Adams v. Adams
Adams v. Adams
Opinion of the Court
AFFIRMED.
Concurring Opinion
concurring specially.
I concur in this case because of the broad discretion accorded trial judges in dissolution cases by Canakaris v. Canakaris, 382 So.2d 1197 (Fla. 1980). However, I believe the trial judge could have awarded more of the husband’s income to the wife as alimony and child support without abusing her discretion.
Mrs. Adams was an “Army wife.” She and Mr. Adams were married eighteen years and had four children who ranged in age from eight to sixteen years at the time of the dissolution. The trial judge split the assets of the parties about fifty-fifty. She awarded combined alimony and child support equaling forty-nine percent of the husband’s net income to the wife. The trial judge indicated that even though the need for more support by the wife and children was apparent, she believed it would be an abuse of her discretion to award more than fifty percent of the husband’s net income as support.
The husband’s net income is approximately seven hundred thirty dollars ($730.00) per week. Thus, the husband has approximately fifteen hundred dollars ($1,500.00) per month to support himself. Under this decree, the wife must support herself and the four children on the same amount. Her living expenses, which include a monthly mortgage payment in the amount of seven hundred twenty-one dollars ($721.00), substantially exceed her income, even when her part-time earnings and the hoped-for earnings of the children from a paper route are included.
The equitable distribution concept that makes fifty-fifty a fair starting point for division of marital property should not apply to support as a hard and fast rule. Such a rule creates a hardship for large families such as this one, where the wife and minor children may need more than fifty percent of the husband’s net income for a limited time. Or does Florida endorse and implicitly follow the rule of the “Lion’s share”?
Case-law data current through December 31, 2025. Source: CourtListener bulk data.