Joshua Trees Flower Episodically in Arizona

Intro

Joshua trees are large, visually-striking trees in the Mojave desert.  Most of them are in California and Nevada, but there is also a population in the western part of Arizona.  They are frequently photographed and there are more than 17,000 observations (1,000 in AZ) saved on iNaturalist, a website and app used to document biodiversity.  

Arizona Joshua Tree locations observed on iNaturalistiNaturalist.

Joshua trees produce showy clusters of white flowers at the tips of their branches in March, but this year I noticed they were not flowering.  I wondered how often they produce flowers and decided to answer this question using data from iNat.

53 observations in Arizona showed evidence of flowering, always in March and April.  

Methods

iNat observations of Joshua Trees (Yucca brevifolia) in Arizona were marked using the Plant Phenology option in the Annotation Field.  Plant phenology (flower budding, flowering, or fruiting) was determined based on visual inspection of the saved photos in iNat.

The iNat website has a nice phenology visualization tool.  This view is filtered to show only Arizona observations.  However, it cannot show differences in phenology from one year to the next.  

Observations were then filtered on the iNat Explore page by adding &term_id=12&term_value_id=13 to the URL and downloaded for analysis in Excel.

More info about using iNat search URLs.

Results

I graphed the results starting in 2017, because there are fewer iNat observations before 2017.  It appears Joshua Trees flower episodically.  According to this data, Joshua Trees flowered in four out of the last 7 years.  They appear to alternate years from 2017-2020, but then skipped 2021 and flowered in both 2022 and 2023.  

It is interesting to note that the Arizona Joshua Trees didn't flower in 2020, which was one of the wettest springs in the last 10 years. I wonder whether the spring moisture determines flowering, or if perhaps other climate variables, such as moisture in the fall, are more important.  Another possibility could be that the trees are only able to flower every other year, and that the trees were inhibited from flowering in 2020 because of the large number that flowered in 2019.  

According to this data they were able to flower in both 2022 and 2023, but at reduced numbers both years.  Perhaps the plants flowering in 2023 were different from the trees that had already flowered in 2022?  I can't answer that question with this iNat data.  While it appears that the areas of flowering in 2022 and 2023 were the same, not all of the Joshua trees in a given area necessarily flower, even in good years...

How to Estimate Emissions from Land Use Change

This blog post highlights the valuable role played by GIS layers in planning and complying with upcoming GHG reporting standards. New protocols will classify carbon released from land use changes as Scope 1 emissions, requiring stricter tracking.

There are several GIS layers (reviewed below) that can be used to estimate potential carbon emissions from biomass and soil carbon losses due to land development projects. While these layers may not be suitable for final reporting, they can be valuable for:

• Strategic planning: Identifying areas with high potential emissions and prioritizing mitigation efforts.
• Impact Assessment: Estimating the range of carbon emissions from projects.

These GIS layers, available in Esri's ArcGIS Online Living Atlas, have the potential to improve the ability of large businesses to plan for and comply with upcoming regulations related to land use change emissions.

UNEP Above and Below Ground Biomass Carbon 

Two datasets represent above- and below-ground terrestrial carbon storage (tonnes (t) of C per hectare (ha)) for the entire globe (2010).  The first layer layer estimates total biomass (i.e. plant parts such as roots, leaves, trunks) whereas the second layer includes soil organic carbon (SOC) and is therefore weighted to show the contribution of peat and permafrost-contained regions.  Both layers support direct analysis in GIS software.    

Left: First dataset shows plant biomass with large concentrations of C in the world's forests.  Right: Second dataset includes SOC and shows the large amounts of C in the world's arctic peat and permafrost.

USFS Predominant Major Forest Carbon Pools of the Continental United States

This layer layer depicts the predominant major forest carbon (short tons per pixel) pools of the Continental United States. The layer used USFS Forest Inventory & Analysis plot data and Landsat 8 Operational Land Imager scenes as inputs to an ecological climate model to estimate Live, Dead, and Organic Soil carbon pools.  However, the data is somewhat difficult to analyze because each pool is in separate raster image bands, and because the metric reported is short tons per pixel, where the pixel size varies across the map based on Web Mercator projection.  

USFS offers a faster and easier to use layer called CONUS Total Forest Carbon 2018, which provides short tons Carbon per pixel summed across all 8 individual carbon pools.  

Around Prescott, AZ the pixel size is 80 by 80 ft, so each pixel value must be multiplied by 6.8 to get tons per acre.  It looks like most of the pixels show a carbon pool of 30-36 tons/acre in this area.

To compare this layer with the UN layers mentioned above, it is necessary to convert US tons to metric tons and acres to hectares.  Overall this yields a correction factor of 2.24 to get from tons/acre to metric tons/hectare.  This yields a range of 67-80 metric tons/hectare carbon based on the USFS layer.  The UN Total Biomass layer estimates anywhere from 38-50 metric tons/hectare, while the UN layer that adds in SOC estimates 120-160 metric tons/hectare.  It seems that the USFS map estimates carbon pools in between these two ranges.

Northern AZ pine forests viewed in the USFS Forest Carbon layer.  It is not always clear how to interpret this data.

The Biggest Problem in Conservation: Taxonomy

One of the interesting unspoken secrets of the conservation world is that taxonomists are in charge.  More specifically, what taxonomists consider interesting enough to name as a species or a subspecies determines what can be protected.  After all, it is the Endangered Species Act.  But what if the taxonomists can't agree on what a species is?

This excellent short article in the Atlantic provides examples form hawthorn trees, which, depending on who you talk to, are either in decline and in need of conservation, or so widely distributed and common that it would be like trying to preserve Kentucky Bluegrass.

"A few years ago, conservation groups were gearing up to assign the [balsam-mountain hawthorn] tree the rarest rank a species can receive, which would imply an urgent necessity to conserve it. But [a botanist] decided it was probably a hybrid of two other hawthorns. He still believed the tree should be protected, but instantly, the species went from critically rare to nonexistent, from a conservation point of view."

"A prominent evolutionary biologist, wrote in 1976,  that perhaps no true hawthorn species exist at all—that they make up a sort of genetic continuum that doesn’t allow for coherent species classification."

"[another] botanist... told me the biggest threat to the trees is not land-use changes but botanists themselves, who are unwilling to meet the taxonomic challenge. If no one takes on the task of categorizing hawthorns, then no conservation group can take any measures to save them."

"Now whatever solution [the botanists] come to will determine what we try to save."

More Springtime NDVI Observations

 I recently took a driving tour from Prescott to Cottonwood and back.  Most areas have dried out already.  This post reviews the phenology, NDVI greenness maps, and rainfall patterns in the area.

Verde Valley  - wildflowers, hedgehog cactus flowers

2,437 32 AGDD 

501 50 AGDD

I-17 and General Crook  - mesquite just starting to flower, grasses dry

2,202 32 AGDD 

394  50 AGDD

Verde Valley native desert grassland with scattered juniper.  Some wildflowers are present, but most areas are dry.

Dugas - mesquite just starting to flower, grasses dry

2,414 

462 50 AGDD

169 and I-17 - Mesquite still leafing out, some grasses still green

2,224  32 AGDD 

400 50 AGDD

Hills near Dugas with dry invasive annual grasses.  Few to no flowers present.

89A at base of Mingus mountain grasses greening up, still early in the growing season

1,773  32 AGDD 

89A at base of Mingus mountain powerline ROW showing early spring green up of cool season grasses.

NDVI

DroughtView is still showing anomalously green areas between Cordes and Flower Pot along I-17, but these hills around Dugas are already quite dry (see image above).

Most recent (4/6-4/21) NDVI difference map

It matches the NDVI variance from that time period.  At this time there was still anomalous green up around Dugas, for example.  

MODIS NDVI (Near Real Time 8 Day) 4/6-4/21

DroughtView also shows straight NDVI, with a nice mask that only shows areas that are green, and has much more recent data.  For example, the current Near Real time NDVI shows greenness only in the mountains and areas of mesquite that have greened up, shows brown over much of the grasslands.  This is what I observed driving through the area: it has already browned out.  This tool allows visualize of current state of greenness on the landscape.

The difference a few weeks can make for springtime greenness.  Note the difference along I-17 from Cordes to Flower Pot.

MODIS NDVI (Near Real Time 8 Day) 4/22-5/7

QuickDRI (updated 5/6) is still showing "improvement" in drought stress around Congress and South of Cordes lakes, but NDVI (above) shows no greenness there.  I think it could be mesquite leaf out, but interesting that NDVI NRT doesn't show it.  Both maps continue to agree that the area around Yava still looks good.  QuickDRI shows "stress intensification" in the Bradshaw and Mingus  mountain areas that NDVI NRT shows as green.  Both could be true.  QuickDRI shows "improvement" in Chino Valley, an area that NDVI NRT doesn't show any greenness.  This area is still somewhat greening up, so QuickDRI may be more accurate there.

QuickDRI (updated 5/6)

Phenology and Accumulated Precipitation

Most areas are below normal 90 day precipitation, except a small area around Perkinsville.  This area doesn't show up as being anomalously green, or having any greenness in NDVI NRT, or having lower stress in QuickDRI.

Feb-May rainfall

Based on AGDD, it is possible that this area is still too early in Spring and needs more time to green up.  

The area around Congress has received some moisture in the last 60 days, but it may not be enough to compensate for the low rainfall in February, or the high temperatures and complete lack of precipitation over the last 30 days.  

March-May rainfall

April rainfall

The Knife Edge of Spring

"To what purpose, April, do you return again?

Beauty is not enough.

You can no longer quiet me with the redness

Of little leaves opening stickily."

-from Spring by Edna St. Vincent Millay

In AZ, the spring green up of grasses and trees makes use of a narrow window of time between declining winter moisture and increasing summer heat.  Our redbud trees blooms for three or four days (this year, from April 26-29), the lilac bushes hardly last much longer, and the spring green up of weedy lawns is over by the end of May.  June is the dry season in Arizona.  June is when spring dies.

The knife edge of spring in Arizona can be seen in the biomass production.  For example, the Rangeland Analysis Platform shows that peak spring growth in Dugas, AZ in 2020 lasted approximately 3 weeks, from 4/1 to Earth Day 4/22.  By May, the growth of the annual green up was already in freefall.  More examples can be seen in this previous blog post using RAP to investigate biomass production variability from year to year.  

Phenology Mapping

The National Phenology Network's Visualization Tool can be used to follow the spring green up via Accumulated Growing Degree Days (AGDD), which work by adding up all of the days and temperatures above some minimum threshold for growth, usually 32 F for cool season plants (winter annuals, cool season grasses, willows and cottonwoods and other early spring plants) or 50 F for warm season plants (mesquite, acacia, and other warm season trees like Chilopsis, walnut, and warm season grasses and forbs).

AGDD Details

A "growing degree day" (GDD) is calculated by subtracting the threshold temperature (T) from the average temperature for each day when the minimum temperature is above the threshold temperature of 32 or 50 degrees. 

Average T = (Maximum T - Minimum T)  / 2

GDD = Average T - Threshold T

 Accumulated growing degree days (AGDD) simply adds up all of the GDD since the beginning of the year.

AGDD = GDD (January 1) + GDD (January 2) + … + GDD (yesterday)

To use the NPN Visualization Tool for AGDD, choose Map>Base Layer>Category: Daily temperature accumulations>Layer:Current Day.

AGDD Example - 32 F

The figure below shows AGDD around Prescott, AZ from a threshold temperature of 32 as 5/2/24.  Most of the map shows AGDD of about 2,000; since there have been about 120 days since the beginning of the year, that works out to an average daily temperature of 48 degrees F (2,000/120 + 32 =  48).  Of course, some areas have been warmer than that and some have been cooler:  

Phenology AGDD from 32 F 

1,600 - cottonwoods leafed out (Prescott)

1,800 - still winter grasses not green (Kirkland junction)

2,200 -  annual grasses very green, early spring wildflowers blooming (Dugas)

2,245 - mesquite not leafed out yet, annual grasses still somewhat green (Yava)

2,500 - mesquite leafed out, annual grasses brown (Date)

2,800 mesquite flowering (Congress)

AGDD Example 50 F

Or maybe a 50 degree threshold better shows mesquite and grass green up? The average daily temperatures, of course, are the same, but the different threshold yields much lower AGDDs, mostly in the low 100's.  On this map, light green area are grasses already brown and mesquite leafed out, green areas actually are green fields of annual grasses, whereas white and blue are areas where willows, cottonwoods, and elms have leafed out, but herbaceous plants are just barely getting started.

Phenology AGDD from 50 F 

240 - oaks turning brown (Kirkland)

350 - mesquite not greened up yet, annual grasses and forbs green (Dugas)

400 - mesquite not leafed out yet, annual grasses still somewhat green (Yava)

550 - mesquite leafed out, annual grasses brown (Date)

800 - mesquite flowering (Congress)

AGDD Anomalies

The examples above of specific phenology AGDD values can be used in conjunction with NPN's Visualization Tool to predict plant growth stage.  Also, it is possible to use NPN's Visualization Tool to highlight geographic areas that may be ahead or behind the usual spring green up using the "Anomaly" visualization.  In the figure below, anomaly from 32 F AGDD, it can be seen that the Kirkland valley, Black Canyon City, and the Verde valley are behind (blue) normal phenology, whereas Prescott valley and especially the area north of Bagdad are ahead (red) normal phenology.  

"Life in itself 

Is nothing,

An empty cup, a flight of uncarpeted stairs.

It is not enough that yearly, down this hill,

April

Comes like an idiot, babbling and strewing flowers."

-from Spring by Edna St. Vincent Millay