq 1 - Plant height (cm) =  18.9+ 5.2*
 log<sub>n</sub>(seed size) (g)(r<sup>2</sup>=0.95,
 P&lt;0.0001) (BARALOTO et al., 2005). Next, we
 calculate understory light environment at the height of that seedling.  To
 do this, we estimate the vertical light environment under a disturbance
 gradient using the results of a logging experiment from Brazil (Fauset et
 al., 2017) with the following equation: Eq 2 =  T(H) =
 a + exp(kz*H); Where T is light transmission as a
 percentage of the top of canopy irradiance (2,000 µmol
 m<sup>-2</sup> s<sup>-1</sup>) at height Z,
 <em>a</em> is <em>T</em> at 1 meter and
 <em>k</em><sub>z</sub> is an extinction
 coefficient based on height above the ground (H).  Faucet et al 2017 used
 values of 2.5 / 6.2 for a and 0.190 /0.213 for kz for intact/selective
 logged forests.  We used these same values but adapted them for animal
 induced disturbance.  Since the Cretaceous understory was very open
 (Carvalho et al., 2021), we assumed animals reaching the size of sauropods
 (~10,000 kg  - a median including several dinosaur size classes, not just
 the biggest) would mimic the impact of a “light logging” event. 
 We explore this in figure 2 using data from Ehleringer et al 1986
 relating light environment to d13 carbon isotopic ratios (Ehleringer et
 al., 1986).  On this graph, we added the minimum d13 values from a
 Cretaceous forest compared to the minimum from a Paleocene forest (H. V
 Graham et al., 2019).  We justify using the minimum because it is unknown
 which part of the canopy the fossil leaves were from, but the understory
 will always be the darkest and that is the part of the forest of interest
 for our study.  When we place the minimum values from each site into our
 equation, we estimate a change in light levels of 89.9 µmol
 m<sup>-2</sup> s<sup>-1</sup> (a 19% decrease from
 the Cretaceous to the early Paleocene) (Figure 2).  We therefore estimate
 the structural impact of an animal with a size of 10 kg in a grid cell
 using the coefficients of an unlogged forest (2.5/0.19) and an animal with
 a size of 10,000 kg animals with the coefficients of a logged forest
 (6.2/0.213) with linear interpolation in between.  For the fine scale
 light differences at the bottom meter of the canopy, we used data from
 Montgomery 2004 who found that light transmittance decreased from 16 to 9
 to 2% in light in three tropical forests in Brazil, Panama and Peru
 between ~0-1 m height above ground surface (Montgomery, 2004).  Therefore,
 1m light levels are calculated using Eq 2 and below this, light decreases
 linearly to the ground by an additional 9% (also 2 and 16%).  In a
 sensitivity study, we test all these values and we also run a dynamic
 change model where the larger the mean body size the more open the bottom
 meter is (toward 16%). We then calculate the likelihood
 of sapling survival based on the height of the seedling and the light
 level at that height.  Baraloto et al 2005 found a significant positive
 relationship between light and survivorship for eight tree species that
 represent a range of seed sizes with a standardized regression coefficient
 of 0.14 after 5 years for all species (Baraloto et al 2005).  An increase
 in survivorship of 0.14 when light changed from 1.3% (50%) to 4.1% (95%)
 of full sun (assuming top of canopy maximum of 2,000 µmol
 m<sup>-2</sup> s<sup>-1 ) </sup>means understory
 species ability to survive increased by 14% per 28 µmol
 m<sup>-2</sup> s<sup>-1</sup> increase or 0.5% per
 µmol m<sup>-2</sup> s<sup>-1</sup> increase.  The
 light compensation point for photosynthesis can vary between species but
 one study found it averages ~10 µmol m<sup>-2</sup>
 s<sup>-1</sup> (Craine & Reich, 2005), and eq 3 gives
 0% survival at 10 µmol m<sup>-2</sup>
 s<sup>-1</sup> and below. Eq 3 –  survival
 = (0.5*(light level-10))/100 In a sensitivity study, we
 use a non-linear equation (eq 4) which will increase survival more greatly
 as lower light levels are increased. Eq 4 - survival=
 (18.62*log(light level -10)-15.61)/100 At each
 timestep, the seed will replace the seed size of the previous iteration if
 survival is greater than a random number between 0 and 1, if not, the old
 seed size will remain.  As understory light levels increase, we assume the
 more numerous smaller seeds will begin to outcompete the bigger seeds with
 a 50% chance of a 5-fold decrease in seed size between light levels of 75
 and 100 µmol m<sup>-2</sup> s<sup>-1</sup>, a 75%
 chance of a 10-fold decrease in seed size between 100 and 150 µmol
 m<sup>-2</sup> s<sup>-1</sup>, and a 95% chance
 20-fold decrease in seed size above 150 µmol m<sup>-2</sup>
 s<sup>-1</sup> (varied in a sensitivity study – Table
 1).  Larger animals will competitively exclude smaller
 animals for access to terrestrial resources (Abraham et al., 2023) and
 based on this, in our model, we allow larger bodied animals primary access
 to fruit (Gautier-Hion et al., 1985).  We allow for the evolution of
 larger bodied animals in the model over time to replicate the dramatic
 increase in animal body size of the Paleocene (Smith et al., 2010).  The
 edibility (E) of the seeds by frugivores is based on esophagus size, which
 we assume is linearly related to animal size with the equation:
 Eq 5 - esophagus size (cm) =  0.0027 * M (kg) +1.734   Doughty et
 al.  2016 If the seed in the grid cell is too small,
 then it is ill suited for that animal and in the cell, the animal will be
 replaced by a smaller one (if seed is between 3-6 times smaller than the
 throat, the current animal will be replaced by an animal 4.5 times
 smaller, between 6-12 times size of throat, an animal 9 times smaller, and
 less than 12 times the size of the throat, an animal 20 times smaller). 
 If the seed size is too big to be consumed, then we assume that it will
 not succeed and be replaced by the average seed size of all touching
 pixels.  We estimate mammal movement of seeds using equations 6-8 from
 Wolf et al 2013. Eq 6 – Day range (km/d) = 0.453 *
 M^0.368 Eq 7 – Passage time (d) = 0.29 *
 M^0.26 Eq 8 - Linear distance moved (km) = Day
 range*passage time Based on the above equations, we
 separate animal size into three categories (below 5kg, between 5 and 50kg,
 and above 50 kg – these numbers are varied in a sensitivity study in Table
 2).  Animals the size of 5kg or less access only the grid cell they are
 in. Between animal sizes of 5 and 50 kg the animals can access neighboring
 grid cells (3 by 3) and above 50kg can access 5 by 5 grid cells.  We
 assume each grid cell is ~0.25 km<sup>2</sup>, or the
 approximate maximum distance across a 5kg mammal could spread a seed (0.5
 km).  The animal will spread the seeds into the neighboring cells (with
 75% probability – varied in a sensitivity study - Table 1) if the seed can
 fit in the animal’s throat but are not less than 3-12 (explained above)
 times smaller than can fit since such small seed/fruit may not interest
 large animals.  If the animal replaces the seed in the grid cell, it will
 also replace any smaller (but not bigger) animal present in the grid
 cell.    This replicates how larger bodied animals will often
 competitively access resources at preferential times over smaller bodied
 animals(Abraham et al., 2023).  The understory light environment is based
 on the size of the animal in the grid cell following eq 2.  An animal is
 less likely to disperse a seed further away (i.e. 2 grid cells versus 1),
 but nearby cells will have higher density dependent seed mortality, and
 therefore, our model gives seeds in both near and far pixels the same
 success probability (75% but varied in a sensitivity study – Table 2).  We
 recognize the key role of birds in dispersing seeds, but the focus of this
 study is only mammal frugivores.
 <strong>Fertility: </strong>We then explored the
 implications of how changing animal body size could impact fertility. 
 Larger body size can increase fertility at continental scales over
 millions of years (Doughty, 2017).  Here we expand that work to show
 nutrient diffusion capacity for the last 100 million years in greater
 detail.  We first calculate nutrient diffusion capacity (Doughty et al.,
 2013; Wolf et al., 2013) for the last 100 million years based on the
 largest bodied animal in each time period using data from (Benson et al.,
 2014; Smith et al., 2010).  We then compare this to coal (fossilized
 leaves) chemistry data from COALQUAL (CQ20166334750) (Palmer et al., 2015)
 for three time periods – the Cretaceous (N=680), Cretaceous-Tertiary (N=4)
 and the Paleogene-Neogene (labeled Tertiary in COALQUAL) (N=991) for the
 critical plant nutrients P, K, Mg and S as a ratio following the
 methodology from Doughty 2017. K is excluded due to its absorption during
 clay formation (Kumari & Mohan, 2021), hence concentrations of K
 in coal cannot be expected to show good correlation with general plant
 availability.  Cretaceous-Tertiary coal is mainly from the Chuckanut
 Formation which began ~54 Ma. We compare these data to aluminum, a proxy
 for abiotic rock weathering.  We use the exact data and methodology from
 Doughty, 2017.  We then explore how the relationship
 between body size and fertility might impact seed and understory light
 dynamics.  To do this, in our model we make fertility an increasing
 function of average body size and then fertility can impact seed size
 because seed standard deviation is a function of fertility.  We varied
 seed standard deviation between 1 and 2; as the mean body size increased
 towards 5,000 kg the seed standard deviation moved closer to 2.  Increased
 mean body size increases fertility which allows seed size to potentially
 get bigger but does not preferentially choose bigger seeds.  We
 acknowledge there is little empirical data to support the direct
 relationship between fertility and standard deviation of seed size, but
 fertility generally increases fruit abundance with, for instance, a
 fivefold increase in soil phosphorus leading to a fourfold increase in
 fruit abundance (Doughty et al., 2014).
 <strong>Simulations: </strong>With the above
 described model, we simulate three scenarios: Early Paleocene where we
 start with animal size = 1 kg, seed size = 0.038g, light environment =  1
 µmol m<sup>-2</sup> s<sup>-1</sup>, future
 scenario 1 where we start with animal size = 10 kg, seed size = 100 g,
 light environment =  1 µmol m<sup>-2</sup>
 s<sup>-1</sup>, and future scenario 2 where we start with
 animal size = 10 kg, seed size = 100 g, light environment =  150 µmol
 m<sup>-2</sup> s<sup>-1</sup>.
 To test why seed size may have differed across the C -Pg boundary
 between low and higher latitude ecosystems, we add a temporal climate
 variability aspect to our model.  In our model, in mid to high latitude
 systems (Naware & Benson, 2024), on even time steps the standard
 deviation of potential seed size is three and on odd steps it is 1.  For
 low latitude systems, the standard deviation is always 2. This replicates
 the greater variability inherent in mid/high latitude systems which might
 vary between good years (SD 3) and bad, more conservative years (SD
 1).     <strong>Datasets: </strong>We use
 isotopic data from Graham et al 2019 and from Ehleringer et al 1986 to
 predict understory light differences.  We used data from Baraloto et al
 2005 to establish relationships between seed size, height and
 survivability under different light conditions.  We use results from
 Faucet et al 2017 to predict vertical light profiles along a disturbance
 gradient and results from Montgomery 2004 to predict light profiles in the
 bottom meter of the canopy.  We use data from COALQUAL (CQ20166334750)
 (Palmer et al., 2015) to show chemical differences between time periods
 following the methodology from Doughty 2017 (Doughty, 2017).
description: # Ecosystem engineers alter the evolution of seed size by impacting
 fertility and the understory light environment
 [https://doi.org/10.5061/dryad.931zcrjw4](https://doi.org/10.5061/dryad.931zcrjw4) ## Description of the data and file structure We use isotopic data from Graham et al 2019 and from Ehleringer et al 1986 to predict understory light differences.  We used data from Baraloto et al 2005 to establish relationships between seed size, height and survivability under different light conditions.  We use results from Faucet et al 2017 to predict vertical light profiles along a disturbance gradient and results from Montgomery 2004 to predict light profiles in the bottom meter of the canopy.  We use data from COALQUAL (CQ20166334750) (Palmer et al., 2015) to show chemical differences between time periods following the methodology from Doughty 2017 (Doughty, 2017). ### Files and variables #### File: all\_paleo\_data.mat **Description:** Data from various papers listed below to create model and figures from paper ##### Variables * bodysize, Mammal size data from Smith et al 2010 - units kg * seedsize - seed volume from Erikson et al 2016 units mm3 * CQ20166334750, - elemental data from COALQUAL database from Palmer et al., 2015- units PPM * Cret, - Cretaceous Guaduas Formation from Graham et al., 2019 units isotopic fractionation * postKT3015, - Paleocene Cerrejón Formation from Graham et al., 2019 units isotopic fractionation * dino2, - nutrient diffusion capacity based on the largest terrestrial animal size from each period from Doughty 2017 * marine, - nutrient diffusion capacity based on the largest marine animal size from each period from Doughty 2017 * photond13, is a dataset that contains delta carbon 13 values units (units ‰) from four plant species and the understory light environment (units umol m-2 s-1) using data originally from Ehleringer et al 1986 **A detailed description of the software file named "Final_code_Doughty_Palass_2024.m"** This code has two sections.  In the top section, it will produce figures 2,3,6 and 7 from the paper.  These figures graph and manipulate the datasets listed above for the understory light environment (fig 2), seed growth at different light levels (fig 3), animal body size and seed size over time (fig 6) and nutrient concentrations at different time periods (fig 7).  Those data form parameters for the second part of the code starting on line 266 which is the model described in depth in the paper where we allow animals to distribute seeds and change seed size over time.  The output of this section will produce figures 4 and 5. In an update, we changed the y axis of fig 3 to the log scale.  ## Access information Other publicly accessible locations of the data: * [https://ncrdspublic.er.usgs.gov/coalqual/](https://ncrdspublic.er.usgs.gov/coalqual/) Data was derived from the following sources: * Various papers listed in the text